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Yesterday — 5 December 2025Main stream

Smart Legal Contracts: How Blockchain Automates Agreements, NDAs & Leases

By: Duredev
5 December 2025 at 11:40
Smart Legal Contracts: How Blockchain Automates Agreements, NDAs & Leases

The legal industry is rapidly moving from paper-based processes to fully digital workflows. Yet, digital alone isn’t enough. Businesses, law firms, and startups need smart legal contracts on blockchain that automate agreements, reduce human error, and enhance compliance. ⚡

Duredev, a leading blockchain LegalTech development company, helps organizations implement smart contracts that are secure, automated, and tamper-proof — transforming the way legal agreements are executed.

🔐 Why Smart Legal Contracts Are the Future

Traditional contracts involve:

  • Manual approvals
  • Paper signatures
  • Delays in execution
  • Risk of errors or disputes

Blockchain solves these issues by enabling smart legal contracts that automatically execute once predefined conditions are met. Key benefits include:

  • Real-time execution of agreements
  • Automated payments and milestone triggers
  • Immutable audit trail for compliance
  • Reduced disputes and errors

With smart contract development for legal platforms by Duredev, law firms and startups can streamline operations while ensuring legal certainty and operational efficiency.

📝 Common Use Cases: NDAs, Leases & Service Agreements

Non-Disclosure Agreements (NDAs)

  • Activate automatically when all parties sign
  • Timestamped verification for legal enforceability

Lease Agreements

  • Rent or payment schedules trigger automatically
  • Ensures compliance without manual follow-ups

Service Contracts

  • Milestones release funds directly
  • Multi-party approvals executed seamlessly

✍️ How Blockchain Secures Digital Signatures

Digital signatures on blockchain go beyond traditional e-signatures by providing:

  • Cryptographic identity verification
  • Tamper-proof timestamping
  • Compliance with GDPR, eIDAS, and global standards
  • Audit trails for every signing event

Companies integrate secure digital signing integration to ensure signatures are valid, verifiable, and legally defensible. Duredev expertise ensures all digital signatures are seamlessly linked with smart contracts, creating zero-fraud workflows.

🔗 Multi-Party Contract Execution

Many agreements involve multiple parties, witnesses, or lawyers. Blockchain simplifies this by enabling:

  • Sequential or parallel signing
  • Automatic verification of all stakeholders
  • Real-time approval tracking
  • Audit-ready compliance reports

Using multi-party signing workflow automation from Duredev, platforms can manage complex legal agreements efficiently, reducing bottlenecks and human error.

🗄️ Secure Contract Storage: IPFS & Blockchain Integration

Smart contracts often reference sensitive legal documents. Storing these documents securely is critical. Duredev combines blockchain with IPFS legal document storage solutions to offer:

  • Decentralized storage for tamper-proof security
  • Hash-based verification on-chain
  • Cost-effective and scalable infrastructure
  • Full ownership and access control

This approach ensures legal agreements remain immutable, traceable, and accessible while minimizing storage costs.

📊 Compliance, Audit Trails & Legal Certainty

Every contract execution is recorded on-chain, creating:

  • Transparent and immutable audit trails
  • Linked identities for all signers
  • Regulatory compliance and enforceability
  • Easy tracking for audits or disputes

By integrating blockchain audit trails for legal compliance, Duredev ensures that startups and law firms can rely on automated legal verification without additional manual overhead.

🌟 Why Choose Duredev for Smart Legal Contracts

Duredev stands out as a blockchain LegalTech development company that offers:

  • End-to-end smart contract automation for agreements
  • Secure digital signature integration
  • Multi-party signing workflow automation
  • Hybrid IPFS/Filecoin contract storage solutions
  • White-label LegalTech platforms for startups and enterprises
  • Multi-chain support (Ethereum, Polygon, Solana, Aptos, Hyperledger)

Our platforms empower businesses to automate complex contracts, ensure compliance, and enhance operational efficiency — all with minimal human intervention.

🏁 Final Thoughts

Smart legal contracts are revolutionizing the way NDAs, leases, and service agreements are executed. With blockchain-powered LegalTech, businesses, law firms, and startups can:

  • Automate workflows
  • Secure digital signatures
  • Ensure tamper-proof notarization
  • Maintain compliance with audit-ready trails

Duredev provides the technology, expertise, and end-to-end support to make smart legal contract automation a reality. Embrace the future of LegalTech, streamline operations, and deliver trust — all on-chain.


