Summary Bullets:

• SubCo will establish a trans-pacific submarine cable project dubbed ‘APX East’ that will directly connect Australia with mainland US.

• While Australia already has sovereign owned cables, it’s crucial that this type of infrastructure remains in domestic ownership to ensure data sovereignty is met.

Over the last few years, international connectivity strategies have largely been driven by scale – favoring bigger pipes, alternative routes, and the assumption that capacity would keep pace with demand. However, with the rise in data traffic contributed by AI, data-intensive workloads, and diminishing tolerance for outages, this is forcing carriers to rethink how international networks are designed and evaluated.

In that context, submarine network developer and operator SubCo, based in Australia, announced that it would build the APX East cable, directly linking Australia to the US by 2028. This can be viewed as a significant step forward in strengthening Australia’s national telecommunications resilience. As data continues to become a core and strategic national asset, a sovereign-owned international cable offers Australia greater control over how its critical information is transmitted, secured, and governed – reducing reliance on foreign-controlled infrastructure at a time of rising geopolitical and cyber risk. While this project is a commercial infrastructure, it will also be a nation-building digital backbone. Given cables are tied to national security and strategic importance, the Australian government should take steps to encourage local investments and ensure ownership for securing Australia’s digital future.

SubCo plans to establish a direct trans-pacific optical link connecting Sydney (Australia) to San Diego, California (US) using a 16 fiber-pair design with no intermediate landings. The system is expected to cost $500 million (AUD747 million). At an estimated length of 12,000 to 13,000 km (7,500 to 8,075 miles), the cable is expected to be the longest continuous subsea optical route in the world. The project is intended to support the rapid growth of AI infrastructure in Australia, where hyperscalers and emerging neocloud providers are expected to deploy up to 3GW of AI ”factories” in the coming years. This cable will complement the company’s existing Oman Australia Cable (OAC) connecting Perth (Australia) to Muscat (Oman), which was launched in late-2022. It is worth noting that both Vocus and Telstra (including Endeavour to Hawaii) have already built their own cables, which demonstrates that private businesses are ready to invest in the country’s digital backbone. As the importance of this infrastructure grows, ensuring continued domestic ownership of future investments is critical.

As highlighted in GlobalData’s recent subsea cable report (AI Growth Collides with Infrastructure Limits, December 19, 2025), governments are increasingly intervening in the development and operation of cable systems due to digital sovereignty concerns. These concerns directly affect government services, defense, healthcare, and other critical industries. As a result, it’s becoming increasingly important that Australia exercises greater control over how sensitive data is routed and protected, reducing exposure to foreign jurisdictions, commercial priorities, and strategic interests of foreign-owned hyperscalers. In an era of heightened cyber risk and geopolitical uncertainty, ownership and control of digital pathways are as important as capacity.

Governments already co-invest in critical infrastructure such as roads, power, ports, and defense assets. Subsea cables should now be recognized with the same category. The government could show support in various ways from co-investment, underwriting – it could even have long-term capacity commitments. The goal is not to remove private capital; rather, targeted public participation can help ensure that national security, resilience, and data sovereignty are met. As the window narrows for Australia to shape its digital future, projects like APX East will determine who controls the arteries of the nation’s digital economy.

AI has been the rage for at least three years now, first just generative AI (GenAI), and now agentic AI. AI can be pretty useful, at GlobalData we’ve done some very cool things with AI on our site. Strategic things, that serve a defined purpose and add value. The use of AI at GlobalData hasn’t been indiscriminate – it has been thought through with how it could help our customers and ourselves. Even this skeptical author can appreciate what’s been done.

But a lot of what is happening out there with AI is indiscriminate and doesn’t attack problems in a prescriptive way. Instead, it is sold as a panacea. A cure for all business and IT ills. The claims are always huge but strangely lacking in detail. It’s particularly true for agentic AI where only in the last month managed to get MCP into the Linux Foundation as a standard. The security issues of agentic AI are still largely unaddressed and certainly not addressed in any standardized fashion. It’s not that agentic AI is a bad idea, it’s not. But the way it’s being sold has a tinge of irrational hysteria.

Sometimes when a vendor introduces a new capability that proudly uses agentic AI, it’s not clear why that capability being ‘agentic’ makes any difference than just AI. New AI features are appearing everywhere, with vendors jamming Ai in every nook and cranny, ignoring the privacy issues, and making it next to impossible to avoid or turn off. The worst part is often these AI features are half-baked ideas implemented too quickly or even worse, written by AI itself and all of the security and code bloat issues that ensue.

The prevailing wind, no scratch that, the hurricane force gale in the IT industry is that AI is everything, AI must be everywhere, and *any* AI is good AI. Any product, service, solution, or announcement must spend at least half of its content on how this is AI and how AI is good.

AI *can* be a wonderful thing. But serious enterprise IT administrators, coders, and engineers know a few things:

1. In a new market like AI, not every company selling AI will continue to sell AI. There will be consolidation, especially in an overhyped trend. Vendors and products will disappear.2. Version 1.0 hardly ever lives up to its billing. Even Windows wasn’t really minimally viable until 3.1. 3. Aligning IT/business value received vs. costs to implement/continue is a core component to the job.4. The bigger the hype, the bigger the backlash.5. The bigger the hype, the bigger the fear of missing out (FOMO) amongst senior management.6. The problems are in the details, not in the overall concept.

So let’s all slow our roll when it comes to AI. More focus on what matters, what can *demonstrably* provide value vs. what is claimed will provide value. Implementation costs as well as one year, three year, and five year costs. Risk assessment from a data privacy, cybersecurity, and regulation standpoint. In short, a little bit more due diligence and a lot less FOMO. AI is going to happen; that’s not the issue. The issue is for enterprises to implement AI where it will help, rather than viewing it as a panacea for all problems.

Summary Bullets:

• DXC has created AdvisoryX, a global advisory and consulting group to help enterprises scale their AI deployment and create business values.
• Besides leveraging AI to drive innovation with customers, DXC is also adopting AI internally to gain productivity and embedding AI into its services.

DXC has made significant progress expanding its AI capability throughout 2025. The company recently launched AdvisoryX, a global advisory and consulting group designed to help enterprises address their most complex strategic, operational, and technology challenges. This is a positive move that can help enterprises accelerate their AI journey and achieve better outcomes. While enterprises are eager to implement AI, most of them do not have a well-thought-out strategy and operating model, or the necessary expertise to deploy AI successfully. What happens typically is departments working on siloed projects, without organization-wide collaboration, resulting in inefficiencies and governance issues. DXC’s AdvisoryX helps to overcome key challenges from getting started to the full lifecycle management.

DXC’s AdvisoryX offers five integrated solutions, which include DXC’s AI Core (i.e., the foundation including data, modeling, governance, and platform architecture); AI Reinvent (i.e., proven industry use cases across human-assisted, semi-autonomous, and autonomous operating models); AI Interact (i.e., redesigned workflows for collaboration between people and AI); AI Validate (i.e., continuous testing, observability, and governance); and AI Manage (i.e., production operations and lifecycle management).

With AdvisoryX, DXC has strengthened its position as a partner for AI innovation and allows the company to counter efforts by competitors to drive mindshare in the AI space. This is also a buildup of efforts the company has undertaken to develop its AI capabilities. In October 2025, DXC announced Xponential, which is an AI orchestration blueprint that has already been used by global enterprises to scale AI adoption. Xponential provides a structured approach to integrating people, processes, and technology. There are five independent pillars within the blueprint, including: ‘Insight’ (i.e., embedded governance, compliance, and observability); ‘Accelerators’ (i.e., tools to speed up deployment); ‘Automation’ (i.e., agentic frameworks and protocols); ‘Approach’ (i.e., collaboration of skilled professionals and AI to amplify outcomes); and ‘Process’ (i.e., delivery methodology). The company has indicated Singapore General Hospital as a client who has leveraged DXC’s expertise to develop the Augmented Intelligence in Infectious Diseases (AI2D) solution. This solution helps to guide antibiotic choices for lower respiratory tract infections with 90% accuracy and improve patient care while combating antimicrobial resistance.

In April 2025, the company introduced DXC AI Workbench, a generative AI (GenAI) offering that combines consulting, engineering, and secure enterprise services to help businesses worldwide integrate and scale responsible AI into their operations. The company has named Ferrovial, a global infrastructure company, as a customer reference that has leveraged DXC AI Workbench. The customer developed more than 30 AI agents making real-time decisions to optimize field operations, elevate safety measures, manage business knowledge, analyze competition, and assess regulatory impacts.

