IBM targets agentic AI scale-up with new Enterprise Advantage consulting service
IBM has launched a new consulting service named Enterprise Advantage, designed to help CIOs take their agentic and other AI applications from experimentation to large-scale production.
Enterprise Advantage is based on Consulting Advantage, IBMβs internal AI-powered delivery platform, which in turn combines the companyβs consulting expertise and workflows used to transform its internal operations.
Consulting Advantage also includes a marketplace that houses industryβspecific AI agents and applications, which has been rolled into Enterprise Advantage.
Analysts say Enterprise Advantage could help enterprises more effectively build and scale agentic and other AI applications across complex, multi-cloud environments because the service is designed to operate independently of specific cloud providers, AI models, or underlying infrastructure.
This approach aligns with the fragmented and heterogeneous IT landscapes most large enterprises already run, as they need to be able to scale AI applications within the constraints of their current IT estates without having to rip and replace any layer or infrastructure, Sanchit Vir Gogia, chief analyst at Greyhound Research.
Echoing Gogiaβs views, Pareekh Jain, principal analyst at Pareekh Consulting, pointed out that large enterprises already have sunk costs in multiple clouds and multiple model choices.
In fact, Jain sees the new service helping enterprises reduce hyperscaler lock-in and offering more flexibility of choice when it comes to choosing a specific cloud vendor or their AI stack for building an agentic or AI application.
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The flexibility offered by Enterprise Advantage could have its own set of tradeoffs for CIOs.
While Enterprise Advantageβs cloudβagnostic pitch does help enterprises avoid getting locked into hyperscalerβspecific agent platforms like AWS Bedrock Agents or Microsoft Copilot Studio, the dependency might shift to the orchestration layer, Jain pointed out.
βIf companies build their agent workflows, governance rules, and orchestration logic entirely on IBMβs Enterprise Advantage framework, migrating to another provider later could become just as difficult,β Jain added.
Rather, CIOs should internally evaluate whether their enterprise has the talent and expertise to operate the frameworks and workflows that Enterprise Advantage provides because thatβs the only way that they can avoid lock-in at the orchestration and service level, Gogia said.
βIf clients simply deploy Enterprise Advantage without building internal muscle, theyβll end up reliant on IBMβs platform for updates, extensions, and compliance maintenance. This could replicate the same old outsourcing trap weβve seen before,β Gogia added.
In fact, Jain pointed out that enterprises with at least some level of AI maturity should look at adopting the new service.
While firms with very limited AI talent may find a framework-led approach too complex and instead prefer fully managed SaaS solutions, highly tech-native companies tend to build their own orchestration layers to avoid service dependency and retain control, the analyst said.
βThe real sweet spot is the enterprise middle, large organizations with capable IT teams but heavy backlogs, where developers can build agents but are slowed by security, governance, and infrastructure hurdles that IBMβs service can help remove,β Jain added. The service has been made generally available.
