Myth 9: With Ai, Employees Are Less Important

By Al Adamsen  |  Future of Work Advisors

In 2000, a tech founder, amidst the dot-com bust, matter-of-factly shared that his business would be so much better off without employees. He was frustrated, but his sentiment was serious. He wanted to automate and outsource everything so he could just focus on prospects, customers, and making money.

Fast forward to today: Ai, robotic automation, and global talent markets now provide much of the automation and outsourcing he once wished for. The need for employees in some industries, in some businesses, is consequently shrinking. This, however, does not mean employees are no longer needed. It simply means their roles are evolving; and if a company has deemed those roles worth keeping on the payroll full-time, then they’re almost certainly essential.

With this backdrop, there’s no credible leader I know who would walk into a board meeting and declare, “Our employees don’t matter anymore.” Yet actions speak louder than words. Decisions such as cutting headcount to hit short-term financial targets or to support tech-first transformations in the name of “efficiency” send the same message: employees are viewed as expendable, interchangeable, and easily replaced by technology.

The truth is different. Workforce decisions are not just financial, they’re strategic. They reveal what the CEO, the board, and the executive team truly value and believe. Some leaders minimize headcount, betting on Ai and technology to carry the load. At times, this may be a responsible decision. Other times it may grossly downplay the unique, enduring value of people.  Human beings, after all, through their creativity, relationship equity, and ability to anticipate how today’s decisions will shape tomorrow – something Ai doesn’t do very well just yet – are the real sources of organizational elasticity, adaptability, and long-term competitive advantage.

So, as Ai and tech-enabled automation commoditize tasks, processes, and even insights, the true differentiator is not the technology itself, but how employees use that technology and work with one another: how they communicate, make decisions, and create value. Yes, some organizations may need fewer employees than in the past, but far from being less important, employees are increasingly the ultimate differentiator.

|  Evidence from Leading Researchers

While it’s easy to make broad claims about the importance of people in the age of Ai, the evidence is compelling. Researchers across disciplines – from psychology to robotics, sociology to ethics – consistently affirm that human qualities remain irreplaceable in driving performance, trust, and innovation. Their insights reveal not only what Ai can and cannot do, but also where leaders must place their emphasis if they want resilient, future-ready organizations.

Human-Centered Design Matters

Stanford’s Fei-Fei Li argues that Ai should be built to augment human potential, not displace it. For leaders, this means centering strategy on inclusion, well-being, and growth – not just algorithms and efficiencies.

Human Intelligence with Machine Efficiency

Psychologist and author of I, Human Tomas Chamorro-Premuzic reminds us that while Ai is brilliant at speed and scale, it cannot replace human imagination, curiosity, or emotional intelligence. Organizations that neglect these dimensions risk creating hollow cultures with no soul.

Empathy & Connection Are Irreplaceable

MIT’s Cynthia Breazeal shows that Ai succeeds when it supports emotional connection and human goals. Similarly, Justine Cassell has demonstrated that social cues, storytelling, and rapport – the glue of collaboration – remain uniquely human.

Beware Tech Replacing True Connection

MIT sociologist Sherry Turkle warns of confusing technological connection for genuine human connection. Leaders who undervalue employees in favor of digital shortcuts risk undermining trust and belonging, eroding the very foundation of performance.

Curiosity Drives Innovation

Anima Anandkumar of Caltech reminds us that while Ai can generate outputs, only humans can ask the bold questions, push boundaries, and bring the imaginative leaps that define true innovation.

Ethics and Oversight Are Human Work

Finally, ethicist Wendell Wallach emphasizes that fairness, accountability, and values must remain in human hands. Employees are not just operators of systems – they are the moral compass of organizations navigating Ai’s scale.

