The Cost of Thinking: Are We Measuring AI's True Value?

Herbert Simon, the Nobel laureate economist, once posited that a wealth of information creates a poverty of attention. In today's AI-driven world, we might ask: What is the cost of thinking, and how do we measure its value?

As businesses pour millions into AI technologies, many question whether these hefty investments will ever deliver on their promises. Traditional ROI metrics seem inadequate to capture AI's true impact, leaving executives and analysts alike grappling with how to justify the expenditure.

The challenge lies not in the technology itself but in our outdated methods of measuring its worth. We're trying to fit a square peg into a round hole, attempting to quantify the value of AI using metrics designed for an era of tangible, easily measurable outputs.

Consider the "cost of intelligence" that Sam Altman, CEO of OpenAI, spoke about. He envisioned a future where AI drives the cost of intelligence so close to zero that it transforms society. This isn't just about reducing expenses but fundamentally altering how we perceive and value intellectual work.

In academia, for instance, professors now use AI to write letters of recommendation—a task once reliant on personal judgment and time-consuming reflection. The AI doesn't just save time; it reshapes the entire evaluation and communication process.

But how do we measure the value of this shift? Traditional ROI calculations fall short. Instead, we need to develop new benchmarks that consider how AI changes the nature of work and thinking.

Organizations should consider switching from old business metrics to more cognitive metrics. Rather than focusing solely on financial returns, companies should measure improvements in decision-making speed, quality of insights generated, and the ability to process and synthesize vast amounts of information.

New productivity measurements should focus on thinking faster and better. How quickly can employees now solve complex problems? How many more scenarios can they consider in strategic planning? How innovative are their solutions?

The paradigm shift extends beyond mere task completion. It's about reskilling and upskilling the workforce to leverage AI effectively. The value lies in AI's capabilities and how humans learn to interact with and direct these powerful tools and execute strategies.

As AI takes care of mundane tasks, human cognitive capacity is freed up for higher-order thinking. The real ROI of AI investments may be found in the quality of strategic decisions, the depth of creative insights, and the ability to tackle previously insurmountable challenges.

All work has a cost, including thinking with data, information, and knowledge. AI is dramatically altering this equation. By allowing AI to handle routine cognitive tasks, we're not just saving time—we're reallocating our most precious resource: human thought. It's essential to recognize that the only thing "artificial" about this intelligence is its origin, not its capability. Decades of research pioneered by visionaries like Ilya Sutskever have led to increasingly accurate approximations of neural processes. These models, built on deep learning and neural network architectures, are not just mimicking human cognition—they provide a functional analog. The humbling reality is that these models will only get better, more efficient, and more capable over time. As they do, the line between artificial and human intelligence in terms of cognitive task performance will continue to blur, pushing us to reconsider the unique value of human cognition in an AI-augmented world.

The effectiveness of our cognitive resources becomes the accurate measure of AI's impact. How much more effectively can we deploy our attention, creativity, and strategic thinking when AI handles the heavy lifting of data processing and routine analysis?

In this new landscape, the return on AI investment isn't just about dollars saved or revenue generated. It's about the quality of thinking enabled, the breadth of possibilities explored, and the depth of insights uncovered.

Organizations must develop new frameworks for assessing AI's value as we move forward. These frameworks should consider quantitative outputs and qualitative improvements in decision-making processes, innovation capacity, and strategic foresight.

The actual cost of thinking in the AI age may be the opportunity cost of not thinking big enough. As AI drives the cost of routine intelligence towards zero, the premium on uniquely human cognition—our ability to imagine, create, and strategize—will only increase.

In the end, the most successful organizations will not be those that simply implement AI but those that use AI to fundamentally enhance their cognitive capabilities. The ROI of AI isn't just about efficiency gains—it's about expanding the boundaries of what's possible through augmented intelligence.

As we navigate this new terrain, let's not be constrained by old metrics. Instead, let's rise to the challenge of measuring what truly matters in the age of AI: the enhanced power of human thought.