The company has identified AI as a key driver for business growth. Equally, it sees opportunities to apply AI internally for productivity and to gain experience from the technology. For example, DXC’s finance teams have used AI to transform back-office activities and eliminate repetitive processes; its legal department uses AI for legal research, drafting, and document preparation; and its sales and marketing teams deploy AI to automate workflows, generate proposals, etc. The company is also leveraging AI to enhance its service offerings. For example, it has partnered with 7AI to launch DXC’s agentic security operations center. These examples underscore DXC’s experience and capability in creating business values with AI.

That said, DXC is not the only systems integrator using AI to drive a with an AI advisory and consulting practice. While the company is showing traction and building customer case studies, competitors are also moving rapidly to engage clients in AI innovation and implementation. Accenture, for example, has nearly doubled its GenAI bookings in FY2025 to $5.9 billion from FY2024 and tripled its revenues to $2.7 billion. Tata Consultancy Services has also created a dedicated Tata Consultancy Services AI business unit, and it is driving transformation through a ‘responsible AI’ framework.

While DXC has introduced AdvisoryX, there is a lack of details in terms of the size of the group, areas of focus (e.g., geographical regions and industry sectors), and the assets underpinning its five integrated solutions. This makes it harder to see the differentiation against other providers that are also scaling their AI consulting practice. The company should also consider following up with announcements to highlight how AdvisoryX has made a difference in helping clients achieve their AI goals. This can be across the five integrated solutions, especially AdvisoryX’s AI Reinvent and AI Interact, which address many challenges related to human collaboration and business processes.

It is still early days in the adoption of AI, and competition in the AI space will become more intense. To stay competitive, service providers need to continue to strengthen their ability to help clients align business goals, industry-specific processes and challenges; enhance their AI platforms and tools; and expand their AI partner ecosystem. They also need to build more customer case studies to highlight success and gain credibility.

Summary Bullets:

• Mitel CX 2.0 raises Mitel’s stature in the contact center space and its competitive standing in general.

• Mitel has continued to blossom since completing the acquisition of Unify just over two years ago.

Mitel has launched Mitel CX 2.0, an upgrade to its Mitel CX customer experience (CX)/contact center platform introduced in March 2025. Mitel CX 2.0 is significant for the impact it has on Mitel’s position in the contact center space and the role it plays in Mitel’s evolution as a company.

GenAI virtual agents reside at the core of Mitel CX 2.0. They complement human contact center agents, handling basic requests while funneling off more complex ones to the employee best-equipped to handle them whether they reside within the contact center or back-office. The virtual agents also tackle workflows on behalf of human agents such as ordering items, issuing trouble tickets, sending customer notifications, or initiating approvals. Mitel CX 2.0 can be deployed in private cloud, hybrid, or on-premises environments.

The arrival of Mitel CX 2.0 serves as a contemporary signal of the market momentum Mitel has been steadily generating since completing its Unify acquisition in October 2023.

That acquisition more than doubled Mitel’s customer base to over 75 million, broadened its geographic footprint to north of 100 countries, and married its strength serving mid-market customers with Unify’s expertise in the large enterprise space. Since that time, Mitel has reoriented its go-to-market stance from ‘all things to all people’ to a solutions-led approach. Mitel has also restructured its finances by successfully emerging from Chapter 11 bankruptcy proceedings. Most significantly, the company has reinforced its governance and leadership by installing a fresh board of directors and onboarding a new CEO, Mike Robinson, who succeeds Tarun Loomba after roughly four years at the helm. Robinson is charged with tapping his experience guiding companies through post-restructuring phases to sustain Mitel’s corporate progression.

In addition to being a notable step in Mitel’s metamorphosis, more importantly it marks a meaningful leap forward for the company in the contact center space. In the last few years, contact centers have profoundly transformed, steadily yielding to the broader concept of ‘customer experience’. Contact centers are converting from featuring live agents to also including AI agents, from reactive to proactive, from transaction-oriented to relationship-oriented, and from generic to deeply personalized. Mitel and its rivals continue to implement capabilities to help their customers make the transition.

With respect to rivals, Mitel CX 2.0 meets but does not exceed what is offered by the likes of Cisco, Zoom, and RingCentral. However, that does not erase the fact that Mitel is a markedly different company than just two years ago, one that continues to mature and blossom. With a new CEO installed, Mitel has officially launched the next chapter in its transformation. To be continued…

Summary Bullets:

• Cisco AGNTCY will be key for infrastructure multi-agentic AI frameworks leveraging security, identity, and interoperability.

• Solo.io highlighted progress in three high-profile agentic AI projects: Kagent, Agent Gateway, and Agent Registry.

The industry’s fall technology conferences have drawn to a close. Dominant themes included agentic AI integration, ecosystem partnerships to fill AI gaps, observability consolidations, and emerging open-source software (OSS) alternatives for enterprise developers.

One of the industry’s mega, multi-vendor conferences, KubeCon, held in Atlanta, Georgia (US) in November 2025, promoted each of these themes in response to the ongoing complexities surrounding Kubernetes-enabled digital transformations. This blog will focus on OSS technology advancements in particular. (For analysis on broader app modernization and KubeCon themes and news, please see: KubeCon Atlanta 2025: Agentic AI Era Gains Momentum via OSS and Power Partnerships, December 10, 2025).

Open-source technology remains an important approach among developers and DevOps team members in general for several reasons, including access to affordable community-driven collaboration and the experimentation of emerging AI technologies; providing flexibility and customization to agentic AI development tools; easing feature and systems integrations; and streamlined deployment of modern apps across distributed environments.

Over the past year, early agentic OSS tools became available to enterprise developers, such as Microsoft AutoGen, conversational agents; Google’s agent development kit, a Python-based tool for creating AI agents; and LangChain, framework for building LLM-powered apps and agents.

Multiple noteworthy OSS agentic AI events and projects were rolled out this fall and during KubeCon. Of particular interest among DevOps teams, cloud-native networking company Solo.io highlighted its progress in three high-profile agentic AI projects: Kagent, an agentic AI framework for building and running production agents in a cloud-native environment, including security and observability features; Agent Gateway a networking component which complements MCP and A2A protocols, to securely observe enterprises’ entire AI ecosystems; and Agent Registry, a centralized repository for AI applications and agents.

Other noteworthy Kubernetes and agentic OSS projects, which DevOps teams will be closely following in 2026, include:- Cisco AGNTCY, an infrastructure multi-agentic AI framework leveraging security, identity, and interoperability.- Cisco OTel Injector, for zero-coding, automation instrumentation of application observability data.- AIBrix and llm-d, for streamlining the building/scaling process associated with inference systems.- Kube Resource Orchestrator (KRO), a collaboration between AWS, Google, and Microsoft to abstract infrastructure complexity for developers to enable self-service, auto-provisioning of the underlying application stack.- Open Source Project Security (OSPS) Baseline framework for tiered security controls. -OpenFGA, providing developers with fine-grained authentication controls.-Cedar OSS, an Amazon sandbox project to enforce fine-grained access controls.

Progress in these OSS efforts among various infrastructure and app platform participants will dominate investment and news in 2026, as technology providers seek to improve customers’ business transformation requirements.

Summary Bullets:

• Boomi has developed a platform to help connect systems, manage data, and deploy AI agents more effectively.
• Boomi is expanding its customer base and partner base in Asia-Pacific; adding global systems integrators will help to drive penetration in the large enterprise segment.

Boomi highlighted at its Boomi World Tour event in Sydney (Australia) that without connectivity, context, and control, there will be no business impact. This epitomizes the challenge for businesses as they continue to pursue agentic transformation, especially with the recent focus on various AI technologies to drive new operating and business models. As enterprises shift their focus toward agentic AI, they often look at the tasks they can automate with AI agents.

However, the bigger picture is about business impact: Businesses should focus on reimagining their workflows and business operations. This requires communication between systems and application programming interfaces (APIs), which is the backbone for communications between enterprise systems connecting applications, data, and AI agents. The ability to extract data across an organization is key as it adds context for decision-making. Moreover, it is essential for businesses to have the right control over their integration, use of data, and the access rights of AI agents.

It is against this backdrop that Boomi has developed its platform to enable effective management of integration, APIs, data, and AI agents. While Boomi’s business has been anchored on integration and automation, it has made significant investments and efforts to enhance data management, API management, and AI agent management. For example, the acquisitions of Rivery and Thru have added data integration and managed file transfer capabilities respectively. While Boomi now has a compelling API management solution, it has added an AI gateway that sits between applications and AI model to check AI requests, manage costs, apply security rules, and route requests to the right model. These are crucial functions to manage the costs of using AI models that use token-based pricing, provide a layer of security to prevent prompt injection, and process streaming responses.

