INFLUENCE PRO RESEARCH™
EXECUTIVE INTELLIGENCE BRIEF
IPR-EIB-003 | AUGUST 2026
THE FUTURE OF WORK
The Real Risk Isn't Job Loss. It's Transition.
Research • Insight • Adaptability
Executive Perspective
Much of the debate about artificial intelligence and the future of work has been reduced to a deceptively simple question:
Will AI take our jobs?
The evidence suggests that may be the wrong question.
Research examined for the Global Executive Intelligence Review™ 2026 points toward a considerably more complex transformation. Artificial intelligence, automation, demographic change, economic uncertainty and changing business models are simultaneously creating work, eliminating work and changing the skills required to perform work.
The central challenge may therefore not be the disappearance of employment.
It may be whether people and organizations can adapt quickly enough to the changing nature of work.
World Economic Forum research examined in the Review projects substantial employment creation and displacement occurring simultaneously. AI and information-processing technologies alone are expected to contribute to the creation of approximately 11 million jobs while displacing approximately 9 million by 2030. Robotics and autonomous systems are expected to create additional displacement.
Across the broader labour market, the WEF forecasts 170 million new jobs and 92 million displaced jobs by 2030.
On the surface, that represents positive net employment.
But aggregate numbers can conceal the more difficult problem.
The people displaced from declining occupations will not necessarily be the people positioned to fill the jobs being created.
Workers may face differences in skills, geography, education, compensation, age and access to retraining. A growing economy can therefore simultaneously experience labour shortages and significant worker displacement.
That distinction may define the future-of-work challenge.
Work Is Changing Before Work Disappears
The evidence also suggests that focusing exclusively on jobs may obscure an even larger transformation occurring inside jobs.
Employers estimated that in 2025 approximately:
- 47% of tasks were performed primarily by people;
- 22% primarily by technology; and
- 30% through a combination of people and technology.
By 2030, employers expect those three categories to become approximately equal.
That does not necessarily mean one-third of today's jobs disappear.
It means the division of work between people and technology is changing.
For executives, this distinction is critical.
Organizations that approach AI primarily as a technology acquisition may miss the larger transformation. The more consequential questions concern how work should be redesigned, which decisions should remain human, which can be automated, where human-machine collaboration creates greater value, and what capabilities employees will need within redesigned roles.
IBM research examined for GEIR reinforces this point. Its 2026 CEO study argues that AI is becoming an operating-model issue affecting leadership responsibilities, decision-making, collaboration, talent, technology and execution—not simply another technology implementation.
The future of work is therefore inseparable from the future design of organizations.
The Skills Transition May Be the Greater Challenge
Employers expect approximately 39% of workers' existing core skills to change by 2030.
Technical capabilities, including AI, big data, cybersecurity and technological literacy, are increasing rapidly in importance.
But the research also identifies enduring human capabilities:
Analytical thinking.
Resilience and adaptability.
Leadership and social influence.
Creative thinking.
Motivation and self-awareness.
This combination matters.
The emerging workforce does not appear to require a choice between technical capability and human capability. Increasingly, it requires both.
IBM's CEO research illustrates the scale of the challenge. CEOs surveyed expected that between 2026 and 2028, 29% of employees would require reskilling for a different role and 53% would require upskilling to perform their existing role more effectively.
Yet there is an important disconnect between executive confidence and workforce behaviour.
Only 25% of employees reportedly use AI regularly in their work, while 86% of CEOs believe employees possess the skills required to collaborate with AI. At the same time, 83% of CEOs believe successful AI implementation depends more upon people's adoption than upon the technology itself.
That raises an uncomfortable question:
Are organizations as AI-ready as their leaders believe they are?
The Career-Ladder Problem
One of the less discussed consequences of automation may occur at the beginning of people's careers.
Clerical, administrative and junior knowledge-work roles are among the occupations facing significant pressure.
But these positions have traditionally performed another function.
They are where people learn.
Entry-level employees acquire institutional knowledge, observe experienced colleagues, develop judgment, make lower-consequence mistakes and gradually progress toward specialist, managerial and leadership positions.
If AI increasingly performs the work traditionally assigned to junior employees, organizations may solve an immediate productivity problem while unintentionally creating a longer-term talent problem.
The GEIR research specifically identifies the possibility that declining clerical and junior knowledge-work positions could remove traditional pathways through which employees gain experience and institutional knowledge.
Executives therefore need to consider not only:
What work can AI perform today?
but also:
If AI performs the work through which people traditionally learned, how will we develop the experienced people we need tomorrow?
This may become one of the defining workforce-development questions of the AI era.
The Future of Work Is Not Just Technology Work
Another misconception is that the future labour market will simply become a technology labour market.
Technology occupations, including AI specialists, data specialists and software developers, are among the fastest-growing roles by percentage.
But some of the largest absolute employment gains are expected in areas such as:
- healthcare and nursing;
- education;
- construction;
- delivery and logistics;
- sales;
- food production;
- operations management;
- project management; and
- other physical and service occupations.
Technology will reshape these occupations, but it will not necessarily replace them.
The future workforce is therefore likely to be considerably more diverse than a simple division between “technology jobs” and “jobs replaced by technology.”
The Executive Challenge
The evidence reviewed by Influence Pro Research suggests that the central workforce challenge created by AI and related macro-trends may not be the total disappearance of employment.
It is the speed, scale and unevenness of transition between declining and growing forms of work.
For executive leaders, this changes the conversation.
The strategic questions become:
Which jobs will change before they disappear?
Which tasks should be automated, and which should be augmented?
Can our people develop new capabilities at the speed technology is changing?
Are we redesigning work, or simply introducing new tools into old operating models?
How will we develop future managers and specialists if traditional entry-level pathways decline?
Can we redeploy people whose existing skills become less valuable?
And does our organizational culture have the capacity to undergo this transition repeatedly rather than once?
These are not primarily technology questions.
They are questions of leadership, workforce strategy, organizational design and adaptability.
A Different Way to Think About the Future of Work
Predictions about employment inevitably contain uncertainty.
Technology adoption will vary by industry. Economic conditions will change. New occupations will emerge that cannot yet be clearly defined. Some expected productivity gains will materialize; others may not.
But the direction of change is increasingly difficult to dispute.
AI is moving from experimentation into workflows. Automation is expanding beyond repetitive physical work into knowledge work. Human and machine capabilities are becoming increasingly interconnected.
The organizations best positioned for this environment may therefore not be those that make the most accurate prediction about exactly what work will look like in 2030.
They may be those capable of adapting as those answers become clearer.
That requires something more enduring than technology adoption.
It requires Organizational Adaptability™—the capacity to recognize change, redesign work, develop people, reallocate resources and continuously evolve as conditions change.
The future of work will not arrive on a particular date.
It is already being negotiated task by task, role by role and organization by organization.
About the Research
This Executive Intelligence Brief draws upon workforce and organizational findings examined as part of the Global Executive Intelligence Review™ 2026 — Founding Edition, an Influence Pro Research™ publication synthesizing 28 major international research sources across artificial intelligence, workforce transformation, economics, geopolitics and technological change.
The Global Executive Intelligence Review™ 2026 is now available in Kindle and paperback editions through Amazon.
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