If you automated your recruiting process with AI, what would your recruiters do?

The answer to that question isn’t that recruiters or any professionals must disappear. It’s that they must evolve, as Josh Bersin and Bill Pelster from The Josh Bersin Company explained during our recent AMS Masterclass in Singapore.

With this question, they captured the tension that many leaders feel today. AI is transforming how we hire, plan, and lead, but it’s also forcing us to rethink the very nature of work itself. In the past year alone, global tech leaders have already invested more than $1 trillion, creating intense pressure from investors and boards to realize returns. Ninety-two percent of CEOs report they are now heavily investing in generative AI with expectations of revenue growth, not just cost reduction. Yet only 23% believe their organizations can adjust rapidly enough. That pressure lands directly on HR.

Today, workers from the frontline to the boardroom have access to agentic AI tools that can execute tasks and make decisions within defined parameters. The result is a partnership between human judgment and digital capability poised to reshape how work gets done. But early results are mixed. One recent MIT study found that only about 5% of AI projects currently deliver positive ROI. The technology is powerful, but applying it well requires clarity, confidence, and reinvention, not just acceleration.

In our session, five key themes emerged that define how organizations can prepare for the next phase of the AI transformation. These takeaways highlight where agentic AI is already reshaping work and how HR leaders can turn its disruption into opportunity.

1. The Superworker era is here

The world of work has evolved over the past five decades toward more agile, skills-based, and self-directed models. Agentic AI is the next logical step.

Agentic AI allows people to operate at what the healthcare industry calls the ‘top of their license’. Nurses, for example, should spend most of their time on tasks that make the best use of their training while delegating or automating routine work. The same principle now applies across every industry.

This shift defines the Superworker: an employee augmented by AI. When digital agents handle repetitive or administrative tasks, employees can direct their attention to the activities where their judgment and creativity add the greatest value.

The economic case for this shift is clear. Over the past 35 years, as technology has amplified human capability, GDP per worker has risen by 280% while total employment has decreased by 32%. AI now accelerates that shift as organizations move from assistance to automation, agentic workflows, and eventually autonomy, expanding creativity, speed, and output by 100% to 300%.

The rise of the Superworker also raises the bar for HR. As boards and investors push organizations to accelerate AI adoption, the responsibility for redesigning roles, redeploying talent, and reskilling at scale falls squarely on HR and talent acquisition.

2. HR is an engine for reinvention

Many organizations today are using AI to make existing processes faster. That’s a useful first step, but it’s only the beginning. True transformation requires redesigning the work itself. During the session, Bill described this shift between the stages of AI adoption as a line in the sand:

  • On the left side are organizations using AI for incremental productivity, such as accelerating email drafting and candidate screening. The job itself remains the same; only its speed has improved. According to the session data, most organizations are clustered here, with a 10% to 30% increase in productivity.
  • On the right side are organizations using AI for reinvention rather than marginal improvement: questioning whether the job, process, or even the structure around it should exist at all. This is where the real transformation sits. The greatest gains in productivity and efficiency occur here, with cross-functional, multifunctional agents delivering productivity improvements between 100% and 200%. Autonomous systems drive gains above 300%.

This divide illustrates a broader principle. HR has long excelled at optimizing processes that may no longer add value. The opportunity with agentic AI is to question, simplify, and rebuild around what really matters. If the goal is growth, the solution might be to redeploy talent differently, automate low-value steps, or flatten the structure altogether rather than hire new candidates.

The most advanced organizations are already moving in this direction. They treat AI as a design partner, not as a tool. These businesses continuously adapt, empower employees to reinvent how they work, and measure success by outcomes, not activities. Research shows that dynamic organizations like these consistently generate 30% higher returns and outperform their peers during disruption because they combine agility with a deep investment in people.

Agentic AI serves as the lens for this reinvention. It helps leaders see which processes should be optimized, automated, and reimagined from the ground up. The result is a more productive, resilient, and human-centered operating model.