Boomi’s Agentstudio provides AI agent lifecycle management, allowing users to create, govern, and orchestrate agents. Its customers have deployed over 50,000 agents and nearly 350 AI-powered solutions on Boomi Marketplace. The company continues to enhance Agentstudio to meet customer demand. In particular, Boomi is supporting context engineering (e.g., GraphRAG), open-source (e.g., MCP client/server), agent governance (e.g., multi-provider support, FinOps), management of AI agent access (e.g., delegated authorization), and more. All these capabilities – from AI agent management to integration & automation, data management, and API management – are now available through a single Boomi Enterprise Platform.

Boomi’s platform and its AI approach are well-received by enterprise customers. For example, Greencross Pet Wellness Company, Australia’s largest pet wellness organization, leverages Boomi Enterprise Platform to support data integration and business transformation across its inventory systems, HR platforms, warehousing, and digital services. Boomi’s platform also enabled the company to develop its digital pet profile platform, which allows customers to build personalized profiles, receive timely reminders for treatments, view tailored product recommendations, and access relevant services based on their pet’s needs.

Serco Asia-Pacific is another customer in the Asia-Pacific region that has deployed Boomi’s platform and achieved productivity with Boomi’s AI capability. In particular, the company has reduced dramatically the time for a developer to build and document an integration, using Boomi’s DesignGen (creating integration with prompts) and Scribe (generating summaries, descriptions, and documentation) AI agents. Serco now sees Boomi as a crucial partner for its digital transformation, leveraging Boomi Enterprise Platform for integration as well as data management and API management.

Partners play a part in promoting Boomi’s solutions while helping enterprises transform their business. Example of partners in Asia-Pacific include Adaptiv, Atturra, and United Techno, who have been leveraging Boomi for their data and integration business. Atturra is a business advisory and IT solutions provider in Asia-Pacific with a strong industry focus (e.g., logistics, education, financial services, and more). Adaptiv is an ANZ provider of data integration, analytics and AI services. United Techno has a stronger focus on data management and AI solutions especially within the retail, e-commerce, and logistics sectors.

Boomi also engages global systems integrators to promote its solutions to large enterprises for their digital transformation. The company formed a strategic partnership with DXC in August 2025, focusing on application modernization and agentic AI. Particularly for AI projects, consulting services can make a difference in helping enterprises drive more successful outcomes. Systems integrators have been strengthening their consulting capabilities aligned to industry verticals, which can be pivotal in helping companies reimagine their business workflows, implement the right solutions, and measure the business outcomes effectively. They also have existing relationships with many large enterprise customers. Ultimately, the enterprise technology environment is becoming more complex with the need to manage an ecosystem of different technology vendors. Boomi wants to be the glue connecting different technologies, but it also needs partners to bring it all together. Continuing to expand its go-to-market partners and adding more global/regional systems integrators is crucial to penetrate the large enterprise segment across Asia-Pacific.

Summary Bullets:

• Microsoft Teams is front and center at Microsoft despite a very limited number of related announcements made at the event.

• Pairing team collaboration and productivity tools provides Microsoft a distinct competitive position.

Microsoft has officially closed the doors on its annual ‘Ignite’ event, a showcase of enhancements across the entire Microsoft portfolio. Only a handful of Microsoft Teams-related announcements were made, giving the impression that Microsoft Teams has taken a back seat to other Microsoft initiatives. In reality, much the opposite is true. The features unveiled were merely the tip of the iceberg, a small subset of a lengthy and diverse list of improvements that appeared in a Microsoft Teams blog.

While the actual depth of Microsoft Teams introductions might have come as a surprise, what shouldn’t be a surprise is that the introductions were infused with AI. Some examples bear this out.

The user interface for Microsoft Copilot in Teams AI-powered assistant is being unified across chats, channels, and meetings. Deploying a unified front across different functions is reminiscent of the familiar menu structure that cuts across Microsoft’s productivity apps such as Word, Excel, and PowerPoint. The power of this approach allows users to quickly learn a new app based upon their experience with an app they are already familiar with. It’s interesting to note that Microsoft is taking knowledge gained during its ‘Microsoft Office’ era and applying it to ‘modern’ times in the form of the AI-infused Microsoft Copilot. On top of the updated interface, Microsoft Copilot in Teams can now also analyze chat history, meeting transcripts, and calendar content and generate recaps, rewrite messages, and surface insights; this experience is generally available for chat and channels and is rolling out to public preview for meetings.

Providing the ability to collaborate with external users is a growing trend. Microsoft has launched a public preview of several features that enhance interaction between Microsoft Teams users and vendors, clients, partners, and the like. Among other features, Microsoft Teams users can launch a chat, share a file in a chat, and view and respond to Microsoft Teams activity in other accounts and organizations.

A persistent collaborative space is now available from within Microsoft Teams chat and channels, helping organize information and co-create content. The space comes in the form of two features, ‘Pages’ in channels and ‘Notes’ in chat. Taken together, the features mimic the Zoom Docs capability from Zoom. So, although Microsoft is not scoring points for originality, it is introducing some very valuable functionality.

One especially intriguing aspect of Microsoft Ignite 2025 lies beyond the inventory of enhancements revealed, exposing something fundamental to Microsoft. Microsoft is taking a holistic approach to providing team collaboration capabilities. That approach spans Microsoft Teams software, device hardware such as video bars, and security, for instance, blocking files that pose a security risk such as executables before they reach a chat or channel. Normally such an ‘all points covered’ approach would provide Microsoft a unique competitive position, however it does not. Cisco mirrors Microsoft in employing deep lineups of software capabilities, devices, and security. Both companies are setting a tone that others will need to follow to compete in the space; rivals certainly have their work cut out for them.

Collectively, all the new features further cement Microsoft’s position as a leading vendor in the team collaboration/hybrid work arena. With AI touching multiple points of its portfolio including the latest Microsoft Ignite announcements, Microsoft has taken the ‘permeate the platform’ approach to AI adopted by competitors such as Cisco, Google, Zoom, and RingCentral. Coupled with its portfolio of ‘Office’ productivity tools, Microsoft has achieved a degree of differentiation that is largely unmatched.

Summary Bullets:

• Amdocs has broad capabilities for B2B operators.

• The solutions can accelerate their telco-techco transformation journeys across different markets.

At the recent Amdocs Analyst Conference in APAC, the company shared its latest capabilities and directions covering not only its core areas (i.e., OSS, BSS, MVNO platform, and 5G), but also emerging technologies such as AI, autonomous networks, and its integration across the portfolio. This report focuses on Amdocs’s offerings for telco B2B that can accelerate operators’ enterprise telco to techo transformation journeys.

Amdocs Portfolio for Enterprise Telecom
Enabling telcos to transform in the enterprise segment remains a key focus area for Amdocs. Amdocs CES is a leading solution for telcos digital transformation (for more, please see Digital Transformation Platforms: Competitive Landscape Assessment, July 11, 2025). It provides extensive B2B capabilities for telcos, ranging from catalog management to IoT, commerce and care, monetization, service and network automation, data, and AI. The solution can be deployed on-premises or on major hyperscale cloud environments, providing wider options for operators in managing their complex network and IT architecture. Key components of Amdocs CES include:

• Catalog: Enables operators to bundle solutions, including connectivity, products, and digital services from in-house as well as third-party providers and partners. While this is essential for SMBs, solution bundles can be positioned for larger enterprises, for example, as SD-WAN or NaaS underlay.
• Customer Engagement Platform: Provides a full customer lifecycle from marketing and sales to ordering, fulfillment, and customer support. This enhances the configure, price, quote (CPQ) process through automation and cuts down the order-to-activation time from months to days or hours. This benefits low-touch segments (SMBs) while also improving platform and self-serve portal capabilities (e.g., provisioning and change requests) for larger enterprises.
• Monetization Suite: Focuses on diverse monetization options, which includes connectivity as well as 5G services, QoS, APIs, satellites, AI, and more. This is critical for operators to capture market opportunities by driving monetization of their 5G network assets.
• Intelligent Networking Suite: An intent-based orchestration platform spanning across the network, edge, and cloud as well as inventory and assurance. This is vital for operators to accelerate their journey toward an autonomous network and strengthen their enterprise network and cloud offerings such as cloud-connect, SD-WAN, and NaaS. This enables operators to enhance network design and planning for enterprise customers especially for complex requirements, to address the growing enterprise need for agile networking and seamless integration across hybrid cloud and multi-location deployments, and to gain a competitive edge.
• MarketONE: A marketplace featuring hundreds of pre-integrated partners’ offerings, including content, applications, digital services, IoT, and industrial applications. This component is crucial for operators’ platform strategy, enabling adjacent services and providing wide vendor options to meet diverse market needs. For example, SASE, firewall, private 5G, IoT, and cloud services are integrated with NaaS services.
• amAIz Suite: Amdocs’s AI/GenAI and data platform that touches all other components. AI and analytics have been embedded across Amdocs’s entire portfolio, including Catalgo, Customer Engagement Platform, Monetization, and OSS. It enables workflow automation, zero-touch processes, an AI assistant, and analytics. This enables operators to address market demand more efficiently (e.g., personalizations) as well as gain a competitive advantage through AI-driven use cases.