Together, these voices highlight a consistent truth: Ai can enhance work, but it cannot replace the qualities that make organizations truly human. For leaders, the research makes the path clear: if you want performance, innovation, and trust, you must invest in the people, experiences, and culture that carry those qualities forward.

|  The Potential and the Risks

Executives today face a paradox. On one hand, generative Ai tools like ChatGPT-5, Gemini, Claude, and Perplexity are delivering measurable productivity and creativity gains across industries. On the other, many organizations are leaning into Ai as a lever for workforce reduction, risking culture, trust, and long-term competitiveness. The difference lies not in the technology itself, but in how leaders choose to deploy it.

So while executives often focus on strategy, governance, and financial impact, it’s equally important to ask: what are employees themselves experiencing as Ai enters their daily work? Recent research sheds light on how workers perceive, adopt, and adapt to these tools, and the insights are both encouraging and cautionary.

1. Potential: Productivity Gains and Emotional Boosts

• A 2025 Procter & Gamble field experiment showed individuals using GPT-4 or GPT-4o performed on par with two-person teams, while Ai-assisted teams produced the highest-quality solutions. Less experienced employees also reported improved emotional well-being when Ai was part of the workflow.
  
  
• A 2023 – 24 MIT Sloan study found consultants using generative Ai boosted performance by up to 40%, with gains in quality, creativity, and client readiness, not just speed.
  
  
• A May 2025 Harvard Business Review study found professionals collaborating with Ai produced faster, higher-quality outputs but also reported lower motivation. The message: productivity gains alone won’t sustain performance without parallel investment in purpose, autonomy, and connection.
  
  

2. Risk: Misuse, Misalignment & Social Bias

• A 2025 MIT study revealed that 95% of enterprise Ai deployments had no measurable profit impact, not because the models were weak, but because of poor integration into workflows.
  
  
• A Duke University study (2025) found that employees using Ai tools like ChatGPT or Claude were often perceived by peers as less competent or hardworking, a subtle but damaging bias that can erode adoption, trust, and culture.
  
  
• Layoffs tied to “Ai efficiency” may deliver short-term savings, but risk hollowing out culture, draining creativity, and eroding trust, the very human capabilities that make Ai effective.
  
  

3. Divergence: Leaders’ Contrasting Approaches

• A 2024 Deloitte survey reported that 69% of tech leaders plan to expand teams as Ai scales, investing in hybrid human-Ai skill sets. Similarly, Morgan Stanley (2024) projected Ai will create more jobs than it eliminates, especially in leadership, compliance, and governance.
  
  
• But that’s only part of the story. Many organizations are using Ai to justify headcount cuts. While financially expedient, this approach often results in burnout, disengagement, and talent flight, a net loss in competitiveness.
  
  
• A Brookings report (Feb 2025) estimated that generative Ai already impacts at least 10% of tasks for 85% of workers, with 30% of workers seeing 50% or more of their tasks affected. The takeaway? Leaders must intentionally integrate Ai rather than allow it to disrupt work haphazardly.
  
  

4. The Employee Experience: Gains and Anxiety

• The 2024 Microsoft & LinkedIn Work Trend Index shows 75% of knowledge workers already use Ai, with over 80% reporting gains in creativity, focus, and efficiency.
  
  
• Temple University research (2025) confirms that when Ai handles repetitive tasks, employees report less stress, more creative energy, and higher emotional engagement.
  
  
• Research from Erin Eatough and Shonna Waters (2025, Fractional Insights’ Angst-Index) shows that while Ai can free capacity, 44% of employees still report workplace “angst” related to insecurity, stagnation, or obsolescence.
  
  

Taken together, these findings highlight a clear truth: Ai’s value is not automatic. It depends on how leaders align technology with culture, trust, and human potential. Ai can expand creativity, focus, and well-being, but without careful integration, it can also fuel disengagement, fear, and lost trust.

