Contrary to the popular belief that AI's main purpose is to replace humans for less money, user data shows its primary benefit is enabling entirely new functions. As AI costs rise, the focus will shift from simple cost-cutting to strategic investments in capabilities that were previously impossible.

AI doesn't replace analysts in revenue planning; it changes their focus. By automating tedious formula creation and data pulls, it allows them to concentrate on higher-value activities like running sophisticated scenarios, incorporating new business context, and exploring deeper data insights.

Businesses are unlikely to use powerful AI simply to shave a few percentage points off their software spend. The real, high-impact ROI comes from applying AI to improve core business operations, making the actual business more effective and efficient.

While public attention focuses on glamorous AI applications like image generation, the most transformative and valuable contributions of AI are happening in less visible areas. Optimizing logistics, streamlining back-office operations, and improving industrial processes are where AI is quietly delivering significant ROI.

AI excels at generating code, making that task a commodity. The new high-value work for engineers is "verification”—ensuring the AI's output is not just bug-free, but also valuable to customers, aligned with business goals, and strategically sound.

While AI for designing novel molecules gets the hype, its practical, near-term impact is in streamlining operational tasks like summarizing medical charts, preparing SEC filings, and analyzing contracts, which are a better fit for current LLM capabilities.

The most significant value from AI is not in automating existing tasks, but in performing work that was previously too costly or complex for an organization to attempt. This creates entirely new capabilities, like analyzing every single purchase order for hidden patterns, thereby unlocking new enterprise value.

While generating products with AI is popular, a massive unlock lies in applying it to unseen internal processes. AI can optimize workflows, improve content design, and perform analysis. These non-product applications can create significant leverage for design teams within larger organizations.

The focus on AI writing code is narrow, as coding represents only 10-20% of the total software development effort. The most significant productivity gains will come from AI automating other critical, time-consuming stages like testing, security, and deployment, fundamentally reshaping the entire lifecycle.