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Marco Argenti: We Must Prepare AI Natives to Shape the Future of Work

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This opinion article was originally published in Fortune on July 3, 2025.

 

Agentic AI is driving a monumental, generational shift that is poised to revolutionize industries and reshape workforce dynamics in ways we are only beginning to understand. Soon, human and AI “workers” will learn to coexist, collaborate, and thrive together. The path to that future, and the success of this collaboration, will depend on the next generation of talent leading the way.

Agentic AI refers to artificial intelligence systems that can perform tasks on behalf of humans and make independent decisions without direct oversight. These systems can reason based on context, memory, and available data, generate detailed plans, and autonomously execute the steps required to complete a task. Their growing capabilities mark a shift from passive tools to active collaborators.

While some speculate that agentic AI will displace many junior-level roles—and there may well be a certain level of recalibration—the reality is more nuanced. Rather than diminishing the importance of early-career workers, this shift makes them more critical than ever for one simple reason. The generation now entering the workforce has “grown up” alongside generative AI. They are more comfortable with its pace and equipped to shape its future. They are “AI natives.”

At the same time, as someone famously said, “there’s no compression algorithm for experience,” and experience and sound judgement are not intrinsically an attribute of generative AI, which at best is 4 years old and still undergoing rapid evolution. Which begs the question: Who’s going to provide experienced supervision to a potentially limitless number of AI agents entering the workforce?

Understanding how we nurture a generation of AI natives—and equip them with the right skills and tools to be leaders and not passive observers of this transformation—will be critical to defining the future of work and society at large. Their instincts, creativity, and adaptability will determine how successfully we integrate AI into our organizations not just as a tool but as a partner. The challenge ahead is beyond technological; it is cultural, educational, and distinctively human.

The new AI paradigm

Here’s the first thing we need to come to terms with: This is a new game with new athletes who are likely more proficient than previous players ever will be. 

Think of it this way: If you’re asked to learn the piano later in life, you might be enthusiastic and dedicated, but the odds of becoming a prodigy are slim. Similarly, think about someone who learned to use a computer well into adulthood. Even decades later, their typing, mouse usage, or navigation of user interfaces often reveals their late start.

The same dynamic is now unfolding with AI tools. A generational divide is emerging—not because more seasoned professionals lack intelligence or drive, but because they didn’t grow up with these tools. For those who aren’t AI natives, adapting to an AI-first or AI-hybrid workforce may prove more difficult than we anticipate. However, that’s where most of the institutional knowledge and experience lies.

Several technological shifts have created similar knowledge vacuums: the introduction of computers, the internet, mobile, cloud technologies, and others. In each case, it took a decade or more before fluency became a baseline requirement for certain roles. Those who couldn’t adapt either transitioned into roles that didn’t require those skills or exited the workforce altogether. What’s different now is the speed. The AI shift is happening in years, not decades. Workers who lack proficiency in leveraging AI tools will fall behind, and those who have learned to harness it to elevate their work will advance.

As with every major technological shift, a new generation of leaders is emerging, particularly entrepreneurs whose native fluency with AI is reshaping the landscape. Consider the CEOs of companies like Devin, Windsurf, and Scale AI—all AI natives. Could one of them be the next Bill Gates or Michael Dell? It’s possible. Our responsibility as a society and as leaders is therefore twofold: to maximize the potential of this new generation of AI natives, and to ensure the rest of the workforce focuses on accelerating the “path to seniority” for our junior athletes.

Investing in AI natives

Our priority must be to invest in junior talent who will redefine the industries we work in. While the exact contours of this transformation are difficult to predict, its scale is easy to imagine if we accept that AI is the most profound technological disruption of our time. In a world where technology evolves at sonic speed, our focus must be on ensuring that human adaptation keeps pace. Simply put, we need to train our best athletes for this new arena and equip them with the essential skills to manage and lead this change in an accelerated way.

With the arrival of agentic AI, the ability to spin up AI coworkers on demand will soon be a baseline capability. This shift will require even the most junior employees and individual contributors to master three foundational management skills: describing a task clearly, delegating it effectively to an AI agent, and supervising the results. Supervision is especially critical in a world where agent technology is still maturing. The failure mode here is not technological, it’s organizational. Delegating work to an agent without the ability to supervise it is a recipe for disaster, which is why we must instill a new sense of quality control and agency in our people.