Smart Legal Contracts: How Blockchain Automates Agreements, NDAs & Leases was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

Here’s why I added Bluetooth to my Home Assistant server

5 December 2025 at 11:00

Bluetooth is a well-worn technology that you might be tempted to write off in your smart home, especially if your server doesn’t already have Bluetooth capabilities. I wasn’t going to bother, but then I saw an opportunity to pick up a cheap adapter and gave it a shot.

Before yesterdayMain stream

Risk and Compliance 2025 Exchange: Diligent’s Jason Venner on moving beyond manual cyber compliance

The Pentagon is taking a major step forward in modernizing how it addresses cybersecurity risks.

Defense Department officials have emphasized the need to move beyond “legacy shortcomings” to deliver technology to warfighters more rapidly. In September, DoD announced a new cybersecurity risk management construct to address those challenges.

“The previous Risk Management Framework was overly reliant on static checklists and manual processes that failed to account for operational needs and cyber survivability requirements,” DoD wrote at the time. “These limitations left defense systems vulnerable to sophisticated adversaries and slowed the delivery of secure capabilities to the field.”

Weeding through legacy manual processes

The legacy of manual processes has built up over decades. Jason Venner, a solutions sales director at Diligent, said agencies have traditionally relied on people and paperwork to ensure compliance.

“It’s no one’s fault,” Venner said during Federal News Network’s Risk & Compliance Exchange 2025. “It just sort of evolved that way, and now it’s time to stop and reassess where we’re at. I think the administration is doing a pretty good job in looking at all the different regs that they’re promulgating and revising them.”

Venner said IT leaders are interested in ways to help streamline the governance, risk and compliance process while ensuring security.

“Software should help make my life easier,” he said. “If I’m a CIO or a CISO, it should help my make my life easier, and not just for doing security scans or vulnerability scans, but actually doing IT governance, risk and compliance.”

Katie Arrington, who is performing the duties of the DoD chief information officer, has talked about the need to “blow up” the current RMF. The department moved to the framework in 2018 when it transitioned away from the DoD Information Assurance Certification and Accreditation Process (DIACAP).

“I remember when we were going from DIACAP to RMF, I wanted to pull my hair out,” Arrington said earlier this year. “It’s still paper. Who reads it? What we do is a program protection plan. We write it, we put it inside the program. We say, ‘This is what we’ll be looking to protect the program.’ We put it in a file, and we don’t look at it for three years. We have to get away from paperwork. We have to get away from the way we’ve done business to the way we need to do business, and it’s going to be painful, and there are going to be a lot of things that we do, and mistakes will be made. I really hope that industry doesn’t do what industry tends to do, [which] is want to sue the federal government instead of working with us to fix the problems. I would really love that.”

Arrington launched the Software Fast Track initiative to once again tackle the challenge of quickly adopting secure software.

Evolving risk management through better automation, analytics

DoD’s new risk management construct includes a five-phase lifecycle and then core principles, including automation, continuous monitoring and DevSecOps.

Arrington talked about the future vision for cyber risk management within DoD earlier this year.

“I’m going to ask you, if you’re a software provider, to provide me your software bill of materials in both your sandbox and production, along with a third-party SBOM. You’re going to populate those artifacts into our Enterprise Mission Assurance Support Service,” she said. “I will have AI tools on the back end to review the data instead of waiting for a human and if all of it passes the right requirements, provisional authority to operate.”

Venner said the use of automation and AI rest on a foundation of data analytics. He argued the successful use of AI for risk management will require purpose-built models.

“Can you identify, suggest, benchmark things for me and then identify controls to mitigate these risks, and then let me know what data I need to monitor to ensure those controls are working. That’s where AI can really accelerate the conversation,” Venner said.

Discover more articles and videos now on our Risk & Compliance Exchange 2025 event page.

The post Risk and Compliance 2025 Exchange: Diligent’s Jason Venner on moving beyond manual cyber compliance first appeared on Federal News Network.

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AI-Driven Layoffs Push UK Students Toward the Trades

4 December 2025 at 05:48

Many students who once aimed for white-collar careers are now opting for manual professions they believe AI cannot easily replace.

