Despite the tumult of headlines surrounding the current wave of artificial intelligence-fueled innovation and deepening business automation worldwide, the stories highlighting significant job losses remain the most alarming. The World Economic Forum predicted with confidence that 85 million jobs will have disappeared as a direct result of AI-driven optimization and efficiency by the end of 2025.
And 2026 may prove even more disruptive. As of this writing, further automation is being actively planned, with approximately 18 percent of the global workforce—potentially affecting up to 300 million jobs—under consideration for automation within the next two years, according to some estimates.
On a more optimistic note, however, AI adoption is predicted to create approximately 97 million new jobs across various sectors in the coming years, presenting a significant opportunity for businesses to accelerate how they plan, operate, and grow with expanded AI capability. Fully 50 percent of people believe AI likely will assume much of the work currently performed by humans within the next 50 years.
Taking a Strategic Stance
For organizations with the resources and capability to move quickly on AI adoption, the benefits extend beyond immediate efficiencies and faster business cadence. This will prove especially critical as workforces age and newly graduated Generation Z workers struggle to meet the bar raised by AI for entry-level tasks. Corporations will need to take a stronger, more strategic stance on training, retraining, and reskilling their human capital.
At the individual level, workers are—and will remain—under pressure to adapt to automation and AI on a near-constant basis as its capabilities improve. The uncomfortable truth for every worker, from the front desk operator to the C-suite, is that staying ahead of the AI capability curve to avoid having your role placed on the efficiency chopping block will require a fundamental shift from today’s sporadic, sluggish approach to training.
Additionally, organizations face mounting pressure to ensure their workforces remain current and compliant amid growing threats from bad actors using AI to infiltrate systems. Regulatory compliance also has become non-negotiable, as recent GDPR violations and their substantial fines have demonstrated.
Individuals—empowered by their employers—must take greater responsibility for regular skills development and refinement. However, this presents a challenging proposition for employees already at risk of burnout from near-constant retraining pressure. The traditional days of assigning compliance training and chasing completion are rapidly disappearing.
Only by enabling daily and weekly individual learning activity within a supportive corporate culture that encourages consistent, positive, and habitual reskilling can companies and individuals hope to succeed as the AI innovation treadmill accelerates.
The Solution: Strategic Learning Engagement
Leveraging insights from behavioral science research on motivation, positive habit formation, and gamification—paired with micro-rewards and recognition systems—companies can drive unprecedented levels of engagement. Research demonstrates that tangible rewards are particularly effective at increasing engagement and output, especially for less inherently interesting but necessary tasks such as compliance training.
By combining micro-credentialing with diverse digital and blended learning programs, and pairing them with meaningful recognition that rewards positive, repeatable learning behaviors, organizations can better meet and personalize employee needs. When employees are given agency and choice in how and when they undertake training, they essentially drive their own development without requiring constant managerial oversight.
Even more proactively, employees who are recognized for their training initiatives stay well ahead of necessary skills acquisition without requiring organizations to overhaul skills development initiatives every few years. This approach essentially flips the traditional model from an HR push to a strategically advantageous employee pull.
Furthermore, research shows that when rewards are designed to be informational rather than controlling—recognizing competence and achievement rather than simply participation—they can actually enhance intrinsic motivation rather than undermine it. Achievement-based recognition linked to demonstrated mastery creates stronger engagement and longer-lasting behavioral change than completion-based approaches.
A workforce enabled with an agile learning mindset that is intrinsically motivated and regularly recognized provides the adaptability companies need to capitalize on opportunities presented by AI disruption. Simultaneously, it buffers the workforce against negative effects when market downturns and competitive pressures inevitably occur.
The Question Every Organization Must Answer
As AI reshapes the employment landscape at an unprecedented pace, organizations face a fundamental choice: Will they continue managing learning as a compliance checkbox exercise while the workforce falls behind, or will they cultivate a culture where continuous development becomes as natural and rewarding as the work itself? The 85 million jobs already lost won’t return, and the 97 million emerging roles simply won’t wait for stragglers.
Perhaps the more urgent question isn’t whether organizations can afford to invest in a reimagined strategic learning engagement but whether they can afford not to. After all, in a world where AI never stops learning, can your people?
References:
https://sqmagazine.co.uk/ai-job-loss-statistics/
Cerasoli, C. P., Nicklin, J. M., & Ford, M. T. (2014). Intrinsic motivation and extrinsic incentives jointly predict performance: A 40-year meta-analysis. Psychological Bulletin, 140(4), 980–1008. https://doi.org/10.1037/a0035661
Cameron, J., Pierce, W. D., Banko, K. M., & Gear, A. (2005). Achievement-based rewards and intrinsic motivation: A test of cognitive mediators. Journal of Educational Psychology, 97(4), 641–655. https://doi.org/10.1037/0022-0663.97.4.641
Hidi, S. (2016). Revisiting the role of rewards in motivation and learning: Implications of neuroscientific research. Educational Psychology Review, 28(1), 61–93. https://doi.org/10.1007/s10648-015-9307-5
European Data Protection Board (2024). GDPR Fines and Penalties. EDPB Annual Report. https://www.edpb.europa.eu/