3. Talent acquisition is on the front line

One data point from our work with the Josh Bersin Group resonated with the room: roughly 75% of talent acquisition leaders said they were not involved in strategic decisions. Instead, they were being used as fulfilment centers, focused on ‘filling heads’ rather than shaping workforce strategy. That must change.

The job market slowdown adds to the urgency. As we discussed in the session, the U.S. economy recently created almost zero net new jobs, and many sectors are already seeing a task reduction between 10% and 40% through AI. Talent teams are among the first to feel the shift.

AI is already assuming much of talent acquisition’s transactional load, managing sourcing, screening, scheduling, and assessing candidates. Conversational AI can now conduct technical and behavioral screens. Digital twins are beginning to manage the negotiation back-and-forth that once consumed hours of recruiter time. These capabilities are accelerating rapidly, with some predictions suggesting that digital twins will be standard within 18 months.

The question for every talent acquisition leader now is, When AI handles most of the mechanics, what will recruiters do? The answer lies in redefinition. Recruiters will become talent advisors who guide hiring managers through market trends and skills gaps; advise on whether to hire, automate, or redeploy; and strengthen internal mobility by helping employees find their next opportunity inside the business.

This process is how AI creates capacity for more human work. Freed from repetitive tasks, recruiters can focus on problem-solving and relationship-building.

4. Leaders must close the AI gap

Waiting for AI to be ‘perfect’ feels safe, but in practice, it increases risk. Because AI adoption accelerates exponentially, organizations that hesitate are overtaken faster than they realize. Only 7% of CEOs report generating new revenue streams from AI today. One reason is leadership hesitation. Waiting for technology to mature widens the gap between AI capability and organizational readiness, creating organizational risk rather than safety.

The Supermanager is the leader who closes that gap between human capability and technological potential. These leaders encourage experimentation, protect time for learning, and model curiosity from the top. They listen to the frontline employees experimenting with automation, digital twins, and agentic tools and act on what they learn.

Future-fit leaders aren’t the ones who master every tool. They are the ones who shorten the distance between their organization and the AI curve by sponsoring experimentation and modelling the learning themselves. This leadership style is human-centered. It fosters innovation, encourages collaboration between humans and digital agents, and creates an environment where people feel empowered to test ideas and share results.

5. Flattening hierarchies accelerates mobility and profitability

The rise of Superworkers also has structural implications. As AI takes on more monitoring, routing, and reporting, traditional hierarchies start to compress. With fewer layers in the middle, decisions can move closer to the work. Accountability becomes clearer. Performance has a more direct impact on results.

Internal mobility is a critical part of this story. Our research with the Josh Bersin Group on dynamic organizations found that companies that are effective at moving people into new roles and projects are 31 times more effective across key business practices. And a PwC study of 2,700 organizations showed that companies with higher rates of internal movement were 27% more profitable.

In practice, this means that flattening and mobility go hand in hand. Fewer layers also make it easier to assess skills, reward impact, and align people with the work that matters most. With better insight into skills, potential, and workforce data from AI, organizations can redeploy talent quickly to where it’s needed most. Rather than hiring to grow, they can grow through the people they already have.

The time to act is now

What I heard at the session, and what I am taking back into our client conversations, is urgency with optimism. The rise of the Superworker is happening now. The capital being poured into AI will demand outcomes. The technology is moving faster than most organizations. Employees are, understandably, anxious. Thirty percent of recent U.S. college graduates are struggling to find white-collar jobs, and employee satisfaction has dipped to historic lows. The organizations that invest in empowerment, mobility, and transparent AI governance will be the ones that retain trust.

Our role is to make AI a confidence-building technology. Start with a few high-value processes. Give your people access. Pair experimentation with clear governance. And, above all, help your workforce see itself in the Superworker story, not outside of it.

At AMS, we’re working with clients to integrate AI into talent, to redesign talent acquisition for an agentic future, and to build leaders who can close the gap on the curve rather than wait for it to flatten.

If you’d like to explore how to do this in your organization, we should talk.