When the Machines Learn, Humans Must Evolve

S-Curves - Week 5

By Rick Aman

on November 02, 2025

The great aim of education is not knowledge, but action. — Herbert Spencer

Last week’s article explored The AI S-Curve, how automation and intelligent systems are transforming the nature of work. The speed of technology adoption has never been greater, and the implications for human capability are profound.

Leaders now face two distinct curves: Technology Adoption and Human Adaptation. The technology curve rises sharply; the human curve lags behind. The space between them, the adaptation gap, is where organizations either stagnate or reinvent themselves.

Technology accelerates change. Only humans can give that change meaning. Boards and CEOs must focus not on resisting automation but on preparing their people to thrive within it.

The Workforce Transformation Imperative: Higher Education on the Next S-Curve

Higher education stands at a pivotal point. The same forces transforming industry, automation, artificial intelligence, and digital disruption are now reshaping education itself. Colleges and universities can no longer operate at the top of an old S-curve while the next one accelerates beneath them.

The 2025 Future of Work with AI Agents study from Stanford’s Digital Economy Lab and SALT Lab (Shao et al., 2025) confirms what many already sense: AI will automate an increasing share of tasks across nearly every field. Yet this is not a story of job loss, it’s a story of job redesign. Routine work is giving way to roles that demand judgment, empathy, creativity, and complex reasoning.

This shift demands a parallel transformation in how higher education prepares learners. Institutions must evolve from credentialing past skills to curating future capabilities, integrating technical fluency, human insight, and adaptive learning models.

The lesson of every S-curve is clear: growth follows experimentation, not preservation. The institutions that lead the next era will be those that recognize when their current model has plateaued and have the courage to leap to the next curve before being forced to.

The role of higher education is no longer to merely respond to change, but to anticipate it, shaping learners and organizations to thrive amid continuous innovation.

The New Currency: Skills; Not “Butts in Seats”

For more than a century, higher education has measured learning in hours, credits, and degrees. While those measures still matter, degrees remain vital for advanced practice, leadership, and credibility; they are no longer sufficient.

Industry now evaluates readiness through demonstrated competency: Can this person perform at the level the job requires? That question transcends transcripts.

Today’s workforce values competency-based models that verify what learners can do, not just what they have completed. Micro-credentials, digital badges, and stackable certificates enable individuals to demonstrate market relevant skills. These credentials give employers evidence of capability and provide workers with portable proof of value.

Higher education must build ecosystems where degrees and competencies coexist. Degrees anchor theory and depth; credentials capture agility and application. Together, they form the new currency of employability.

Learning Velocity and Adaptability

Adaptability has become a competitive advantage. The most resilient organizations are not those with the newest tools, but those that learn at about the pace of the environment changes.

Learning velocity depends on more than professional development budgets, it requires a culture where curiosity, experimentation, and reflection are encouraged. The ability to unlearn and relearn may soon define career longevity as much as technical skill. If an organization’s learning rate falls below the rate of technological change, obsolescence begins. Investing in human capability is no longer a cost, it’s a strategic hedge against disruption.

The Competency Model Mindset

To build adaptive systems, leaders must shift from knowledge transmission to competency demonstration. A competency model defines the specific skills, behaviors, and mindsets required for success and creates clear pathways for development.

Strong models do more than list skills, they Align workforce development with strategic goals, Clarify expectations and define excellence, Support stackable growth, linking learning to mastery and credentials, and Enable rapid reskilling as technology evolves.

Boards and CEOs who champion competency frameworks send a powerful message: performance and potential are measured by contribution, not seat time.

Human Infrastructure as a Strategic Asset

Digital transformation captures headlines, but human transformation determines whether technology delivers value. Closing the adaptation gap requires deliberate investment in people systems.

Key priorities include:

Reskilling and Upskilling Pipelines – Continuous learning systems aligned to verified regional labor data.
Micro-Credential Pathways – Embedded short-cycle credentials within degree programs so learners can stop, start, and advance fluidly.
Faculty and Staff Readiness – Time and support to master emerging technologies and flexible delivery models.
Culture of Lifelong Learning – Model adaptability from the top; create safe spaces for experimentation and iteration.

Human infrastructure determines whether institutions can pivot when disruption hits. The organizations that thrive will plan their human curves as intentionally as their technology curves.

Leadership and Board Implications: Building Human Capacity for the Next Curve

As organizations invest in technology and innovation, the question is shifting from what to fund to how leadership sustains and integrates those investments. Leadership must serve as the bridge between acceleration and understanding.

Boards and CEOs can no longer view workforce development as a routine expense, it is the frontline of relevance and strategic risk management for higher education. In a changing economy with emerging technologies, even the most advanced systems hold little value if graduates and employees lack the skills and adaptability to use them.

Traditionally, universities viewed a degree as a journey of the mind; cultivating wisdom, character, and civic responsibility. Today, many students see it as a strategic investment, a path to employability, financial security, and relevance in a shifting economy.

Higher education now stands between these expectations: preserving the ideals of intellectual formation while ensuring that graduates leave with the skills and flexibility the workforce demands.

The measure of success is not just retention or completion but application, what learners and employees can do with what they know. When human capacity catches up to the technology curve, institutions are prepared for the next one.

I often close board retreats with a Preferred Future Statement exercise, asking leaders to describe their organization three years ahead when people and technology are in sync. That shared vision becomes the anchor for decisions on budgets, programs, and partnerships. It helps boards see success not only as technological progress but as human advancement, the truest sign of readiness for the next curve.

Closing the Adaptation Gap

Consider again the two S-curves: one representing the rapid rise of technology, the other the slower but essential rise of human adaptation. The space between them, the adaptation gap, holds both anxiety and opportunity. The work of leadership is to close that gap through deliberate investment in competencies, learning systems, and culture. The faster the human curve rises, the greater the organization’s resilience and value.

Technology may disrupt jobs, but leadership can redefine work. Every board and executive team should ask three questions:

What skills are fading? Which competencies no longer create advantage?
What must be learned next? Which emerging skills will sustain relevance and revenue?
How will we prove it? What evidence will demonstrate real capability and readiness?

These questions form the blueprint for the Human S-Curve.

Summary

Week 5 of the Colliding S-Curves series explores The Human S-Curve, the arc of skills, adaptability, and competency that must rise to meet accelerating AI and automation. Boards, professional organizations and CEOs can close the adaptation gap by investing in reskilling systems, micro-credentials, and cultures of lifelong learning that turn disruption into advantage.

Source: Shao, Y., Zope, H., Jiang, Y., Pei, J., Nguyen, D., Brynjolfsson, E., & Yang, D. (2025). Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce. Stanford Digital Economy Lab & SALT Lab. https://arxiv.org/pdf/2506.06576.pdf

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Aman & Associates Insight

At Aman & Associates, we help boards, executive teams, and professional organizations align their human and technology curves through AI-assisted futuring, mission-focused strategy grounded in Ikigai principles, and strategic leadership development. Our work centers on building adaptive institutions prepared for the AI and technological s-curve disruption already underway.

Every organization faces colliding curves. The goal isn’t to slow the technology line; it’s to accelerate the human one.