Photo via Fast Company
For years, executives have poured resources into artificial intelligence initiatives, yet frustration persists—not among skeptics, but among true believers whose programs haven't moved the needle on the bottom line. According to Todd James, founder and CEO of Aurora Insights and former AI leader at Kroger and its data science subsidiary 84.51°, the disconnect between ambitious AI activity and measurable business results has become untenable. Charlotte's business leaders managing tighter margins and more demanding boards are increasingly feeling this tension.
The core issue isn't whether AI matters—it's that most organizations cannot articulate what their AI investments are actually worth. Companies can recite the number of models in production but struggle to connect those systems to revenue growth, cost reduction, or improved unit economics. James argues that the relevant question isn't where a company deploys AI, but where AI fundamentally changes how the business makes money. At Kroger, success was measured in margin, basket size, and customer retention—not technological achievement. Charlotte retailers, manufacturers, and financial services firms should apply the same discipline to their AI spending.
Beyond financial accountability, James identifies two additional leadership imperatives: organizational velocity and informed decision-making. Many large organizations sit on valuable data insights but move too slowly to act on them. In one financial services example, a team built a model to identify high-probability customer switches, but bureaucratic delays meant the market window closed before leadership could decide. The technology worked; the moment didn't. AI's real strategic advantage lies in accelerating the distance between signal and response—compressing decision cycles so companies can capitalize on opportunities when they matter most.
Ultimately, closing the AI execution gap requires CEO ownership of AI as a business priority, not a technology mandate. That means setting specific expectations for economic impact, measuring outcomes instead of effort, and having the discipline to discontinue initiatives that generate activity without generating value. For Charlotte's competitive business landscape, the companies that master this mindset—linking AI work directly to financial results—will establish a new standard others will struggle to match.
