Millions of US federal government workers are about to get a new AI assistant on their devices for free in the form of Microsoft Copilot. The move is part of a deal between Microsoft and the US General Services Administration (GSA) that’s also expected to save taxpayers $3.1 billion in its first year.

The centrepiece of this huge new agreement is a full year of Microsoft 365 Copilot at no extra cost for government workers using the high-security G5 licence. This is a push to get the latest AI tools into the hands of public servants quickly and safely, aiming to improve how the government operates.

Microsoft pushes the US government into the AI era

This deal aims to place the US government at the forefront of AI adoption. It’s a direct response to the administration’s AI Action Plan, designed to bring the power of modern artificial intelligence to everything from managing citizen enquiries to analysing complex data.

“OneGov represents a paradigm shift in federal procurement that is leading to immense cost savings, achieved by leveraging the purchasing power of the entire federal government,” explained FAS Commissioner Josh Gruenbaum.

The free Copilot offer is specifically for users on the Microsoft 365 G5 plan, the premium tier for departments that handle sensitive information and require the tightest security protocols. But the benefits extend further, with the deal helping agencies to use AI for automating routine tasks, freeing up people to focus on the work that matters most.

The agreement also makes it cheaper and easier for different departments to modernise their technology. By offering big discounts on Azure cloud services and getting rid of data transfer fees, it tackles a major headache that has often slowed down collaboration between agencies.

Security is not an afterthought

Of course, giving AI access to government systems raises immediate security questions. The deal addresses this head-on, with Microsoft emphasising that its core cloud and AI services have already passed FedRAMP High security authorisation, a critical standard for handling sensitive government data.

While the full FedRAMP High certification for Copilot itself is expected soon, it has already been given a provisional green light by the Department of Defense. The package also includes advanced security tools like Microsoft Sentinel and Entra ID to support the government’s “zero trust” security goal.

GSA Deputy Administrator Stephen Ehikian strongly encouraged government agencies to take advantage of the new tools.

“GSA is proud to partner with technology companies, like Microsoft, to advance AI adoption across the federal government, a key priority of the Trump Administration,” said Ehikian. “We urge our federal partners to leverage these agreements, providing government workers with transformative AI tools that streamline operations, cut costs, and enhance results.”

Helping government agencies to use AI effectively

Microsoft is also putting money into making sure the technology is actually used effectively. The company has committed an extra $20 million for support and training, including workshops to help agencies get the most out of the new tools and find other areas to reduce waste.

All told, the package is estimated to deliver more than $6 billion in value over the next three years.

“With this new agreement with the US General Services Administration, including a no-cost Microsoft 365 Copilot offer, we will help federal agencies use AI and digital technologies to improve citizen services, strengthen security, and save taxpayers more than $3 billion in the first year alone,” commented Satya Nadella, Chairman and CEO of Microsoft.

For the millions of people working within the US government, this agreement with Microsoft means that an AI-powered assistant is set to change their daily work.

See also: Marketing AI boom faces crisis of consumer trust

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Swarm Network, a platform developing decentralised protocols for AI agents, recently announced the successful results of its first Swarm, a tool (perhaps “organism” is the better term) built to tackle disinformation. Called Rollup News, the swarm is not an app, a software platform, nor a centralised algorithm. It is a decentralised collection of AI agents that collaborate to solve a bigger problem. The problem is that platforms like X allow any type of viral claims, some by incredibly influential people. How can we know what is true?

Currently, we try to solve this problem through equally loud opposing voices who offer facts or expert opinions. But if those sources are from a political side you oppose, why should you trust them? After all, these are people with their own motivations, and two additional issues are created: facts presented by a single person can easily get caught up in the “fake news” accusations; and misinformation presented as “facts” can be used to attack the ground truth.

Unfortunately, this isn’t just a current trend that will eventually lose its popularity and fade out. The more technology and access to varied news sources we have, the harder it becomes to not treat these sources equally. Some might be a traditional outlet that is legally liable if they falsify claims. Others might be a popular podcaster with an audience of millions, and whose fear-mongering ties nicely in with the products in their merch store. If it stopped at this, we could probably tell the truth from fiction. But it isn’t that simple. Official news channels have a history of spinning the news in their own bias, or ignoring other stories that are important to the public. On the other side, there are genuinely powerful influencers who seem to be hell bent on finding the truth and reporting it, no matter what side of the political spectrum it hits.

The world has become both confusing and dangerous, and the old “sticks and stones” saying has been proven false. After all, we have seen global elections swayed by disinformation, major policy shifts driven by false claims, lives damaged and lost as the result of powerful people lying, but lying loudly enough and often enough to sway large groups of people into believing them; and convincing these same groups that any facts to the contrary are the actual “fake news.”