For executives, the implication is clear: the question is not whether Ai will change work, but whether you will create the conditions where your people thrive alongside it. 

|  What to Do

If employees are the differentiator, what should leaders do? It’s not just about adopting Ai, as stated, it’s about creating the right conditions for humans to thrive alongside it. Here are 12 key actions to consider:

1. Get the Right People in the Room
   Complex, Ai-enabled decisions require cross-functional voices, not just data scientists and engineers, but also HR, operations, finance, compliance, and, when appropriate, frontline employees who know the work best.
   
   
2. Build Ongoing Governance & Decision-Making
   Establish continuous oversight of Ai’s role in work, with mechanisms for learning, risk assessment, and course correction. Governance and decision-making must be dynamic, not one-offs.
   
   
3. Workforce Planning & Workforce Size
   Treat workforce size as both a financial and strategic decision. Balance efficiency with the recognition that the capability and capacity of employees are sources of skills, creativity, resilience, relationship equity, and more.
   
   
4. Organizational Design for Agility
   Rethink structures, processes, and reporting lines for an Ai-augmented world. Prioritize agility, collaboration, and distributed decision-making, ensuring humans and machines reduce friction, not create it.
   
   
5. Involve Experts in Human & Organizational Behavior
   Partner with psychologists, organizational scientists, and ethicists. Technical fixes alone cannot address the human dynamics of Ai adoption.
   
   
6. Measure What Matters
   Track not just outputs but culture, trust, collaboration, and well-being, the true drivers of sustained performance in an Ai-enabled workplace.
   
   
7. Redesign Roles for Human Strengths
   Let Ai handle the repeatable and transactional. Elevate humans to the empathetic, creative, ethical, and strategic roles where their value is unique and multiplies value.
   
   
8. Clarify Human–Ai Dynamics
   Make it explicit: are we augmenting employees with Ai, or are employees being asked to add value on top of the tech? This distinction shapes both culture and outcomes.
   
   
9. Study Work & Capacity Closely
   Recognize that Ai often adds hidden work (monitoring, training, oversight). Use workflow analysis and employee input to evaluate both how work is done and whether workloads are sustainable at the individual, team, and organizational levels.
   
   
10. Understand Employee Experiences
    Go beyond surface metrics. Use ongoing surveys, interviews, listening, and ethnographic research to understand how employees feel, engage, and grow with Ai tools.
    
    
11. Invest in Learning & Growth
    Provide opportunities for employees to build Ai literacy along with human strengths like curiosity, creativity, adaptability, and emotional intelligence. Help people see Ai as a path to growth, not obsolescence.
    
    
12. Prioritize Transparency & Ethics
    Be clear about how Ai is being used, what it means for roles, and how decisions are made. Transparent, ethical practices build trust, credibility, and alignment.

|  Conclusion

The belief that Ai makes employees less important is dangerously misguided. Ai can accelerate productivity and automate routine work, but it cannot replace the human spark that drives strategy, innovation, and culture.

As Tomas Chamorro-Premuzic reminds us, machines may be smart, but only humans can be wise. Fei-Fei Li calls on us to keep Ai human-centered. Sherry Turkle warns against mistaking digital efficiency for authentic connection. And Anima Anandkumar highlights the irreplaceable power of human curiosity.

And, as my friend Raquel Roca observes, the future belongs to the knowmads, workers who are adaptable, creative, and resilient. These workers, far from being expendable, will define the unique identities of organizations in a world where technology is everywhere and differentiation ultimately comes only from the human touch.

Finally, the call to executives is clear: choose wisely. You can treat Ai as a cost-cutting lever, eroding trust and culture, or you can treat it as a catalyst for human potential, creating workplaces where people thrive and, in turn, where organizations excel.  Contrary to the myth, the reality is, that in the age of Ai, employees don’t matter less, they now matter more than ever.

To learn more about the other Myths click here.  And to learn how to assess your organization’s adaptive readiness and, in turn, build executive decision-making processes rooted in timely, relevant, and actionable insight, follow and connect with me here on LinkedIn.  Finally, be sure to subscribe to the Future of Work Advisors Newsletter.