As agentic capabilities evolve, I’m increasingly seeing this same concept also being applied to AI agents that reinvent the customer experience. Look at the mortgage industry for an example. These lenders report a high drop-off rate in online mortgage applications. The reality is that mortgage applications can be quite complicated. The average applicant is often overwhelmed by financial jargon or documents they may not have readily available. If the user gets confused and steps away, odds are they won’t come back. Now, imagine replacing that with an AI agent that interacts with the core service. It can answer questions, translate complex financial terms into plain terms in real-time, save the session if needed and securely reach out for bank documents. Just a 1-2% increase in completed applications from this represents a material impact on the bottom line. That’s high-impact for the business.
Don’t swing for the fences, just get on base
As you’re allocating your budget for AI in 2026, here’s my advice: stop chasing moonshots. These vaguely scoped, overgeneralized agent dreams are often expensive, they rarely ship and they burn resources faster than they can create value. Instead, look for opportunities to hit singles and doubles. Keep your eye out for specific, high-value and outcome-driven projects that can deliver wins in months, not years. I’ll walk you through the coaching that I use with enterprise leaders planning AI projects.
Start with this question: What are 10 processes that are repetitive, well-documented and still being manually performed by humans? Score each one on a 1-10 scale across these three dimensions: the impact if you automated it, the risk if the project fails (where 10 is catastrophic) and the complexity to build and deploy it. The winning formula is high impact, low risk and low complexity. That’s your AI sweet spot. Aim your swings there.
