AI’s Promise Lies in Smarter Thinking, Not Job Cuts
As a veteran entrepreneur behind ventures like Freshly and Petfolk, I’ve seen firsthand how transformative technologies demand more than incremental tweaks—they require a rethinking of how businesses operate. Artificial intelligence (AI), contrary to current criticisms, is not failing us. Rather, it’s leadership that is failing to understand and harness its full potential.
Across industries, CEOs and executives are expressing disappointment in the return on investment from AI. According to a PwC Global CEO Survey, over half of companies report that AI has not delivered cost savings or revenue growth. Only a small fraction—about 12%—have seen gains on both fronts. But this perceived failure stems not from the technology, but from how it is being measured and implemented.
Understanding AI as a New Economic Input
The dominant approach to AI has focused on efficiency—cutting labor costs, automating workflows, and seeking quick returns within existing structures. This narrow lens misses the point. AI is not just a better tool; it’s a transformative input that dramatically lowers the cost of high-quality cognitive work.
I refer to this shift as Synthetic Human Intelligence Hours (SHIH)—a term that encapsulates the analytical and intellectual capacity AI can deliver at near-zero marginal cost. These are not artificial people; they’re scalable, synthetic thought processes capable of supporting real human decision-making.
Much like how the Industrial Revolution reduced mechanical labor costs and cloud computing slashed data processing expenses, AI slashes the cost of thinking. This redefines what’s economically feasible in terms of analysis, decision-making, and innovation.
Why Traditional Metrics Fall Short
Companies are trying to squeeze SHIH into systems designed for limited human bandwidth, and the results are unsurprisingly disappointing. A study by MIT highlighted this disconnect, showing that only 5% of integrated AI pilots produced measurable value, while 95% did not. These failures stem not from bad models, but from poor integration, generic tooling, and treating AI as a siloed experiment instead of an embedded capability.
Leaders are applying outdated ROI metrics to a fundamentally new capacity-expanding input. That’s like judging a new engine solely by its fuel efficiency, ignoring the miles it can add to the journey. AI’s benefits accrue over time through better decisions made more frequently—not via immediate cost cuts.
Putting SHIH to Work at Petfolk
At Petfolk, we’re building a network of veterinary clinics empowered by AI. Our regional managers oversee dozens of performance metrics—everything from labor and inventory to training, compliance, and customer satisfaction. Traditionally, these managers spend 40-50 hours a week analyzing data and making choices, often sacrificing depth for breadth due to time constraints.
Our vision is to multiply their analytical capacity without increasing their workload. By deploying AI agents capable of generating SHIH, we aim to create the equivalent of a 500-hour analytical workweek. These agents will process every invoice, customer review, and performance metric, generate training plans, and synthesize insights. The human manager will still lead, prioritize, and communicate—but now backed by a virtual team of tireless analysts.
This kind of scalable intelligence was previously out of reach due to cost. With AI, it’s not only possible—it’s practical. It’s not about replacing people; it’s about supercharging their capabilities.
The Compounding Advantage of Intelligence
One reason AI disappoints early on is that its impact is subtle. It doesn’t immediately slash costs or spike revenues. Instead, decisions become slightly better, errors are caught earlier, and inefficiencies are gradually reduced. These small advantages compound over time, becoming game-changing in the long run.
Organizations that judge AI solely by short-term ROI will miss these benefits. Those that recognize SHIH as a compounding advantage will redesign around this new capacity, positioning themselves for sustained success rather than quick wins.
PwC also notes that CEO confidence in revenue growth is at a five-year low, partly due to weak AI returns. But again, the issue isn’t AI’s power—it’s the lack of organizational redesign to utilize it effectively. AI’s benefits don’t show up in a single line item; they manifest in thousands of better decisions made across the business.
Shifting the Strategic Question
As the cost of thinking continues to fall, the question for leaders is no longer, “Where can we cut costs?” but “What problems can we finally afford to solve?” AI is not about replacing jobs; it’s about unlocking potential. The real competitive divide will be between companies stuck in efficiency mode and those that embrace AI’s capacity for scalable cognition.
Small, focused teams, when augmented by SHIH, can achieve what once required armies of analysts. It’s a new era—not of fewer jobs, but of cheaper, smarter thinking. The organizations that adapt to this reality will lead the next wave of innovation.
This article is inspired by content from Original Source. It has been rephrased for originality. Images are credited to the original source.