Besides, Amdocs also offers a comprehensive services portfolio – Amdocs Studios, designed to bridge the experience, outcomes, and technology gaps. Amdocs Studios provides a range of service capabilities spanning consulting, experience design, data and AI, cloud services, and quality engineering. The service layer is essential for B2B operators to address not only their legacy infrastructure and systems, but also drive change management to overcome operators’ legacy cultures (e.g., siloed organization) that can slow down innovations. Amdocs Studios is shifting its services layer to agentic services to enable key oeprational enterprise workflows such as application modernization, cloud migration, and quality engineering.

Accelerating Enterprise Telco-Techco Transformation
Operators have been expanding their portfolio beyond connectivity for years to meet enterprise demand and to offset declining legacy service revenue. GlobalData forecasts ICT markets (e.g., cloud, data center, security, AI, and IoT) to grow at strong double-digit CAGRs Further, telcos are also well-positioned in the market. GlobalData research indicates that over half of enterprises prefer telcos as their ICT providers due to brand reputation and existing relationships. While leading operators like SK Telecom, Singtel, NTT, have advanced their transformation, many telcos in emerging markets (e.g., ASEAN) are still in the early stages.

Nevertheless, Amdocs’s capabilities can address telcos across the entire telco-techno transformation journey. Most advanced operators have already developed platform and marketplace capabilities and have integrated enterprise ICT offerings (e.g., network, cloud, security). They can also leverage Amdocs Monetization Suite to fully capitalize on their 5G-Advanced networks such as with network slicing and APIs. Besides, these operators can alsoe leverage Amdocs amAIz Suite to boost operational efficiency through workflow automation. This can accelerate operators’ solution development and time-to-market. Meanwhile, for emerging telcos, capabilities like Amdocs Catalog and Amdocs MarketONE offer higher impact. Many operators in ASEAN are aggressively expanding their ecosystem, but most services remain silo for enterprise customers. Amdocs MarketONE enables operators to address integration challenges across multiple services. This can drive operators’ operational efficiency and customer experience. Besides, given that connectivity is still a key growth driver, Amdocs Catalog is key to developing an innovative bundling strategy.

Conclusion
Amdocs’s comprehensive Amdocs CES and Amdocs Studios portfolios provides the necessary technological and service foundation to empower operators across the entire telco-to-techco transformation stages. By addressing critical areas like ecosystem integration (via Amdocs MarketONE), 5G monetization, and AI-driven automation, Amdocs is well-positioned as a key strategic partner for operators to accelerate their transformations and to capture high-growth enterprise ICT opportunities.

Summary Bullets:

• IBM leads the quantum compute (QC) race with its 156-qubit machine leading, yet the technology is also causing significant cybersecurity concerns.

• While IBM is driving IBM Quantum Safe, investments in other areas are also important for addressing the ‘Known, Unknowns’ with managing emerging security threats.

IBM leads the QC race with its 156-qubit machine leading major rivals such as Google, Fujitsu, and Rigetti.

This latest machine can dimensionally space of 2 to the power of 156 states at the same time, which equates to a 47-digit number. QC is less of a novelty and gradually becoming commonplace. Unlike conventional computing, QC utilize the quantum mechanical principle of superposition, which stipulates that the quantum qubits, ‘qubits’, can be simultaneously in the states 0 and 1 and everything in-between unlike classical computers, which have only two possible binary states of 0 and 1. And through a process of entanglement, QC can see relationships between qubits, impossible on classical computers. This fresh approach brings massive parallelism to computing and promises to accelerate advances research into domains such as science and medicine as well as accelerating AI research.

The Threat to Cyber Defenses
The major discussion however has been the threat to cybersecurity. Namely, the fear that RSA 2048, a 2048-bit encryption key (a top standard for cryptography), for example, could be broken by Cryptographically Relevant Quantum Computers (CRQC) through massively parallel factorization using Shor’s algorithm on a day that is often referred to as “Q-Day”. This would take the best classic computer perhaps a billion years to do and speculatively months or days for QC. Who knows? There is fear that QC can escalate cyberattacks through fraudulent authentication accessing data, systems and applications. It can forge digital signatures, fake records, and compromise blockchain assets. And while nothing is on the market today, cyber adversaries can potentially steal sensitive data now as well as store and decrypt sensitive data when QC is mature.

IBM’s Approach for IBM Quantum Safe
The conversation is recognition that QC is evolving much faster than any previous time. IBM estimates its superconducting QC are between 1,200x to 70,000x cheaper to run, and between 400x to 2,000x faster than ion trap quantum computers. And while IBM is ahead in terms of having the largest computers, it is working with other businesses, government, and regulatory bodies to raise awareness. It is also looking to standardize quantum resistant algorithms. IBM, for example, played a leading and foundational role in three of four proposed NIST standards for post quantum cryptography (PQC). There is also quantum key distribution (QKD) to ensure the secure exchange of information between two or more parties continues in the quantum world. NIST has a 2030 recommendation for new quantum resistant cryptography to be in place. The EU, for example, is coordinating its Quantum roadmap. The switch over to post quantum is likely 2035.

While the impact of securing infrastructure and key distribution for all scenarios – Quantum Safe – will be far reaching, the IBM play is leadership in building the fastest quantum computers, including the processors, hardware, software, and middleware. This is also the experience in supporting industries, especially those regarded as critical national infrastructure (e.g., telecommunications, energy, utilities, banking, and payments), which tend to be highly regulated, rely on legacy systems, and require extra levels of security protection for compliance considerations.

IBM is working with enterprise on mapping cryptographic footprint and assets across systems and applications (e.g., source code, libraries) and network protocols (SSL and TLS). This is to better understand vulnerabilities, dependencies, current posture, before understanding where and how to apply IBM Quantum Safe principles. This is often done to align with compliance laws specific to industry verticals, including critical infrastructure. The company has 160,000 global consultants, has vibrant partner ecosystem working with the likes of Palo Alto Networks, for example, on threat detection and management. The vendor also has a play for quantum readiness.

While leading in overall quantum R&D is important, investments in adjacent many areas such as hybrid cloud, agentic AI, including multi-agent orchestration, will also have big implications for security as much as everything else. In the era of disaggregation, multi-domain experience and optionality will be important for tackling multiple issues, including the challenges with quantum. IBM is supporting its customers goals of being rigid on security, yet flexible on IT strategy and business agility.

Summary Bullets:

• Telecom companies are facing many challenges moving beyond their legacy business and adopting digital solutions including AI to drive business transformation.
• Amdocs is helping telcos to drive transformation with AI and its consulting-led services play a key role to accelerate the process from customer engagement to backend operations.

Telecommunications companies (telcos) are in various stages of transforming their businesses. The industry as a whole faces several challenges that have hindered progress.

These include regulations (e.g., to meet quality of service, data privacy, consumer protection, etc.); the need to constantly invest in their networks (e.g., upgrading mobile networks to 5G and 5G-A), legacy systems, and processes (including IT, network, and operations support system); and growing competitive pressures from traditional competitors to new telco start-ups and disruptive players (e.g., over-the-top providers, cloud providers, LEO satellite companies, etc.). They also have a huge workforce that may not be ready to transition into new technology areas such as AI, data science, cybersecurity, and cloud computing. While telcos’ leadership teams are well aware of the opportunities of emerging technologies, they have to take a more holistic approach in transforming the business, not just adding new digital capabilities. They need to reimagine their business (i.e., define the core business and operating model), right-size the organization with the right talent, adjust the company culture, and ensure effective change management.

