Ethan Mollick argues that AI agents have crossed a critical threshold: they are now capable of performing economically relevant work. He first draws on a recent OpenAI study comparing AI models to human experts (14 years of average experience in finance, law, retail) on realistic tasks designed to take 4 to 7 hours, evaluated blind by a third group of experts. Result: humans still win, but narrowly, with margins that vary by sector. The most recent models are progressing rapidly, and AI's main weakness — output formatting and instruction-following — is improving fast. Mollick predicts that the next generation of models will surpass human experts on average. He qualifies this, however: AI replaces tasks, not entire jobs, and its capabilities remain "jagged," excellent on some tasks and deficient on others.
To illustrate the value of this real work, Mollick recounts his own experience: he asked Claude Sonnet 4.5 to replicate a sophisticated economics paper involving multiple experiments, providing the full text and the replication data archive. Autonomously, the model read the paper, sorted the files, converted the STATA code to Python, and methodically verified all the findings, including complex interactions. Mollick spot-checked the results and had the replication re-replicated by GPT-5 Pro. What would take experienced researchers hours is accomplished in minutes — a major avenue for addressing the scientific replication crisis, by enabling large-scale verification that was previously impossible.
This leap in capability stems from improved model accuracy: even small gains substantially reduce failures across long chains of tasks, and recent "thinking" models incorporate self-correction. The METR study shows that the length of tasks AI can accomplish autonomously has grown exponentially since GPT-3.
Mollick nonetheless notes that agents lack agency in the human sense: they do not decide their own objectives, and humans must define goals and boundaries. He identifies three productive uses: automating routine tasks (reports, presentations), augmenting human capabilities (research replication), and creating new opportunities. The symmetrical risk is the "infinite overproduction of PowerPoints": unimaginative organizations using agents to generate ever more low-value content. The future of work will depend on our ability to conceive of uses that complement human capabilities rather than mechanically replacing them.