Fixing fact checking

Given how challenging the disinformation industry is, and how absolutely slippery the truth is today, how can anyone hope to battle it? We have seen that people of all sides, realising that all news is skewed to some extent, will believe those sources that support their pre-existing beliefs.

A third party source, backed by overwhelming evidence, is needed to arbitrate. The source should not have an opinion, its methods should be transparent, and everyone should be able to see the same thing. This is nearly impossible, but the Web3 industry has shown that these attributes are what makes it incredibly powerful. Smart contracts handle billions in value daily, managing agreements from complete strangers from anywhere on the globe. The information is validated and the decisions are transparent, then locked in via the blockchain. The model has moved trillions of dollars using these very powerful, and neutral, tools.

Combine this trust with the other element Web3 excels in: decentralisation. Now attach another fast-emerging technology, the AI agent, which is easily built and designed to perform one task very well. The system is the centre of Swarm Network’s model, and its first deployment is Rollup News. The growing population of AI agents, the swarm, is designed to work collectively to scour the corners of X, find claims from users, and collectively test their validity using sources found in the information space. The results of these assessments are posted on the blockchain once validated by a large enough group of independent agents. Selective human participation helps to ensure the context and other subtle areas are handled well. The human element is also decentralised, preventing any particular viewpoint from being able to assert itself, and misconduct equals expulsion if someone tries to present fiction as fact. Rollup News has been operating for several months, with astonishing results: 128,000+ users have been onboarded, with over 5,000 rollup requests daily in July 2025. Over 3 million tweets were processed during that time, which is impressive in its own right, but when you consider the designed scalability of Web3 and AI agents working together, this is the linchpin of the battle in a world of disinformation.

The start of something new?

Rollup News’ success and Swarm Network’s larger model teach us a few things about fixing today’s problems. It is a demonstration that Web3 and AI are components in providing scalable solutions, that small AI agents can effectively work together to solve giant challenges, even if there is no centralised system. That decentralised environment, anchored by Web3, is the key to generating transparency, trust, and allowing strangers anywhere in the world to work together. Finally, the tokenisation of such a system creates the necessary incentives to attract more participants, fuelling the growth of a system. As long as it creates value, people will pay for its use, and those who help to validate and secure the decentralised network earn rewards. The type of truly free market system can scale up or down with the global demand faster than any traditional company. Swarm Network’s founder, Yannick Myson, sums it up nicely: “Rollup News shows what’s possible when AI agents, human insight, and blockchain converge. This isn’t a prototype – it’s working, and it’s scaling.”

We need to pay close attention to these lessons, as they offer a great deal of insight. First, the “truth-tech” sector, which is focused on using technology to combat mis/dis-information, has a strong blueprint for combining blockchain and AI. Second, there are many other sectors that need this level of global scaling and independent management, with untold value just ready to be developed and launched.

Image source: Unsplash

Agentic AI is being talked about as the next major wave of artificial intelligence, but its meaning for enterprises remains to be settled. Capgemini Research Institute estimates agentic AI could unlock as much as US$450 billion in economic value by 2028. Yet adoption is still limited: only 2% of organisations have scaled its use, and trust in AI agents is already starting to slip.

That tension – high potential but low deployment – is what Capgemini’s new research explores. Based on an April 2025 survey of 1,500 executives at large organisations in 14 countries, including Singapore, the report highlights trust and oversight as important factors in realising value. Nearly three-quarters of executives said the benefits of human involvement in AI workflows outweigh the costs. Nine out of ten described oversight as either positive or at least cost-neutral.

The message is clear: AI agents work best when paired with people, not left on autopilot.

Early steps, slow progress

Roughly a quarter have launched agentic AI pilots, while only 14% have moved into implementation. For the majority, deployment is still in the planning stage. The report describes this as a widening gap between intent and readiness, now one of the main barriers to capturing economic value.

The technology is not just theoretical – real-world applications are starting to emerge, and one example is a personal shopping assistant that can search for items based on specific requests, generate product descriptions, answer questions, and place items in a cart using voice or text commands. While these tools typically stop short of completing financial transactions for security reasons, they already replicate many of the functions of a human assistant.

This raises bigger questions about the role of traditional websites. If AI can handle tasks like searching, comparing, and preparing purchases, will people still need to navigate online stores directly? For those who find busy websites overwhelming or difficult to navigate, an AI-driven interface may offer a simpler, more accessible option.

Defining agentic AI

To cut through the hype, AI News spoke with Jason Hardy, chief technology officer for artificial intelligence at Hitachi Vantara, about how enterprises in Asia-Pacific should think about the technology.

“Agentic AI is software that can decide, act, and refine its strategy on its own,” Hardy said. “Think of it as a team of domain experts that can learn from experience, coordinate tasks, and operate in real time. Generative AI creates content and is usually reactive to prompts. Agentic AI may use GenAI inside it, but its job is to pursue objectives and take action in dynamic environments.”

