RISING TIDES
Observations from the IMC Research Process

The AI Payoff is Arriving

The next phase of AI is less about what companies spend, and more about what they get back.

This earnings season, companies across industries have highlighted AI as a contributor to productivity, revenue, or both.  AI is no longer confined to technology budgets or long-dated transformation plans. It is beginning to show up in operating costs, employee productivity, customer engagement, product development—and ultimately, earnings.

A few examples of how AI is beginning to translate into financial outcomes across industries – including travel, insurance, food distribution, consumer finance, drug development, and networking.

• Lower costs and greater productivity. Airbnb’s (ABNB) AI assistant now resolves roughly 45% of customer issues without a live agent, helping drive a 16% year-over-year decline in support cost per booking. Recruit Holdings’ Indeed is using automation to evolve from a search engine into a higher-value matching and hiring-automation platform. Chime (CHYM) is similarly using AI to help smaller teams ship products faster, creating the potential to scale revenue without a corresponding increase in headcount.
• Better decisions at scale. Zeta Global (ZETA) is using AI to improve marketing outcomes, with comprehensive AI adopters growing 4x faster than non-adopters and posting net revenue retention 400 basis points above the company average. MetLife (MET) is applying AI across claims, customer service, and employee productivity, areas where small improvements can compound across millions of interactions.
• New demand and new revenue pools. Charles River Laboratories (CRL) expects AI-enabled drug discovery to create more compounds requiring testing and validation, while also using AI to shorten pathology timelines internally. Arista Networks (ANET) captures another second-order benefit: more models, agents, and machine-to-machine activity mean more network traffic, increasing the need for the high-performance networking infrastructure it sells.

The common thread is not AI spending. It is financial output. AI can lower the cost to serve, increase employee productivity, improve retention, expand wallet share, accelerate product development, and create entirely new sources of demand. As adoption broadens, the investment question is shifting from who is spending on AI? to who can turn AI into sustainable revenue growth, margin expansion, and earnings power?