The post AI-Driven Layoffs Push UK Students Toward the Trades appeared first on TechRepublic.

AI-Driven Layoffs Push UK Students Toward the Trades

4 December 2025 at 05:48

Many students who once aimed for white-collar careers are now opting for manual professions they believe AI cannot easily replace.

The post AI-Driven Layoffs Push UK Students Toward the Trades appeared first on TechRepublic.

Gen AI adoption is reshaping roles and raising tough questions about workforce strategy

3 December 2025 at 16:45

 

Interview transcript:

 

Terry Gerton I know you have studied how workers of different skill levels choose to use generative AI and the concept of AI exposure. Can you talk to us a little bit about what you’re finding there? Are there certain roles more likely to embrace AI, or certain roles that are more likely to be replaced?

Ramayya Krishnan AI exposure, to understand that, I think we have to think about how occupations are structured. So the Bureau of Labor Statistics has something, a taxonomy called O*NET. And O*NET describes all the occupations in the U.S. economy, there are 873 or so. And each of those occupations is viewed as consisting of tasks and tasks requiring certain sets of skills. AI exposure is a measure of how many of those tasks are potentially doable by AI. And thereby that becomes, then, a measure of ways in which AI could have an impact on people who are in that particular occupation. So, however, AI exposure should not be assumed to mean that that’s tantamount to AI substitution, because I think we should be thinking about how AI is deployed. And so there are capabilities that AI has. For instance, this conversation that we’re having could be automatically transcribed by AI. This this conversation we are having could be automatically translated from English to Spanish by AI, for instance. Those are capabilities, right? So when you take capabilities and actually deploy them in organizational contexts, the question of how it’s deployed will determine whether AI is going to augment the human worker, or is it going to automate and replace a particular task that a human worker does? Remember, this happens at the task level, not at the occupation level. So some tasks within an occupation may get modified or adapted. So if you look at how software developers today use co-pilots to build software, that’s augmentation, where it’s been demonstrated that software developers with lower skills usually get between 20% to 25% productivity improvement. Call center employees, again, a similar type of augmentation is happening. In other cases, you could imagine, for instance, if you were my physician and I was speaking to you, today we have things called ambient AIs that will automatically transcribe the conversation that I’m having with you, the physician. That’s an example of an AI that could potentially substitute for a human transcriber. So I gave you two examples: software developer and customer service where you’re seeing augmentation; the transcription task, I’m giving you an example of substitution. So depending on how AI is deployed, you might have some tasks being augmented, some being substituted. When you take a step back, you have to take AI exposure as a measure of capability and then ask the question, how does that then get deployed? Which then has impact on how workers are going to actually have to think about, what does this then mean for them? And if it’s complementing, how do they become fluent in AI and be able to use AI well? And if there’s a particular task where it’s being used in a substitutive manner, what does that then mean longer term for them, in terms of having to acquire new skills to maybe transition to other occupations where there might be even more demand? So I think it’s we have to unpack what AI exposure then means for workers by thinking about augmentation versus automation.

Terry Gerton There’s a lot of nuance in that. And your writings also make the point that Gen AI adoption narrows when the cost of failure is high. So how do organizations think both about augmentation versus replacement and the risk of failure as they deploy AI?

Ramayya Krishnan If you take the example of using AI in an automated fashion, its error rate has to be so low because you don’t have human oversight. And therefore, if the error rates are not sufficiently appropriate, then you need to pair the human with the AI. In some cases you might say the AI is just not ready. So we’re not going to use the AI at all. We’ll just keep human as is. In other cases, if AI can be used with the human, where there is benefits to productivity but the error rates are such you still need the human to ensure and sign off, either because the error rates are high or from an ethical standpoint or from a governance standpoint, you need the human in the loop to sign off, you’re going to see complementing the human with the AI. And then there are going to be tasks for which the AI quality is so high, that its error rates are so low, that you could actually deploy it. So when we talk about the cost of failure, you want to think about consequential tasks where failure is not an option. And so either the error rates have to be really low, and therefore I can deploy the AI in an automated fashion, or you have to ensure there is a human in the loop. And this is why I think AI measurement and evaluation prior to deployment is so essential because things like error rates, costs, all of these have to be measured and inform the decisions to deploy AI and deploy AI in what fashion? Is it in augmentation fashion or not, or is it going to be used independently?