This means opportunities for technology services providers including consulting firms, systems integrators, and other telco vendor partners to help telcos modernize their technology and transform their business. Amdocs is a key player within the telco partner ecosystem. It already serves 350 communications and media providers across more than 85 countries, including many tier-1 telcos (e.g., AT&T, BT, Telefonica, and Globe) with long-standing relationships. The company offers a range of products for catalog management, commerce and customer care, billing/monetization, network deployment and optimization, service & network automation, and more. Amdocs has also embedded AI (including GenAI and agentic AI) into its solutions. For example, its customer engagement platform is a customer relationship management (CRM) solution to deliver AI-driven customer journeys and personalized services serving both consumer and B2B customers. This is developed in partnership with Microsoft, leveraging Microsoft Dynamics 365 and Microsoft Azure, verticalized for telecoms by Amdocs. Amdocs amAIz suite lays the foundation for telco data management, AI control and governance, and AI application and AI agent deployment. More importantly, since Amdocs is already embedded in telcos’ operations, the company has a deep understanding of the telco business and operational requirements. This places the company in a better position to help telcos adopt AI, particularly agentic AI, to automate workflows (from IT operations to business operations and network operations) to deliver the desired business outcomes.

However, due to the aforementioned challenges, many telcos are facing in transforming their business: They are not merely looking for more technologies but partners that can help them drive business outcomes. Many technology vendors choose to partner with service providers to help telcos close their capability gaps, recognizing the need to work across technologies from different vendors, which may require systems integration. Amdocs has taken a different approach by building a more comprehensive set of services to support telco customers, which it can also extend to customers in more verticals over time. Besides services to support network management and operations, the company is also helping telcos to transform various aspects of their business from CX to the modernization of backend systems. This is through Amdocs Studios, which has broad expertise across cloud services (e.g., strategy, migration, and operations), data and AI (e.g., data strategy, AI & analytics, and GenAI), and consulting services (e.g., experience design, product development, cybersecurity, and risk management). Amdocs is developing agentic services to support operational aspects of the Amdocs Studios’ main practices, including application modernization, data modernization, quality engineering, and more. The company has an extensive partner ecosystem to deliver the right outcomes for customers. For example, it has strategic partnerships with AWS, Google Cloud, Microsoft Azure, Oracle, and Red Hat to offer cloud services.

Consulting services in particular are crucial in aligning technologies with business outcomes and helping drive change especially in using cloud, data, and AI to improve customer experience, employee experience, and operations experience (the processes involved to facilitate the interaction between a customer and a brand). Successful implementation will require enterprises to focus on the experiences they want to deliver and the brand image they want to establish. In particular, a human-centered design is crucial especially in AI initiatives to promote trust and focus on the benefits to enhance human capabilities (not to replace them).

Amdocs has invested significantly to develop experience design capabilities, which will be pivotal to compete with other service providers. Some global systems integrators also have strong creative design consulting capabilities (e.g., Accenture Song, Deloitte Digital, and TCS Interactive). As businesses are adopting digital solutions to drive business and operational changes, it is imperative for service providers to have an industry-focused approach for their go-to-market. This is already the case for most global systems integrators. While Amdocs does not have the scale of some of the largest global systems integrators, it has deep expertise in the telco sector. However, the company will continue to face stiff competition from systems integrators, especially Accenture, Infosys, and HCLTech, which have made acquisitions, high-profile customer examples, and extensive partnerships with vendors important to telcos.

Summary Bullets:

• The combination of omni-channel capability, effective data management, and AI will drive better customer experience.
• As Twilio’s business evolves from CPaaS to customer experience, the company focuses its product development on themes around trust, simple, and smart.

The ability to provide superior customer experience (CX) helps a business gain customer loyalty and a strong competitive advantage. Many enterprises are looking to AI including generative AI (GenAI) and agentic AI to further boost CX by enabling faster resolution and personalized experiences.

Communications platform-as-a-service (CPaaS) vendors offer a platform that focuses on meeting omni-channel channel communications requirements. These players have now integrated a broader set of capabilities to solve CX challenges, involving different touch points including sales, marketing, and customer service. Twilio is one of the major CPaaS vendors that has moved beyond just communications applications programming interfaces (APIs), including contact center (Twilio Flex), customer data management (Segment), and conversational AI. Twilio’s product development has been focusing on three key themes: Trusted, Simple, and Smart. The company has demonstrated these themes through product announcements throughout 2025 and showcased at its SIGNAL events around the world.

Firstly, Twilio is winning customer trust through its scalable and reliable platform (e.g., 99.99% API reliability), working with all major telecom operators in each market (e.g., Optus, Telstra, and Vodafone in Australia). More importantly, it is helping clients win the trust of their customers. With the rising fraud impacting consumers, Twilio has introduced various capabilities including Silent Network Authentication and FIDO-certified passkey as part of its Verify, a user verification product. The company is also promoting the use of branded communications, which has shown to achieve consumer trust and greater willingness to engage with brands. Twilio has introduced branded calling, RCS for branded messaging, Whatsapp Business Calling, and WebRTC for browser.

The second theme is about simplifying developer experience when using the Twilio platform to achieve better CX outcomes. Twilio has long been in the business of giving businesses the ability to reach their customers through a range of communications channels. With Segment (customer data platform), Twilio enables businesses to leverage their data more effectively for gaining customer insights and taking actions. An example is the recent introduction of Event Triggered Journey (general availability in July 2025), which allows the creation of automated marketing workflows to support personalized customer journeys. This can be used to enable a responsive approach for real-time use cases, such as cart abandonment, onboarding flows, and trial-to-paid account journeys. By taking actions to promptly address issues a customer is facing can improve the chance of having a successful transaction, and a happy customer.

The third theme on ‘smart’ is about leveraging AI to make better decisions, enable differentiated experiences, and build stronger customer relationships. Twilio announced two conversational AI updates in May 2025. The first is ‘Conversational Intelligence’ (generally available for voice and private beta for messaging), which analyzes voice calls and text-based conversations and converting them into structured data and insights. This is useful for understanding sentiments, spotting compliance risks, and identifying churn risks. The other AI capability is ‘ConversationRelay’, which enables developers to create voice AI agents using their preferred LLM and integrate with customer data. Twilio is leveraging speech recognition technology and interrupt handling to enable human-like voice agents. Cedar, a financial experience platform for healthcare providers is leveraging ConversationRelay to automate inbound patient billing calls. Healthcare providers receive large volume of calls from patients seeking clarity on their financial obligations. And the use of ConversationRelay enables AI-powered voice agents to provide quick answers and reduce wait times. This provides a better patient experience and quantifiable outcome compared to traditional chatbots. It is also said to reduce costs. The real test is whether such capabilities impact customer experience metrics, such as net promoter score (NPS).

Today, many businesses use Twilio to enhance customer engagement. At the Twilio SIGNAL Sydney event for example, Twilio customers spoke about their success with Twilio solutions. Crypto.com reduced onboarding times from hours to minutes, Lendi Group (a mortgage FinTech company) highlighted the use of AI agents to engage customers after hours, and Philippines Airlines was exploring Twilio Segment and Twilio Flex to enable personalized customer experiences. There was a general excitement with the use of AI to further enhance CX. However, while businesses are aware of the benefits of using AI to improve customer experience, the challenge has been the ability to do it effectively.

Twilio is simplifying the process with Segment and conversational AI solutions. The company is tackling another major challenge around AI security, through the acquisition of Stytch (completed on November 14, 2025), an identity platform for AI agents. AI agent authentication becomes crucial as more agents are deployed and given access to data and systems. AI agents will also collaborate autonomously through protocols such as Model Context Protocol, which can create security risks without an effective identity framework.

It has come a long way from legacy chatbots to GenAI-powered voice agents, and Twilio is not alone in pursuing AI-powered CX solutions. The market is a long way off from providing quantifiable feedback from customers. Technology vendors enabling customer engagement (e.g., Genesys, Salesforce, and Zendesk) have developed AI capabilities including voice AI agents. The collective efforts and competition within the industry will help to drive awareness and adoption. But it is crucial to get the basics right around data management, security, and cost of deploying AI.

Summary Bullets:

• Don’t use AI browsers or AI browser extensions – the loss of privacy isn’t worth the functionality.

• AI companies mean well, but the privacy implications of these products are unsuitable for enterprise or personal use.

“If you are not paying for it, you’re not the customer; you’re the product being sold.” – Andrew Lewis (blue_beetle), MetaFilter comment (2010)

It’s not news that AI is being talked about everywhere. It’s also not news that the websites and applications you use regularly are doing their level best to spy on you or obtain data that can be used internally or be sold to advertisers. Nor is it news that the state of privacy laws across the world is pretty poor, despite the EU giving its best attempt and the US pretending that three lines of legalese in a 15-page disclaimer somehow magically sets the ‘informed’ flag on users.

But the latest trend involves AI companies either creating browser extensions or, in at least one case, creating their own browser. OpenAI is touting its AI-enabled browser called Atlas, designed to both remember all activity, search that activity, chat, and do any number of AI-enhanced things. OpenAI rival Perplexity has a browser product called Comet. There are even sidebar browser extensions for Microsoft Copilot and Google Gemini. Some browsers, such as Firefox and Brave, come with an AI sidebar but uses your choice of LLM.

