Every CEO and executive enthusiastically slashing headcount in anticipation of an AI-driven productivity boom should read a new meta-analysis from the UK’s Royal Docks School of Business and Law. It suggests those decision-makers might be optimizing for the wrong thing.

While mass layoffs have an immediate measurable payoff, the study says the best use of AI is to boost human cognition and decision-making, not replace it. The research looks at how people can leverage AI to improve how knowledge is created and shared.

The study found that AI excels at tackling complex tasks quickly, while people excel at tasks involving judgment, meaning, and responsibility.  AI can also improve an organization’s “collective intelligence” by pulling together facts and ideas from various subjects into one clear picture.

For example: 

• A hospital where AI surfaces relevant research from specialties the treating physician doesn’t follow, but the doctor still makes the call
• A law firm where AI cross-references precedent across jurisdictions in minutes, while partners decide the best argument for the client
• A product team where AI synthesizes feedback from support tickets, sales calls, and app reviews — but humans decide what to build

AI use is far more effective than AI or people working independently. 

Despite huge gains in in the technology’s capabilities, AI still needs people for interpretation and making ethical choices, according to the study. And it warns that over-reliance on AI erodes irreplaceable human judgment. 

Instead of assuming AI can replace human expertise, organizations should focus on building “knowledge ecosystems” (the ways groups create, store, and share information) where AI supports human learning, innovation, and decision-making, according to the study. 

The goal shouldn’t be to ban AI or replace employees outright, but to use AI to cultivate a powerful knowledge ecosystem that captures knowledge, facilitates its movement, and creates new understanding. (Think Slack channels, wikis, tribal knowledge, onboarding docs, expert networks, and AI layers on top.)

While replacing employees with AI captures cost savings, it surrenders the collective-intelligence opportunity. 

On the cultivation of human talent

Initially, many organizations responded to the emergence of powerful AI chatbots and tools with a simplistic “we need more of this.” Now, it’s time to confront the “skills atrophy paradox.” 

Some companies are trying to replace junior employees with AI used by senior employees. But if that’s happening at scale, where do tomorrow’s senior employees come from? 

According to a new paper titled “AI Assistance Reduces Persistence and Hurts Independent Performance,” conducted by researchers from major US and UK universities, reliance on AI chatbots erodes human capability. 

The study tested the effects of AI assistants such as ChatGPT on tasks like math and reading comprehension with over 1,200 participants. It found that while AI improved performance, scores dropped sharply once it was removed, and users were more likely to give up on hard problems than those who didn’t use AI at all. 

These aren’t long-term effects. They appear after only about 10 to 15 minutes of using AI — about the same time it takes to drink a cup of coffee. 

The researchers don’t recommend banning AI, but argue it should be used to help people grow and learn. 

The takeaway from both studies: organizations benefit greatly by keeping people in authorship of decisions and avoid demoting them to rubber-stamping AI’s output. 

Another error is to focus too much on the narrow idea of “productivity” or output. Companies that keep people in charge will be more legally defensible, more trusted by customers, and better at catching the high-cost mistakes AI makes confidently, according to the Royal Docks study. 

How to build a strong ‘knowledge ecosystem’

The building blocks of a human-AI knowledge ecosystem are, according to the Royal Docks study: 

• Workflow redesign: map tasks by who (or what) is best suited — then design handoffs, not replacements
• New roles: hire or cultivate AI specialists
• Training shift: from domain skills alone to metacognition — knowing when and how to combine individual personal knowledge with AI input
• Documentation matters more, not less: Focus on high-quality, thorough documentation of everything knowing that AI can handle the complexity of it all
• Ethical guardrails baked in: use people to keep AI aligned with human- and business-centered goals

The new AI strategy

The uncomfortable truth in the Royal Docks findings isn’t that AI is less powerful than we thought. It’s that its power is wasted on the strategy most organizations have chosen for it. 

Replacement is a one-time cost saving. But using AI as part of a real knowledge ecosystem where AI makes humans smarter and humans keep AI honest delivered compounding advantages. 

To focus on the cost savings of cut salaries is to fall for the quantitative fallacy, which is to favor the measurable and believe the unmeasurable isn’t important or doesn’t exist. 

This will all play out over time. The companies replacing too many employees in the hopes AI will do their jobs will find themselves at a competitive disadvantage against those who invest in building those powerful knowledge ecosystems and a culture of partnership between people and AI. 

AI disclosure: I don’t use AI for writing. The words you see here are mine. I do use a variety of AI tools via Kagi Assistant (disclosure: my son works at Kagi) — backed up by both Kagi Search, Google Search, as well as phone calls to research and fact-check. I use a word processing application called Lex, which has AI tools, and after writing use Lex’s grammar checking tools to find typos and errors and suggest word changes. Here’s why I disclose my AI use and encourage you to do the same.