Terry Gerton I’m speaking with Dr. Ramayya Krishnan. He’s the director of the Center for AI Measurement Science and Engineering at Carnegie Mellon University. So we’re talking there about how AI gets deployed in different organizations. How do you see this applying in the public sector? Are there certain kinds of government work where AI is more suitable for augmentation versus automation and that error rate then becomes a really important consideration?

Ramayya Krishnan I think there are going to be a number of opportunities for AI to be deployed. So you remember we talked about call centers and customer service types of centers. I mean, public sector, one aspect of what they do is they engage with citizens in a variety of ways, where they have to deliver and provide good information. Some of those are time sensitive and very consequential, like 911 emergency calls. Now, there you absolutely want the human in the loop because we want to make sure that those are dealt with in a way that we believe we need humans in the loop, which could be augmented by AI, but you know, you want humans in the loop. On the other hand, you could imagine questions about, you know, what kind of permit or what kind of form, you know, administrative kinds of questions, where there’s triage, if you will, of having better response time to those kinds of questions. The alternative to calling and speaking to somebody might be just like you could go to a website and look it up. Imagine a question-answering system that actually allows for you to ask and get these questions answered. I expect that, and in fact you’re already seeing this in local government and in state government, the deployment of these kinds of administrative kinds of question-answering systems. I’d say that’s one example. Within the organizations, there is the use of AI, not customer-facing or citizen-facing, but within the organizations, the use of these kinds of co-pilots that are being used within the organization to try and improve productivity. I think as AI gets more robust and more reliable, I expect that you will see greater use of AI in both trying to improve efficiency and effectiveness, but to do so in a responsible way, in such a way that you take into account the importance of providing service to citizens of all different abilities. One of the important things with the public sector is … maybe there’s multilingual support that is needed, you might need to help citizens who are disabled. How might we support different kinds of citizens with different ability levels? I think these are things where AI could potentially play an important role.

Terry Gerton AI is certainly already having a disruptive impact on the American workforce, particularly. What recommendations do you have for policymakers and employers to mitigate the disruption and think long-term about upskilling and reskilling so that folks can be successful in this new space?

Ramayya Krishnan I think this is actually one of the most important questions that we need to address. And you know, I served on the National AI Advisory Committee to the President and the White House Office of AI Initiatives, and this was very much a key question that was addressed by colleagues. And I think a recent op-ed that we have written with Patrick Harker at the University of Pennsylvania and Mark Hagerott at the University of South Dakota, really we make the case that this is an inflection point which requires a response pretty much on the scale of what President Lincoln did in 1862 with the Morrill Act in establishing land grant universities. Much like land grant universities were designed to democratize access to agricultural technology, really it enabled Americans from everywhere in the nation to harness this technology for economic prosperity both for themselves and for the nation. I think if you’re going to see AI be deployed and not have the kind of inequality that might arise from people having access to the technology and not having access to the technology, we need something like this. And we call this the Digital Land Grant Initiative that would connect our universities, the community colleges, with various ways of providing citizens, both in rural areas and urban areas, everywhere in the country, access to AI education and skilling appropriate to their context. So if I’m a farmer, how can I do precision agriculture? If I’m a mine worker, or if I’m somebody who wants to work in in banking — from the whole range of occupations and professions, you could imagine AI having a transformative effect on these different occupations. And there may be new occupations that are going to emerge that you and I are not thinking about right now. So, how do we best position our citizens so that they can equip themselves with the right sets of skills that are going to be required and demanded? I think that’s the big public policy question with regard to workforce upskilling and reskilling.

The post Gen AI adoption is reshaping roles and raising tough questions about workforce strategy first appeared on Federal News Network.

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I’m not proud of this Home Assistant smart lighting hack, but it works

28 November 2025 at 14:30

It’s no secret that smart light switches are better buys than smart light bulbs, but I don’t have any smart switches installed yet. That’s what led me to devise a delightfully devilish hack that still lets me use my existing light switches to turn on my smart bulbs in a pinch.