As an example, AI systems today are highly sensitive to how questions are posed. The prompt or “context” is processed by the AI’s attention layers, which determine the relative importance of each word or token. A slight miscommunication can be amplified, distorting the output. In the case of autonomous agents, hallucinations don’t just lead to bad answers, they can trigger incorrect or even dangerous actions. Until we are confident these tools will not act irrationally, we must keep humans in the loop. Therefore, rethinking the concept of agency is essential.

Agency, in this broader sense, includes the tasks delegated to an AI agent, how those tasks are executed, and how the agent communicates with humans, data sources, and other agents. New communication protocols like MCP and A2A are emerging to standardize these interactions. But the human role remains central.

As junior employees take on the responsibilities of “managers,” the traditional boundaries between business and engineering are dissolving. Much like how product managers and engineers have converged, today’s professionals must be fluent in both domains. To be a great engineer now means also being a great product manager: understanding the customer, defining the roadmap, identifying risks and biases, and designing compensating controls. This is the mindset we must cultivate in our AI-native workforce. They will be expected to manage their AI agents not just by issuing commands, but by understanding their capabilities and limitations, and by anticipating risks before they become problems. Supervision is key, which requires experience, and experience requires time—which, at this pace of change, is a scarce commodity. 

Supervision is key to this evolution. We must ensure that the one who delegates has the ability to check the quality of the work being created by an AI. Imagine an airline that, because of the introduction of the autopilot with auto-land and auto-take-off features, decides to fill some of the flights with only junior pilots. Would we sense the same level of safety and quality control? Only if we felt the junior pilots were properly equipped to supervise.

Ultimately, cultural transformation in a period of such sharp technological advancement is about more than adopting new tools. It is about forming a new generation of leaders and accelerating their path to experience, equipping them with managerial skills from the outset, and leveraging their innate familiarity and proficiency with this new technology. 

Today, technology change is ahead of human change. It’s easier to change software and AIs than it is to rewire the human brain, to break old habits and create new skills. Non-AI natives—most of us—have possibly the most challenging task of all: to pass the baton to a new generation of humans entering the workforce and equip them with the skills necessary to manage something that the current generation does not fully understand. All this, without the luxury of time.



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Govt. AI Assessment Ranks States’ Readiness, Adoption Levels

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An AI readiness assessment released Wednesday by Code for America explores how U.S. state governments are preparing for the AI-powered public-sector transformation and identifies emerging trends within that shift.

Trends highlighted in the analysis include the rise of chief AI officers, investment in training programs, an evolving cybersecurity threat landscape, state-level policymaking, and secure sandbox environments for experimentation.

The Government AI Landscape Assessment explores AI readiness in three areas: leadership and governance, capacity building, and technical infrastructure and capabilities. The resource classifies states’ readiness levels in each of these areas under one of four categories: early, developing, established or advanced. The early classification includes states that have taken the initial steps in AI adoption, while the advanced classification recognizes states with sophisticated capabilities, frameworks and approaches.


States leading in readiness, according to this assessment, are Pennsylvania, New Jersey, and Utah, each of which received two “advanced” classifications and one “established” classification.

Each of these states has prioritized AI readiness. Pennsylvania has been testing and measuring AI for impact, and New Jersey is taking an economy-focused approach to AI and has been an early implementer of AI training. Utah has been an early AI adopter and even recently created an AI policy office that aims to answer societal AI questions.

Overall, in the category of leadership and governance, only three states were classified as advanced. Half, or 25, were classified as established; 16 as developing; and seven as early. Washington, D.C., was included as a state in this assessment. Utah and North Carolina were highlighted for their work in this area.In AI capacity building, four states were classified as advanced, 10 as established, 23 as developing, and 14 as early. New Jersey and Pennsylvania were highlighted for their work here.

In technical infrastructure and capabilities, three states were classified as advanced, 16 as established, 23 as developing, and nine as early. Colorado and Minnesota were highlighted for their work in this.

“This analysis demonstrates what many of us know to be true: states are leading the way when it comes to adopting AI to make government more efficient and effective,” Jenn Thom, Code for America’s senior director of data science, said in a statement.

