Cut Twice, Pay More.
Why chasing short-term AI efficiency erodes the human intelligence your business runs on.
Founder’s Note: In the last issue, I wrote about the danger of mistaking a convincing representation of people for a real understanding of them. That question has stayed with me because the same thing happens inside organisations. We make decisions about people through roles, org structures and workforce projections, while overlooking what they actually contribute. This issue looks at what organizational reinvention really requires, beyond deciding what can be automated, restructured, or removed.
The Memo.
Executive boardrooms are under pressure to get leaner and faster with AI. Yet, almost none are asking:
“Are we solving real operational problems, or just performing our idea of what the future looks like?”
When leaders rely on org charts, workflows, and headcount models to make those decisions without a full understanding of their people, they optimize the skeleton of the business while starving the human intelligence that keeps it alive.
Consider Microsoft’s voluntary exit program. Framing restructuring as an employee “choice” looks clean on a workforce model, yet it sidesteps the deeper question of what true employee agency looks like, and whether leadership actually understands the institutional capability walking out the door. This is a diagnosis problem, disguised as a talent problem.
The decisions leaders make are shaped by how they diagnose problems, what they choose to prioritize and whose strategic insights they recognize in the process.
When technology and cost efficiency become the starting point rather than solutions to clearly identified problems, leaders risk overlooking the human capabilities their operations depend on. And when those capabilities are lost, the consequences can extend far beyond the initial workforce decision.
The Unfiltered Take.
The problem isn't AI adoption or leaner teams. It's the flawed logic driving both.
Firstly, are leaders solving the right problem? Technology adoption can become a response to pressure to be perceived as “tech forward”, rather than a deliberate answer to an organizational need. A Harvard Business School field experiment, involving 758 knowledge workers, illustrates why this distinction is important. Across 18 tasks within AI’s capabilities, participants using GPT-4 completed 12.2% more tasks and worked 25.1% faster. But on a complex managerial task outside those capabilities, AI users were 19% less likely to produce correct solutions than those without AI. The same technology could improve performance in one context, and undermine it in another.
This is the challenge with adopting technology before understanding the work – the solution may be effective, but not for the problem being addressed.
Recent customer-service industry research found that only 4% of customer-service organizations had achieved the ROI they expected from their AI initiatives. The question is not simply how much organizations are investing, but whether those investments are actually addressing the appropriate problems.
Secondly, what are leaders prioritizing? When efficiency is measured primarily through cost reduction and headcount, human contribution starts to be treated as an expense rather than an organizational capability.
That shift is already reflected in workforce decisions where 21% of service and support leaders say their organizations have reduced human-agent headcount because of AI. Yet 7% report rehiring after previous reductions, while another 11% plan to rehire within the next 18 months. And the rehiring consequences are already emerging. 51% of employed adults surveyed by SHL across the US and UK said they would require a substantial pay increase if asked to return after being replaced.
Meanwhile, Gartner predicts that 30% of workers terminated or replaced by AI will be rehired by 2029, predictably at a higher cost.
These findings signal the growing risk of leaders reducing human capacity based on anticipated technology value, rather than demonstrated operational results. Leaders are hollowing out long-term capability to hit short-term efficiency gains.
Third, whose intelligence informs leadership decisions? Employees carry intrinsic value and institutional knowledge, far beyond the skills listed in their job descriptions. They understand customers, informal processes, cultural dynamics, operational gaps and the dynamic relationships that are essential to collaboration, productivity, and fiscal success. Yet leaders often make decisions about their roles without meaningfully involving the people closest to the work. This is where cultural intelligence becomes strategic infrastructure.
Listening to employees isn't about simply making people “feel heard” in the next Glint survey. It's an opportunity to access the institutional intelligence and esoteric knowledge that performance reports, workforce projections, and technology assessments cannot capture.
More importantly, leaders must then be prepared to act on what they learn.
The Action.
Before approving the next major restructuring, workforce, or AI investment decision, work through three questions:
Diagnose before deciding: What specific problem are we trying to solve? And what evidence tells us this is the actual problem rather than a symptom?
Account for human contribution: What human knowledge, judgement, relationships and cultural understanding currently make this work possible? What might we lose if we redesign or remove these roles?
Involve the people closest to the work: Have we sought input from the employees who directly understand these processes? What have they identified that leadership may have overlooked, and what are we prepared to change as a result?
How leaders diagnose problems determines what they prioritize, and what they prioritize determines whose knowledge, capabilities, and contributions they value. When those underlying assumptions are wrong, even well-executed strategies can undermine organizational trust, erode collective capability, and sacrifice critical contextual knowledge in pursuit of technology and cost efficiency.
The future of an organization should be designed around what it needs to achieve, what people make possible, and how technology strengthens both.
Forward this to the leader signing off on organizational restructuring. The Clarity Memo: Unfiltered drops bi-weekly. Subscribe to get it directly to your inbox.
This content is for informational purposes only and does not constitute professional, legal, financial, or organizational advice. For guidance specific to your organization, contact Fadéké Strategic Consulting, LLC at admin@fadeke.com