What comes next for federal workers after AI takes over the mundane tasks

26 November 2025 at 18:52

 

Interview transcript:

 

Bob Venero As we look at AI in in the federal government, but also in the companies that support the federal government — like the Northrop Grummans of the world, the Raytheons — AI is extremely important in helping them accomplish mission. Whether that mission is for the warfighter or whether that mission is for the Veterans Administration or any of the other areas within the government. And what we’re seeing is there’s a tremendous amount of pilots that are happening within those government agencies. At the end of the day, AI means something different to everybody, right? And really if you look at it, what is going to be the business outcome of some type of AI strategy or AI automation that you, as an agency or as a federal systems integrator, are trying to accomplish? That’s the key factor. I don’t want to say there’s no magic behind the curtain as it relates to what AI is — it’s things that are going to happen at speed and scale, tied to incredible technologies from companies like NVIDIA. I look at them as the grandfather of AI. And actually, I think next week is NVIDIA’s GTC event in DC, right? Really geared towards the government and you know what AI is doing for them. So as we look at different areas within the different government spaces, automation is key. Having the proper large language models to support what those agencies are trying to do, and then really protecting the security around what those AI models are going to do, and the guardrails that the government has to have, which is different than the bad actors around their AI testing processes and procedures.

Eric White That’s one thing I’ve been curious about as large language models and other AI tools start being implemented and the idea of contractors competing for different jobs. How are government officials going to judge who has the better large language model or who’s piggybacking off of who? Just getting your thoughts on what the future in that realm will look like.

Bob Venero Well, when you look at that … people are saying, hey, prove to me that you didn’t use an AI model to do that, right? And I look at it and say, if I’m smart enough to use that AI model, you should be looking at me because I’m going to be innovative and smart to help accomplish the goal. I don’t necessarily look at it as a bad thing. Who is going to leverage the proper tools that are out there to accomplish the job in the most efficient, effective and cost-based area? And I think that’s key for people to start to look at. You’ll see now when people actually do interviews, they’re asking them, are you doing this interview with AI or not with AI? And they have to attest to that. But to me, that goes counter to what AI is looking to do for everybody, right? It’s about speed, accuracy, and automation. And if someone knows how to leverage it better, that’s probably the person that you want, because those tools are going to be in your environment. It doesn’t necessarily mean that it’s a bad opportunity or they’re a bad contractor or there’s a bad comparative against large language models. It’s who’s using the technology to the best of its ability to accomplish the goals and the business outcomes? That’s the answer.

Eric White How much help will it provide on the bottom line, do you think, as far as budgets are getting tighter and tighter? How much more will this provide?

Bob Venero As we look at what AI can accomplish, automation is a lot of that AI conversation. Because when you can do automation, then you can take people out of the mundane tasks that are just labor-intensive and have them focus on better things to do, that are more thought-provoking, within their environment. So, it will make a difference as far as cost is concerned. Because if I have an individual that we’re paying $150,000 a year, and we had him doing tasks that were mundane because it was a part of his job description and now we can automate that and have him do more thought-provoking things? That’s better for the environment that we’re going to put him in, but it’s also better for the bottom line. Because now I can do things quicker, more efficient, and more effective. And now I can come in under budget potentially. So as budgets become more and more strained, AI becomes a much better tool. But you know, the big fear … am I going to lose my job to AI? That’s a very broad question. You shouldn’t lose your job to AI, and if you do lose your job to AI, then you weren’t focusing on really what your career was in your future. Because if AI can just take the job away, then you haven’t built value for yourself as an individual. It’s about how AI can help you do your job better, faster and right now the question is accuracy, right? Because there’s a lot of mistakes that happen within that model. Whether it’s Grok or ChatGPT, and you ask it a question that you know the answer to, and you know that the answer they gave you is wrong, and then you just say, are you sure? And you prompt that in, and they’re like, oh you’re right, actually, I did make a mistake. Now that I thought about it, here’s what it is. So it’s not even a question of oh, is that model 100% accurate? If you’re taking that as the rule of law, then you’re going to be in a situation where it’s going come back and bite you in the butt.

Eric White We’re speaking with Bob Venero, he’s the president and CEO of Future Tech Enterprise. That’s been the selling point of this technology, faulting whatever the doomsdayers say about loss of jobs, that you know it will help automate and free you up from those mundane tasks. Are we already seeing that or when is that going to kick in? Because I still find myself doing a lot of data entry here, Bob.

