AI promises productivity, but for managers, it’s mostly a headache for now

The Productivity Paradox

We’ve been sold a dream where AI does the heavy lifting while we sit back and oversee the results. The promise was simple: give everyone a GPT-powered co-pilot, and the output will skyrocket while management time shrinks. But according to new survey data, that’s not what’s happening on the ground. For over half of the managers out there, AI isn’t a shortcut; it’s a source of massive friction.

As someone who builds in this space, I see this as the classic "first-inning" problem. We are introducing powerful tools without updating the ways we measure human effort. When the work looks the same whether it took ten minutes or ten hours, the old management playbook breaks. Managers are now spending more time questioning the authenticity and quality of work than they are actually leading teams.

The Measurement Crisis

The core issue highlighted in the recent TechCrunch report is evaluation. More than 50% of managers admit they are struggling to judge employee performance in an AI-integrated environment. This is a massive red flag for any founder or builder. If the people running the show can't tell the difference between high-value human insight and a mediocre AI summary, the entire corporate structure begins to rot.

We are entering an era of "synthetic mediocrity." Employees are using tools to produce more volume, but that volume is often just noise. For a manager, this creates an impossible workload. Instead of reviewing five high-quality reports, they are reviewing fifty AI-augmented documents that all sound eerily similar. The signal-to-noise ratio is tanking.

Why Founders Should Care

If you’re building AI tools, you have to stop focusing solely on the generation phase. We have enough tools that make stuff. What we don't have are tools that help managers validate, audit, and contextualize that stuff. If your product increases output by 10x but increases the management overhead by 20x, you haven't built a solution; you’ve built a liability.

Founders need to realize that the end-user isn't just the person typing the prompt. The end-user is the person paying the bill and the person responsible for the output. If the manager feels like their job has become a game of "detect the hallucination," they will eventually push back against the adoption of these tools altogether.

The Incentives Are Broken

The reason we are seeing this headache is that corporate incentives haven't caught up to the technology. Most employees are still measured by throughput. In a pre-AI world, throughput was a decent proxy for effort. In a post-AI world, throughput is just a proxy for how well you can copy-paste.

Managers are stuck in the middle. They are being told to embrace AI to stay competitive, but they are still being held accountable for the accuracy and originality of their team's work. When a junior analyst turns in a brilliant-looking deck in record time, the manager has to decide: did this person suddenly become a genius, or did they just get lucky with a prompt? That uncertainty creates anxiety, not productivity.

• Increased Audit Time: Managers are spending hours fact-checking AI output that used to be verified by the employee during the drafting process.
• Loss of Mentorship: Junior staff are bypassing the struggle of learning a craft, leaving managers with a team that lacks foundational skills.
• Performance Inflation: Everyone looks like a top performer on paper, making it impossible to identify who deserves a promotion or a raise.

A Message to Builders

Stop pitching "productivity" as a raw number of words or lines of code produced. That metric is dead. Start pitching "transparency" and "provenance." Builders who win in the next two years will be the ones who create ways to show how the work was done, not just that it was done.

We need tools that track the iterative process between a human and the AI. If I can see that an employee spent three hours refining a prompt and editing the output, I know they are engaging with the material. If I see a one-click generation, I know they are coasting. As a founder, I want to reward the former and coach the latter. Current AI implementations make it nearly impossible to distinguish between the two.

The Skeptic's View

I’m naturally skeptical of any technology that claims to be a "magic button." AI is a tool, not a replacement for judgment. The current headache for managers is a symptom of us trying to use a scalpel like a sledgehammer. We are forcing AI into workflows where the human element—the actual thinking—is the most valuable part.

The most dangerous thing in a company isn't a slow worker; it's a fast worker who is wrong. AI enables everyone to be fast and wrong simultaneously.

Until we solve the evaluation problem, AI will remain a net-negative for management sanity. We are essentially asking managers to become full-time forensic investigators. That’s not a sustainable way to run a business, and it’s certainly not the future of work we were promised.

The Takeaway

The headache isn't going away until the tools change. If you are a builder, focus on the "Manager Experience" (MX) just as much as the User Experience (UX). If you can't prove to a manager that your tool makes their team better—rather than just faster—you’re going to lose the enterprise market.

For founders and managers, the lesson is clear: slow down. Before you roll out AI across your entire org, figure out how you’re going to measure success. If you can't define what "good" looks like in an AI-driven workflow, don't be surprised when you end up with a mountain of average work and a burnt-out management team.

Read the original at TechCrunch AI →