The distinction – between producing outputs and driving outcomes – captures the meaning of agentic AI for enterprise IT.

Why adoption is accelerating

According to Hardy, adoption is being driven by scale and complexity. “Enterprises are drowning in complexity, risk, and scale. Agentic AI is catching on because it does more than analyse. It optimises storage and capacity on the fly, automates governance and compliance, anticipates failures before they occur, and responds to security threats in real time. That shift from ‘insight’ to ‘autonomous action’ is why adoption is accelerating,” he explained.

Capgemini’s research supports this. The study found that while confidence in agentic AI is uneven, early deployments are proving useful when the technology takes on routine but essential IT tasks.

Where value is emerging

Hardy pointed to IT operations as the strongest use case so far. “Automated data classification, proactive storage optimisation, and compliance reporting save teams hours each day, while predictive maintenance and real-time cybersecurity responses reduce downtime and risk,” he said.

The impact goes beyond efficiency. The capabilities mean systems can detect problems before they escalate, allocate resources more effectively, and contain security incidents more quickly. “Early users are already using agentic AI to remediate incidents proactively before they escalate, strengthening reliability and performance in hybrid environments,” Hardy added.

For now, IT remains the most practical starting point: its deployment offers measurable results and is central to how enterprises manage both costs and risk, showing the meaning of agentic AI in operations.

Southeast Asia’s starting point

For Southeast Asian organisations, Hardy said the first priority is getting the data right. “Agentic AI delivers value only when enterprise data is properly classified, secured, and governed,” he explained.

Infrastructure also matters, meaning that agentic AI requires systems that can support multi-agent orchestration, persistent memory, and dynamic resource allocation. Without this foundation, adoption will be limited in scope.

Many enterprises may choose to begin with IT operations, where agentic AI can pre-empt outages and optimise performance before rolling out to wider business functions.

Reshaping core workflows

Hardy expects agentic AI to reshape workflows in IT, supply chain management, and customer service. “In IT operations, agentic AI can anticipate capacity needs, rebalance workloads, and reallocate resources in real time. It can also automate predictive maintenance, preventing hardware failures before they occur,” he said.

Cybersecurity is another area of promise. “In cybersecurity, agentic AI is able to detect anomalies, isolate affected systems, and trigger immutable backups in seconds, reducing response times and mitigating potential damage,” Hardy noted.

The capabilities are not limited to proof-of-concept trials. Early deployments already show how agentic AI can strengthen reliability and resilience in hybrid environments.

Skills and leadership

Adoption will also require new human skills. “Agentic AI will shift the human role from execution to oversight and orchestration,” Hardy said. Leaders will need to set boundaries and monitor autonomous systems, ensuring they stay in ethical and organisational limits.

For managers, the change means less focus on administrative tasks and more on mentoring, innovation, and strategy. HR teams will need to build governance skills like auditing readiness and create new structures for integrating agentic AI effectively.

The workforce impact will be uneven. The World Economic Forum predicts that AI could create 11 million jobs in Southeast Asia by 2030 and displace nine million. Women and Gen Z are expected to face the sharpest disruptions, with more than 70% of women and up to 76% of younger workers in roles vulnerable to AI.

This highlights the urgency of reskilling, and major investments are already underway, with Microsoft committing $1.7 billion in Indonesia and rolling out training programmes in Malaysia and the wider region. Hardy stressed that capacity building must be inclusive, rapid, and strategic.

What comes next

Looking three years ahead, Hardy believes many leaders will underestimate the pace of change. “The first wave of benefits is already visible in IT operations: agentic AI is automating tasks like data classification, storage optimisation, predictive maintenance, and cybersecurity response, freeing teams to focus on higher-level strategic work,” he said.

But the larger surprise may be at the economic and business model level. IDC projects AI and generative AI could add around US$120 billion to the GDP of the ASEAN-6 by 2027. Hardy sees the implications as broader and faster than many expect. “The suggests the impact will be much faster and more material than many leaders currently anticipate,” he said.

In Indonesia, more than 57% of job roles are expected to be augmented or disrupted by AI, a reminder that transformation will not be limited to IT. It will cut in how businesses are structured, how they manage risk, and how they create value.

Balancing autonomy with oversight

The Capgemini findings and Hardy’s insights converge on the same theme: agentic AI holds huge promise, but its meaning in practice depends on balancing autonomy with trust and human oversight.

The technology may help enterprises lower costs, improve reliability, and unlock new revenue streams. But without a focus on governance, reskilling, and infrastructure readiness, adoption risks stalling.

For Southeast Asia, the question is not whether agentic AI will take hold, but how quickly – and whether enterprises can balance autonomy with accountability as machines begin to take on more responsibility for business decisions.

(Photo by Igor Omilaev)

See also: Beyond acceleration: the rise of agentic AI

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and is co-located with other leading technology events, click here for more information.

AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.