The first problem is an AI watching everything – your passwords, all text you type, your URLs… everything. Then that data isn’t stored locally; it’s stored with the AI. The problems here are no different than the problems with Microsoft Recall, an AI-driven search and backup feature that Microsoft released earlier in 2025, much to the consternation of pretty much everyone. All these AI companies have multiple safeguards to protect data, have stated policies on how such data can be used and where, and are being pretty upfront about how and when they use your data. They allow end users to pick and choose when the AI is available or even forget that data after a session. Companies adding these AI features to the browser are legitimately trying to make the lives of users easier with AI and protect user privacy.

They are adding other safeguards as well. OpenAI says that its Atlas AI browser cannot access other applications, download files, and cannot install extensions. Technological limits to prevent AI browsers and extensions from becoming security risks are being taken.

But giving any corporation a detailed record of all activities conducted on the internet, including every click, search, text, or picture and the metadata around it could have disastrous consequences in the long term. Hackers could gain access to the data. Governments could seize the data and use it against a populace or an individual. Companies get bought, end user agreements change, or investors could simply demand that all that personal data is monetized. If companies go out of business, what happens to the data? A fair amount of the world doesn’t have any legal mechanism to force businesses to delete data either.

Then there are the other issues, regarding security on your desktop. Social engineering or AI chat window spoofing is a real issue. That’s just the tip of the iceberg.

Every individual and every enterprise have the choice to decide whether the risks are worth the utility of having AI integrated into your browser. Everyone wants tools that work better; some of the features in AI browsers are impressive, and likely even more features will be coming. But that shouldn’t be at the expense of risking all your personal data or risking the company’s internal data, no matter how nice the tools look or how much you trusts a given AI vendor. This is about ensuring personal privacy and the data security of enterprises. Take a pass on AI browsers and AI browser extensions. Nobody would stand for being under video and audio surveillance every second and everywhere. Don’t allow the same to happen to your digital life.

Summary Bullets:

• Oracle shifts pitch from technology to outcomes, driven by AI-injected tools.

• Oracle APEXLang, slated for 2026, to modernize Oracle’s development practices.

Last week’s Oracle AI World couldn’t have been timelier, attended by customers and partners still buzzing from a corporate earnings report, which triggered the tech giant’s stock to soar based on its mounting investments in AI and cloud infrastructure.

Executive Chairman and CTO Larry Ellison’s high-level keynote speech included profound possibilities and some examples of a variety of outcomes that AI advancements can have on global enterprises. Executives continued to carry his message in other keynotes, noting the company’s shift in focus from CIOs to CEOs through conversations that emphasized outcomes versus products. For example, in one case, Oracle’s ability to apply AI-injected applications, app platforms, and data platforms to a particular healthcare clinic resulted in productivity gains, which saved individual health workers 100 minutes per day.

He and other executives further described situations involving various medical diagnostic imaging and genetic testing with examples of how AI will diagnose, treat, and cure health issues at significantly greater levels and speeds through modernized code bases, medical systems, and ecosystems.

Oracle announced new functionality across Oracle Cloud Infrastructure’s (OCI) comprehensive cloud offering, spanning its developer portfolio: AI Agent Studio, Fusion AI Agent Marketplace, and Agent Hub (preview) AI tools for business users. Oracle’s AI agent studio has been enhanced to build and deploy AI agents across the enterprise including Oracle Fusion Applications. Oracle’s new AI agent marketplace extends the company’s LLM ecosystem and third-party agent-building resources. Ellison noted that Oracle’s low-code and automation technology, Oracle Application Express (APEX), will continue to demonstrate a growing role in AI code generation of applications connected through workflows and shored up by security. Advancements will make applications developed more scalable and reliable. This led to other application development discussions throughout the week, including some on the future of Oracle APEX.

A little-known app development tool, Oracle APEXLang, shows promise in modernizing and extending Oracle’s current development practices. Set for 2026 release, the Apex extension uses a structured, file-based format to build and format Oracle APEX applications, specifically to enable app development to be integrated with enterprises’ latest digitization practices.

Oracle APEX, traditionally used in a browser-based, declarative environment over the past five years, is valued by enterprise developers for its low-code cloud service advantage, traditionally used to build apps on Oracle databases. Oracle APEXLang represents a significant shift for these traditional developers. Features include version control support (e.g., Git) and tools to adhere to CICD pipelines for improved automated test and deployment. It works with developers’ app platforms of choice including code assistants, because the new file-based approach is particularly well suited for GenAI and LLMs. Oracle research notes Oracle APEXLang is not a replacement for Oracle APEX, SQL, or JavaScript, but an enabler for defining components of applications.

Summary Bullets:

• ANS’ acquisition of Sci-Net Solutions expands its portfolio of value-added enterprise technology solutions in a highly competitive UK B2B market
• AI is a hook everyone latches on to – there are even products and solutions out there – but this is an acquisition of a service provider with current revenues

The ANS acquisition of Sci-Net Business Solutions is positioned as a complement to previous acquisitions such as Makutu as part of the ANS strategy to exploit and deliver the opportunities presented by artificial intelligence (AI). Sci-Net is an Oxford-based business solutions specialist with expertise in ERP, CRM, and cloud infrastructure solutions (e.g., 365 Business Central, Microsoft Dynamics NAV, CRM, and Microsoft Azure).

With ANS already having a strong relationship with Microsoft (Services Partner of the Year in 2024 and over 100 certified Microsoft specialists), the combination makes sense and grows the ANS talent base to over 750 including 65 technology consultants from Sci-Net. It offers opportunities to cross- and up-sell to the companies’ existing customer bases, and to continue to move up the value chain as a managed services provider (MSP).

The move also underlines some key trends in the UK marketplace. Competition remains fierce, so being able to act as a trusted advisor is becoming more important to win and retain business. At the same time, technology continues to become more complex, therefore offering a full portfolio of services ‘above and beyond’ connectivity is vital. MSPs and value-added resellers (VARs) recognize this and represent an ever-stronger force in the market as they can work closely with customers to develop technology solutions that directly address their business needs.

That is not to say that the ‘Big Three’ B2B service providers – BT, Vodafone, and O2 Daisy – do not also recognize this. All of them are positioning to become more solutions-oriented with a focus on areas like cloud, security and, increasingly, AI. They have the advantage of significant existing customer bases, deep human and partnership resources, strong brands, and nationwide fixed and mobile networks from which to deliver their services. By contrast, the likes of ANS and other VARs/MSPs can exploit their agility to differentiate themselves in the market.

It will continue to be a highly competitive market to win the custom of enterprises of all sizes in the UK, which is a tough challenge for all service providers. But it is good news for UK plc as businesses stand to benefit from innovation and value.

Summary Bullets:

• Agentic AI streamlines workflow automation and transformations.
• Application and automation platforms to integrate agentic AI capabilities in next 12 months.

Digital transformations will receive a major boost over the next 12 months following new platform integrations with agentic AI. The AI-injected solutions will significantly streamline the creation of workflow automation, which are critical to organizations moving to migrate legacy apps to cloud environments in order to realize CICD and improved application lifecycle efficiencies.

This next generation of intelligent automation will have far-reaching ramifications among service providers, from traditional PaaS players to leading automation vendors to newer telco/infrastructure providers offering managed Kubernetes services.

Business transformations have been largely stalled over the past few years due to the fact that many enterprises lack the internal expertise necessary to configure the backend integration and connectivity to enable workflows that support critical business processes. Automation leaders – including Automation Anywhere, UiPath, SS&C Blue Prism, ServiceNow, and Pegasystems – have played a pivotal role in advancing workflow automation, particularly predictable and rules-based workflows. Application platform solutions including Microsoft Power Platform and IBM Cloud Pak for Business Automation also compete in this space.

In coming months, these solutions and platforms will be equipped with advanced cognitive capabilities such as generative AI (GenAI) and agentic AI to enable dynamic business processes capable of adapting and reasoning in an autonomous fashion. This will be a welcome relief to those enterprise personas involved in back-office transactional processing where accuracy and quality of solutions are critical. They will be most inclined to rely on their trusted technology partners integrating such agentic capabilities through mature platform services.

Automation and platform leaders are only just beginning to offer the industry glimpses into their agentic AI roadmaps, having spent the last couple of years integrating GenAI into developer tools and workflow solutions. Beta versions of AI agent capabilities are starting to appear, typically in the form of prebuilt templates and ultimately agent building toolkits and agent orchestration management capabilities.

