Our opportunity to rethink human capability as we rush to redesign work
by Julian Reeve
06.12.2026
As news unfolded about AI this past week, I found myself watching three separate stories collide.
Sam Altman and OpenAI’s chief scientist publicly argued that a future where everything is automated would be “dangerous” and “unfulfilling,” prompting thousands of organizations to put the brakes on implementation strategies. Other corporate leaders questioned their return on investment, voicing further concern about cost amid the inability to demonstrate measurable returns. Major towns and city councils were forced to reckon with the building of massive data centers, with growing public concerns about power usage, water consumption, and AI-related job displacement influencing decisions.
Growing unrest about the development and implementation of AI makes one thing clear: we’re out of the honeymoon phase and into reality — a critical moment that presents huge opportunity for those willing to look.
The rush to adopt AI has largely been fueled by the desire for lower costs and higher returns, with the assumption that AI will become more capable than humans driving early integration. Now the initial push is over, and with AI still some way to go in its development, organizations are designing work based on current human and AI capability while leaning on the hope that AI will eventually do everything they believe it can in the future.
This approach is risky and potentially expensive. Lack of certainty around AI’s eventual capability could drive decisions that cannot be realized, forcing organizations to capitulate and start again. That same ambiguity could lead to the search and procurement of workers aligned with specialized skills that may ultimately prove unnecessary or obsolete.
Some organizations are willing to accept the consequences of this uncertainty, arguing they do not have a choice but to push forward despite the confusion. Others are taking stock of their current position and asking a fundamentally different question:
What happens if we challenge current norms and assumptions about human capability to predict better results?
The idea of thinking differently about human capability isn’t new. The industrial revolution forced a major reckoning with ability and skill as decisions on whether or not to adopt machinery into workflows became more urgent. Entrepreneurs wrestled with their desire for higher productivity and profit, ultimately building systems that measured human contribution through productivity, consistency, and scale.
Perception of human value shifted. Machines were implemented to solve the productivity problem while workers were asked to conjure alternative attributes to offer value. Factory owners asked those more naturally connected to emotional intelligence to take on more managerial and supervisory roles, leaving other workers — skilled only with their hands — to face a more complicated future.
Today, organizations and workers are confronted with a similar challenge. The traditional acceptance of productivity, efficiency, intelligence, and influence as predictable indicators of capability are fundamentally challenged by AI’s ability to automate complicated tasks and provide exponential knowledge at scale.
What’s more, standardized assessment and psychometric testing previously relied upon to provide strong predictions for success and fit are left wanting as we’re not even sure what we’re searching for.
The question of where humans will fit and the value they need to offer is an ongoing debate, with Sam Altman saying this week that human judgment, values, and direction-setting remain vital for the future of work. Taste, trust, and discernment are other attributes being promoted as key differentiators, with adaptability an omnipresent quality of choice among those leading the charge.
An alternative solution is synthesis — a unique quality largely overlooked until now. The human ability to fuse attributes already in possession in ways not yet explored to produce differentiated results is an exciting possibility, and something worth considering in greater depth as we try and solve the puzzle.
Take, for example, the synthesis of identity, creativity, and judgment. Would someone with a much deeper sense of self, advanced creativity skills, and strong discernment and judgment ability be able to produce work of substantial quality? Yes, that’s a likely outcome.
But what if that same human understood how to fuse all three components in ways that produced an even better outcome? Would understanding the relationship between each and how to optimize them accordingly become a new capability?
That knowledge, and the work it produces, may be a strong candidate for focus as we continue to redefine the relationship between human and machine contribution. As more technology leaders acknowledge the ongoing need for human contribution, human capability is worth deeper evaluation and investment.
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This essay is part of The Intentional Creative series, my ongoing exploration of human capability, identity, creativity, judgment, and sustainable performance as technology transforms the way we work.
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