The most successful organizations will view AI not as a tool for cost-cutting (doing the same with less) but as an expansionary technology. This mindset focuses on using AI to create new products, enter new markets, and dramatically increase scope, rather than just incremental efficiency gains.

Focusing on AI for cost savings yields incremental gains. The transformative value comes from rethinking entire workflows to drive top-line growth. This is achieved by either delivering a service much faster or by expanding a high-touch service to a vastly larger audience ("do more").

Most companies use AI for optimization—making existing processes faster and cheaper. The greater opportunity is innovation: using AI to create entirely new forms of value. This "10x thinking" is critical for growth, especially as pure efficiency gains will ultimately lead to a reduced need for human workers.

Focusing AI efforts on efficiency and cost reduction offers limited, short-term benefits. The truly transformative approach is to invest in AI to create new revenue streams, enhance product offerings, and grow the business exponentially.

Contrary to expectations, even cutting-edge companies are not yet using AI to automate internal operations. Their best talent and resources are focused on the larger prize of building new AI-driven products, leaving internal efficiency as a latent, uncaptured opportunity for now.

As AI dramatically lowers the cost of building software, competitive advantage shifts. Value now accrues to leaders who can best identify real user problems (product) and effectively scale distribution in a crowded market (go-to-market), rather than just the ability to build.

While AI-driven efficiency is an obvious first step, it often results in workforce reduction if company growth is flat. True differentiation and sustainable advantage come from using AI for innovation—creating new products, markets, and business models to fuel growth.

While tracking ROI is important, a heavy-handed focus can create a bias toward 'efficiency AI'—using AI for existing work. This overlooks 'opportunity AI,' which unlocks entirely new products and capabilities. The former is a foundation, but the latter should be the ultimate strategic goal for true growth.

A key litmus test for a company's ambition is how it deploys AI investment. The best founders prioritize using AI to build new revenue-generating products over simply optimizing internal costs, as the upside for revenue growth is unbounded.