According to Forbes, Joe McKendrick is an author, independent researcher and speaker who has been exploring innovation, information technology trends and markets for decades. He specifically covers the impact of AI on jobs, including challenging premature assumptions in pieces like “Generative AI As A Killer Of Creative Jobs? Hold That Thought.” McKendrick has served as co-chair of the annual AI Summit in New York since 2021 and regularly contributes to prestigious publications including Harvard Business Review and ZDNet on technology innovation issues. His background includes serving as communications and research director of the Administrative Management Society, an international professional association focused on IT and business management knowledge. This extensive experience provides a crucial perspective as we examine what’s truly changing in the current technological landscape.
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The Patterns We’ve Seen Before
Having covered technology transitions for multiple decades, McKendrick represents a rare breed of analyst who’s witnessed multiple waves of workplace transformation. What’s often missing from current AI discussions is historical context—we’ve been here before with previous technological revolutions. The personal computer revolution of the 1980s, the internet boom of the 1990s, and the mobile computing shift of the 2000s all generated similar fears about job displacement. Each time, the doomsday predictions proved overstated, though the transitions were genuinely disruptive. The key insight from these historical patterns is that technology typically transforms jobs rather than eliminates them entirely, creating new roles that didn’t previously exist while making others obsolete.
What Makes This AI Wave Different
While historical patterns provide comfort, there are legitimate reasons why current AI advancements represent a qualitatively different challenge. Previous technological revolutions primarily affected manual and routine cognitive tasks. Today’s generative AI systems are demonstrating capabilities in creative domains—writing, design, strategy formulation—that were previously considered exclusively human domains. This isn’t just another productivity tool; it’s a technology that can potentially replicate core human cognitive functions. The speed of adoption is also unprecedented—where previous technologies took years to diffuse through organizations, AI tools are being adopted at breathtaking pace due to cloud distribution and intuitive interfaces.
The Real Risk Isn’t Job Loss
The most significant threat from AI may not be mass unemployment but rather a different set of challenges that receive less attention. We’re facing potential issues around skill obsolescence at an unprecedented scale, where workers may find their hard-won expertise devalued almost overnight. There’s also the risk of creating a bifurcated workforce where those who can work effectively with AI tools see their productivity and compensation soar, while those who struggle with the transition face diminishing opportunities. Additionally, we’re underestimating the organizational change management challenges—retraining entire workforces, redesigning business processes, and developing new management practices for AI-augmented teams will be enormously complex undertakings that many organizations are unprepared to handle.
Navigating the Transition Successfully
The organizations that thrive in this new environment will be those that view AI as a collaborator rather than a replacement. This requires fundamental shifts in how we think about work design, education systems, and career development. We need to move beyond the simplistic “humans versus machines” narrative and focus on human-machine collaboration models. This means redesigning education to emphasize uniquely human skills—critical thinking, creativity, emotional intelligence, and ethical reasoning—while treating technical skills as continuously evolving capabilities that require lifelong learning. Companies that succeed will be those that invest as heavily in change management and workforce development as they do in the technology infrastructure itself.
Why Experienced Voices Matter
In an environment saturated with both AI hype and alarmism, the perspective of seasoned analysts like McKendrick becomes increasingly valuable. Having observed multiple technology cycles, they understand that the initial excitement and fear typically give way to more nuanced realities. The most accurate predictions usually come from those who’ve seen how technologies actually get adopted in real organizations with all their complexities and constraints. As we move forward, we need more voices that can separate genuine transformation from temporary excitement and help organizations make strategic decisions based on realistic assessments rather than either utopian or dystopian extremes.