The assessment was created by reviewing public materials, AI-focused legislation and policy, guidance and reports, news coverage, and direct input.

Debate has arisen recently about whether AI policymaking should occur at the state or federal level, with the consensus largely being that both should have a role in regulation. With the removal of a provision to enact a moratorium on state-level AI regulation from the federal budget bill, states retain the authority to enact policy to guide responsible AI use.





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Microsoft launches $4B artificial intelligence reskilling institute

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Microsoft unveiled a new initiative Wednesday that’s intended to bring artificial intelligence skills to millions of people around the world.

Microsoft Elevate will spend $4 billion in cash and technology donations to philanthropic, educational, and labor organizations over the next four years, as it seeks to accelerate the proliferation of AI technology.

Microsoft makes the AI tool CoPilot, and is a key partner of OpenAI, the maker of ChatGPT. The company is investing aggressively in the infrastructure needed to power its AI push, pledging to spend $80 billion on data centers this year.

The investments come as Microsoft lays off thousands of employees in in its home state, Washington, and globally.

RELATED: Latest Microsoft layoffs could hit 9,000 employees

“ One of the things that has changed the most dramatically about Microsoft is we’ve moved as a company — as our industry has moved as an industry — from one that spent almost every dollar it earned on employing people to what is in fact the greatest capital and infrastructure investment in the history of global infrastructure,” Microsoft President and Vice Chair Brad Smith said at a launch event in Seattle.

In an interview with KUOW, Smith said that restructuring is “ frankly something that should always be hard, but it is something that needs to be done for a company to be successful for many decades and not just a few years.”

Smith said Microsoft Elevate will employ about 300 people, and partner with organizations around the world on a variety of initiatives aimed at increasing AI literacy. The Microsoft Elevate Academy plans to help 20 million people earn AI skilling credentials to be more competitive in an uncertain job market.

“ I think in many ways it gives us the opportunity to reach everybody,” Smith said, “and that includes people who will be using and designing AI in the future, say the future of what computer science education becomes, people who are designing AI systems for businesses, but consumers as well, students and teachers who can use AI to better reach and prepare for helping students.”

The initiative also includes the creation of Microsoft’s AI Economy Institute, a think tank of academics that will study the societal impacts of AI.

The effect generative AI will have on education remains a source of much speculation and debate.

RELATED: Learning tool or BS machine? How AI is shaking up higher ed

While some educators are embracing the technology, others are struggling to rein in cheating and question whether the technology could undermine the very premise of education as we know it.

Regardless of the ongoing debate, Microsoft has always been at the forefront of bringing technology into the classroom, first with PCs and now AI. The company is betting that the resources it is devoting to Microsoft Elevate will help shape a path forward that allows AI to be more useful than disruptive in education and across the economy.

RELATED: AI should be used in class, not feared. That’s the message of these Seattle area teachers

“ There are many different skills that we’re all going to need to work together to pursue, but I think there’s also a North Star that should guide us,” Smith said. “It’s a North Star that might sound unusual coming from a tech company, but I think it’s a North Star that matters most. We need to use AI to help us think more, not less.”



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Artificial Intelligence and Criminal Exploitation: A New Era of Risk

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WASHINGTON, D.C. – The House Judiciary Subcommittee on Crime and Federal Government Surveillance will hold a hearing on Wednesday, July 16, 2025, at 10:00 a.m. ET. The hearing, “Artificial Intelligence and Criminal Exploitation: A New Era of Risk,” will examine the growing threat of Artificial Intelligence (AI)-enabled crime, including how criminals are leveraging AI to conduct fraud, identity theft, child exploitation, and other illicit activities. It will also explore the capabilities and limitations of law enforcement in addressing these evolving threats, as well as potential legislative and policy responses to ensure public safety in the age of AI.

WITNESSES

  • LTC Andrew Bowne, Former Counsel, Department of the Air Force Artificial Intelligence Accelerator at the Massachusetts Institute of Technology
  • Ari Redbord, Global Head of Policy, TRM Labs;  former Assistant United States Attorney
  • Zara Perumal, Co-Founder, Overwatch Data; former member, Threat Analysis Department, Google



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