Bob Venero I think it’s definitely happening. Not as efficiently and effective as it should, and that’s because we haven’t been educated properly on prompt engineering. If you don’t know how to ask the AI model the question the right way, it’s going to take you longer sometimes to get to the end result. So there’s a whole education cycle that needs to happen on how to create the right prompting, to ask the right questions to get to your end result and goal. And I think that’s going to develop over time. So right now we’re in the infancies of it. I can tell you that it definitely helps in some of the mundane tasks that are tied to, hey, I want to write a brief about something, here is my topic. It gets you 80% there, and then you have to go in and adjust it. But that 80% has saved you a lot of time and effort, from starting it from the beginning to the end. But then you need to validate what it is, the end result, and make sure your answers are correct. So, we’re not quite there yet. I think in the next 12 to 18 months you’ll see a big difference as these models become more and more intelligent in supporting the businesses that they’re handling, the government agencies that they’re handling, whatever the area that it is, because it’s all about the data. And you know … [garbage] in, [garbage] out, right? And that is, from a data perspective, extremely important as these models become trained.

Eric White Let’s zero in on the defense side of things. Where, from a warfighter perspective, could this technology even work out for the Department of Defense? In the procurement contract world, could this technology be of assistance?

Bob Venero Oh, without a doubt. So a lot of times when the agencies like the DoD put out an RFQ for some type of solution, they’ve got criteria that they need to look at and vet each time the respondent is doing what they’re doing. And that criteria now can be handled by AI versus an individual having to compare hundreds or thousands of pages of response, going through it, pulling out the key areas in there, and then evaluating them across each other. And I think that’s very important. As you take a look at the speed of getting things done, what we’re seeing in the organizations, the systems integrators, speed is so important to them. Now to be able to respond to something accurately, efficiently, and be there first versus somebody else who maybe isn’t leveraging those tools is key. If the Department of Defense can use those same tools to evaluate and compare and contrast versus the human eye, it’s a game changer. It really, really is. And it can give you weighted results against each of the potential bidders on there and pick what it believes is the right solution based on your criteria. But then you still have that human intervention that says, okay, let’s really weigh the results here. Thank you for giving me the information. I see it this way, but Northrop Grumman performed better than BAE did on this, or vice versa, and there’s historics that you can take a look at from a DoD perspective. So I think the more and more it’s adopted within that space, the more efficient those agencies can become, the quicker they can give awards, and the better the cost base will be. They it’s going to reduce their costs as well.

Eric White And the bidders may be able to use it if they have to go through a lengthy RFQ, right?

Bob Venero Which without a doubt. Future Tech as a company, we do a lot of RFQs because we support a lot of the federal systems integrators. And we have an AI tool now — we’ve been in business 29 years, so 29 years of responses — and we fed it into the large language model. So now when something comes across the plate, I don’t have to have a team of seven: “Hey, pull from this, pull from that, pull from here, pull from that.” The AI goes in, it looks at the criteria, it then pulls it in and helps us write a draft of what the response is, the key things that we’ve had. And that’s been amazing from a time-reduction perspective and from a personnel and skill perspective.

Eric White Yeah, pointing it back at yourself, you gave that example. What are you having those seven folks do now that you don’t have to have them digging through all of that paperwork?

Bob Venero Here’s a perfect example. The person now who heads up our RFQ team, she wanted to expand and be a part of the onboarding and training for individuals that come into the company. And so now she has a dual role in the organization. That role wasn’t there before, but now we created this additional role, she’s got both of them, she has the time to do it based on the tools that are there. And now from an onboarding and training perspective, we’re going to bring in an AI module that’s going to help her with that as well. So if you’re embracing it properly, it is going to take you to places that are good. I always use this analogy. I’m a boater, right? And years ago, you had two sticks when you had two engines, right? You had sticks for left and right and back and forth, and then they came out with a joystick. And the joystick is just like we know, you turn the joystick left, it goes left, turn it right, back, forward. All intelligence built into it. The key and smart thing about what that has done — I used to get yelled at, “you’re a cheater, you’re a cheater, you know, you’re not learning the old way.” I’m like, no, I’m actually smart — it’s a lot easier to do it this way. I can get to my route quicker and I can park a lot more easy. It’s the same thing with these tools, right? Embrace them. Bring them into your environment, leverage them out there, and it’ll help you as an organization. But also any of the agencies that do it, it will help them be more efficient, effective, and that’s important right now, tied to costs and cost reduction.

The post What comes next for federal workers after AI takes over the mundane tasks first appeared on Federal News Network.

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