GlobalData will be closely following the slew of later conferences hosted by platform providers including IBM, Oracle, Salesforce, AWS, and multi-vendor Kubernetes/DevOps show KubeCon for advancements in this space. Similarly, IT ops teams should keep an eye out for a constantly changing ecosystem of players and partnerships in this space, which will encourage more service providers to support global companies struggling with digitization integrations.

Summary Bullets:

• AWS Singapore Innovation Hub shows the company’s shift from technology-led to business-driven, turning use cases into commercial applications.

• The F1 partnership showcases AI and cloud innovation, but also AWS’ capabilities with real-time data intensive analytics and insights.

AWS held an analyst day in Singapore, showcasing its Innovation Hub and the partnership with Formula 1 (F1).

AWS Innovation Hub

At the innovation hub, AWS demonstrated a diverse range of AI and cloud enabled use cases – from document analytics and loan processing for BFSI, to preventive maintenance and AI-driven surveillance in manufacturing. The facility also houses many other industry-specific use cases with additional use cases in the pipeline. This initiative reflects AWS’ ongoing shift from a technology-focused to a business-led engagement model. While technologies remain at the core, the company is deepening collaboration with enterprise leaders beyond IT, engaging directly with business executives and functional owners. Leadership, culture, and people are key enablers of successful digital transformation. The Innovation Hub serves as a platform for enterprises to explore and co-develop use cases tailored to their business needs.

Innovation labs are not new. Many other providers like global system integrators, telcos, and tech vendors, have been opening new facilities over the last few years. It is a proven way to drive adoption of emerging technologies through solution co-development, commercialization and ecosystem expansion. Besides, innovation labs can also strengthen providers’ brand share and enable them to gain deeper market knowledge such as understanding customers’ pain points. The use cases demonstrated at the AWS facility were innovative and promising, but most are somewhat comparable to use cases found in other providers’ facilities. But what differentiates AWS is its strong execution. Over 70% of the use cases have been brought into production. This is consistent with its strategy to expand focus on outcome-led engagements, and a strong proof point that the efforts are not just conceptual but outcome-driven.

AWS x F1

In the latter part of the event, there were sessions with executives at the track sites including a visit to the F1 Event Technical Center (ETC), sharing how the AWS and F1 collaboration is driving innovation and enabling various use cases for F1, teams, drivers, fans, and viewers. Since the partnership began in 2018, AWS has evolved from providing core cloud infrastructure to powering advanced AI solutions. Early deployments include leveraging over 1,000 AWS compute cores for computational fluid dynamics (CFD) projects to design race cars. Today, the partnership extends to AI applications including real-time insights, car performance, race strategy, issue resolutions/root cause analysis, fan engagement (e.g., hyper-personalization), game strategy, and safety and reliability.

Sports, as one of the most data-intensive industries in the world, offers an ideal testbed for real-time analytics. For example, an F1 car alone carries around 300 sensors, generating over one million telemetry data points per second with a total of 600TB across entire race. Similarly, a football match generates about 3.6 million data points. Furthermore, data from sports events are often highly fragmented (structured and unstructured) and need to be processed in real-time. Apart from F1, AWS is also an official technology partner in various major global sports events such as the NFL, PGA Tour, Bundesliga, NHL, and many other sports teams. While sports in APAC are not as big as in other regions such as the US and Europe, AWS collaborations with F1 and other sports organizations show its leadership in this industry. More importantly, it can also be seen as a powerful platform to demonstrate its broad capabilities and innovation in complex and data-rich environments.

Jaguar Land Rover, the iconic British car manufacturer has had virtually no production in its plants since the end of August 2025. A devastating cyberattack shut the company down – details on how the attack happened, who initiated the attack, and why it so thoroughly shut down Jaguar Land Rover have not been released to date. The postmortem will be an interesting read, more so to find out how much of the effect of this cyberattack was Jaguar Land Rover’s fault. No, this isn’t indulgent victim-blaming, and right now there is no proof the Jaguar Land Rover was anything but diligent. But the length of the shutdown and the secrecy does arise suspicions. Under principles of good business continuity and disaster recovery, Jaguar Land Rover should have been at least somewhat back in production by now. But analysis will really have to wait until details emerge.

This does highlight an issue that most organizations struggle with. Cybersecurity, as well as disaster recovery and business continuity, are preventative – they shouldn’t be noticed unless they are needed… or if they didn’t work. It’s hard to get satisfaction creating business continuity/disaster recovery (BC/DR) systems that you may never get to actually use. Security has a much higher profile… but ‘everything is running smoothly’ doesn’t often gain accolades.

Cybersecurity, and especially BC/DR are often pressured to compromise, for finance, for convenience, and because neither function will ever make money for the organization. Often there is a push to compare cybersecurity and BC/DR to an automotive or homeowner’s insurance policy, that they offer peace of mind. There is a better way to think about it. Think of cybersecurity and BC/DR like law enforcement thinks about bomb squad units. Bomb squad units get all the training and practice they want. Bomb squad units are encouraged to get the latest training, learn the latest advances, and to keep their equipment as up to date as possible. Nobody thinks that the bomb squad has it easy when they render an explosive safe, or in the best of times are not called on. Nobody suggests that the bomb squad does more with less. Because the consequences are so extreme, both for the bomb squad and for the law enforcement organization.

Budget holders need to start viewing cybersecurity, BC/DR, and BC/DR testing like the bomb squad. Yes, they provide peace of mind. But what they really provide is protection from extreme consequences. Nobody wants the organization in the news for having been knocked offline for a month in every major news outlet. Nobody wants to have to create the postmortem and present it to the board and likely various government officials, insurance executives, investor representatives and lawyers. Let’s not let this plea to take cybersecurity and BC/DR seriously fall on deaf ears like it has in the past.

Summary Bullets:

• Data center cooling has become an increasingly insurmountable challenge because AI accelerators consume massive amounts of power.

• Liquid cooling adoption is progressively evolving from experimental to mainstream starting with AI labs and hyperscalers, then moving into the colocation space and later enterprises.

As Generative AI (GenAI) takes an ever-stronger hold in our lives, the demands on data centers continue to grow. The heat generated by the high-density computing required to run AI applications that are more resource-intensive than ever is pushing companies to adopt ever more innovative cooling techniques. As a result, liquid cooling, which used to be a fairly experimental technique, is becoming more mainstream.

Eye-watering amounts of money continue to pour into data center investment to run AI workloads. Heat management has become top of mind due to the high rack densities deployed in data centers. GlobalData forecasts that AI revenue worldwide will reach $165 billion in 2025, marking an annual growth of 26% over the previous year. The growth rate will accelerate from 2026 at 34%, and in subsequent years; in fact, the CAGR in the period 2004-2025 will reach 37%.

Source: GlobalData

The powerful hardware designed for AI workloads is growing in density. Although average density racks are usually below 10 kW, it is feasible to think of AI training clusters of 200 kW per rack in the not-too-distant future. Of course, the average number of kW per rack varies a lot, depending on the application, with traditional IT workloads for mainstream business applications requiring far fewer kW-per-rack than frontier AI workloads.

Liquid cooling is a heat management technique that uses liquid to remove heat from computing components in data centers. Liquid has a much higher thermal conductivity than air as it can absorb and transfer heat more effectively. By bringing a liquid coolant into direct contact with heat-generating components like CPUs and GPUs, liquid cooling systems can remove heat at its source, maintaining stable operating temperatures.

Although there are many diverse types of liquid cooling techniques, direct to chip is the most popular cooling method, also known as “cold plate,” accounting for approximately half of the liquid cooling market. This technique uses a cold plate directly mounted on the chip inside the server, enabling efficient heat dissipation. This direct contact enhances the heat transfer efficiency. This method allows high-end, specialized servers to be installed in standard IT cabinets, similar to legacy air-cooled equipment.

There are innovative variations on the cold plate technique that are currently under experimentation. Microsoft is currently prototyping a new method that takes the direct to chip technique one step further by bringing liquid coolant directly inside the silicon where the heat is generated. The method entails applying microfluidics via tiny channels etched into the silicon chip, creating grooves that allow cooling liquid to flow directly onto the chip and more efficiently remove heat.

Swiss startup Corintis is behind the novel technique, which blends the electronics and the heat management system that have been historically designed and made separately, creating unnecessary obstacles when heat has to propagate through multiple materials. Corintis created a design that blends the electronics and the cooling together from the beginning so the microchannels are right underneath the transistor.

Summary Bullets:

• Organizations are spending more on technology across business functions, and it is imperative for them to understand and optimize their tech spending through technology business management (TBM).
• IBM is a key TBM vendor helping organizations to drive their IT strategy more effectively; it is making moves to extend the solution to more customers and partners.

