The most important question isn’t where to deploy AI. It’s what outcome matters most to your business, and whether AI can help move it.
That means grounding every AI effort in a clear priority. It could be increasing revenue per salesperson, improving customer retention, accelerating product development, or reducing risk. In some cases, cost matters. In many, it’s not the primary driver.
Organizations that focus too much on the tools often end up with pockets of activity but little business impact. Some leaders describe this as “pilot purgatory.” In contrast, companies that make real progress start from a different place. They define the outcome first, then work backward to where AI can make a meaningful difference.
We’re seeing this across industries. Some teams are using AI to shift from reactive audits to proactively identifying risk. Others are focused on catching system vulnerabilities earlier, before they escalate. Even in areas like sales, teams are rethinking how they prepare for customer conversations, while engineering groups are designing products that anticipate customer needs rather than respond to them. We are starting to call this AI’s “capability add,” an ability to create new strategic value from work processes, in addition to optimizing the efficiency, speed, and quality associated with the original process outcomes.