Every company is a tech company. While this is a cliché, especially in the tech industry, it is becoming real in the era of data and AI. For some time, businesses have been gathering data and analyzing them for insights to improve processes and develop new business models. By feeding data into AI engines, enterprises accelerate transformation by automating processes and reducing human intervention. The result is less friction in customer engagement, more agile operations, smarter decision-making, and faster time to market. This is, at least on paper, the promises of AI.

However, enterprises face challenges as they modernize their tech stack, adopt more digital solutions, and move AI from trials to production. Visibility into tech spending and the ability to forecast costs, especially with many services consumed on a pay-as-you-go basis is a challenge. While FinOps addresses cloud spend, a more holistic view of technology spend is necessary, including legacy on-premises systems, GenAI costs (pricing is typically based on the tokens), as well as labor-related costs.

This has made the concept of TBM more crucial today than ever. TBM is a discipline that focuses on enhancing business outcomes by providing organizations with a systematic approach to translating technology investments into business values. It brings financial discipline and transparency to their IT expenditures with the aim of maximizing the contribution of technology to overall business success. Technology is now widely used across business functions such as enterprise resource planning (ERP) for finance, human capital management (HCM) for HR, customer resource management (CRM) for sales, and supply chain management (SCM) for operations. Based on GlobalData’s research, about half of the tech spend today is already from budgets outside of the IT department. It is becoming more crucial as the use of technology becomes even more pervasive across the organization especially with AI being embedded into workflows. Moreover, TBM capability also help to elevate the role of tech leaders within an organization, as a strategic business partners.

IBM is one of the vendors that offer a comprehensive set of solutions to support TBM in part enabled by acquisitions such as Apptio (which also acquired Cloudability and Targetprocess) and Kubecost. Cloudability underpins IBM’s FinOps and cloud cost management, which is a key component that is already seeing great demand due to the need to optimize cloud workloads and spend as companies continue to expand their cloud usage. Apptio offers IT financial management (ITFM) which helps enterprises gain visibility into their tech spend (including SaaS, cloud, on-premises systems, labor, etc.) as well as usage and performance by app or team. This enables real-time decision-making, facilitates the assessment IT investments against KPIs, makes it possible to shift IT budget from keeping the lights on to innovation, and supports showback/chargeback to promote fairness and efficient usage of resources. With Targetprocess, IBM also has a strategic portfolio management (SPM) solution that helps organizations to plan, track, and prioritize work from the strategic portfolio of projects and products to the software development team. The ability to track work delivered by teams and determine the cost per unit of work allows organizations to improve time-to-market and align talent spend to strategic priorities.

Besides IBM, ServiceNow’s SPM helps organizations make better decision based on the initiatives to pursue based on resources, people, budgets, etc. ServiceWare is another firm that offers cloud cost management, ITFM, and a digital value model for TBM. Other FinOps and ITSM vendors may also join the fray as market awareness grows.

Moreover, TBM should not be a practice of the largest enterprises but rather depends on the level of tech spending involved. While IBM/Apptio serves many enterprises (e.g., 60% of Global Fortune 100 companies) that have tech spend well over $100 million, there are other vendors (e.g., MagicOrange and Nicus) that have more cost-effective solutions to target mid-sized enterprises. IBM is now addressing this customer segment with a streamlined IBM Apptio Essentials suite announced in June 2025 which offers fundamental building blocks of ITFM practice that can be implemented quickly and more cost-effectively. Based on GlobalData’s ICT Client Prospector database, in the US alone, there are over 5,000 businesses with total spend exceeding $25 million, which expands the addressable market for IBM.

For service providers, TBM is also a powerful solution for deeper engagement with enterprises and delivers a solution that drives tangible business outcomes. Personas interested in TBM include CIOs, CFOs, and CTOs. While there are TBM tools and dashboards that are readily available, service providers can play a role in managing the stakeholders and designing the processes. Through working with multiple enterprise customers, service providers are also building experiences and best practices to help deliver value faster and avoid potential pitfalls. Service providers such as Deloitte and Wipro already offer TBM to enterprise customers. Others should also consider working with TBM vendors to develop a similar practice.

Summary Bullets:

• Major telecom companies like Vodafone Germany, T-Mobile US, and Deutsche Telekom are launching distinct 5G network slicing services aimed at business customers, each reflecting unique strategies and market contexts, from Vodafone’s standardized pricing for virtual private campus networks to T-Mobile’s all-in-one premium mobility plan and Deutsche Telekom’s focus on mission-critical services for emergency responders.

• While these launches signify progress in 5G enterprise services, the concept of network slicing is still evolving, with offerings being marketed more as tailored connectivity solutions rather than fully programmable network tools.

The long-promised potential of 5G network slicing—dedicated, virtualized “lanes” in the mobile network—is finally being brought to market in structured offers for business customers. But what exactly is being offered? Vodafone Germany, T-Mobile US, and Deutsche Telekom have all announced distinct slicing propositions in recent weeks, each reflecting a different strategy and market context.

One of the promises of network slicing is that–in theory–it can be used to design an almost limitless number of unique offers based on the feature requirements of individual users and applications. We are still some ways away from dynamic programmability of bespoke network slices on the fly, but even at this early stage of commercialization, each slicing service launch looks completely different from the others. That’s kind of the point, but it could also provoke some head scratching by enterprises trying to understand the concept.

Vodafone Germany has taken perhaps the boldest step towards mainstreaming slicing by publishing standard pricing. Campus Flex Exclusive (EUR2,000/month per location) delivers a virtual private 5G campus network, offering guaranteed uplink and downlink speeds. Campus Flex Starter (EUR10-20 per user/month) is an entry-level, shared slice for light applications like payment terminals or push-to-talk. Vodafone’s use of “Campus Network” branding and positioning is interesting, reflecting its investment in marketing earlier versions of hybrid private 4G and 5G networks leveraging its macro network. The new offers position slicing as a virtual private network alternative, faster and cheaper than deploying a full private network. What’s impressive is the fact that customers can order slices directly from the Vodafone business portal. On the other hand, Vodafone hasn’t detailed service level agreements beyond basic throughput. Transparency on latency, jitter, and other guarantees will be required prior to adoption by more demanding industrial users.

T-Mobile US, meanwhile, is packaging slicing into a broad business mobility plan called SuperMobile, which combines a “nationwide 5G Advanced slice with dynamic, real-time resource optimization” and built-in security (encryption, device authentication, and Threat Protect VPN for smartphones). It also includes T-Satellite, the company’s new satellite-to-mobile service with coverage via more than 650 satellites.

This all-in-one proposition is pitched as a general-purpose premium business solution, not an industrial, mission-critical, or application-specific product. Delta Air Lines and Axis Energy Services are early adopters, showcasing both urban and remote-field use cases.

Unlike Vodafone, T-Mobile has not disclosed pricing, and it remains unclear whether customers can define or request custom quality of service (QoS) parameters per slice (the announcement refers only to data prioritization and latency optimization). That makes the offer more of a broad performance upgrade than a programmable network service.

Deutsche Telekom (DT), by contrast, is going deep into a vertical, announcing slicing-enabled mission-critical broadband services for police, fire, and rescue agencies. Partnering with Motorola Solutions, DT is deploying 3GPP-standard Mission-Critical Services (MCX) protocols, allowing push-to-talk, push-to-video, and prioritized data sharing across LTE, 5G, and traditional radios.

By reserving network capacity through slicing, DT provides emergency responders with a guaranteed “blue light lane” on the network, ensuring reliable communications during congestion. The solution has already been tested with German federal police and proven during the 2024 European Football Championship. Pricing is not disclosed, and the service appears restricted to the public sector. It’s not yet clear whether DT intends to extend MCX-style slicing to commercial industries with critical communications needs.

These three very different commercial launches represent progress in 5G enterprise services, but are we seeing network slicing go mainstream?

Rather than seeing an enterprise “network slicing market” emerge, what is more likely to appear in the near-term are even more examples of market, vertical, or application-specific offerings that benefit in part from network slicing functionality, but which avoid the hype of telecom technology vendors in favor of communicating with business customers in their own language.

Slicing is moving beyond pilots, but its mainstream role remains in flux. Today, it is being marketed less as a programmable network tool and more (as seen in these recent launches) as a value-added connectivity layer, tailored either for specific industries (DT), standardized private network substitutes (Vodafone), or premium broad-market plans (T-Mobile). The key question for the next phase: Will operators empower customers with true programmability and SLAs—or keep slicing as a behind-the-scenes enhancement bundled into premium plans?