Making Sure AI Solves the Problem

September 5, 2024

Written by Eric Krapf, General Manager and Program Co-Chair, Enterprise Connect Publisher

AI may be moving quickly as a technology, leaving enterprise leaders feeling pressured to do something now. But the wisest strategy may be to approach AI like you’re in it for the long haul.

That was one of the key messages from an Enterprise Connect virtual event last week. Derek Top, senior analyst at Opus Research, said in a keynote that while it’s important to keep up with the state of play in AI, it’s a “fool’s errand” to try and adjust to every announcement that comes out about a new Large Language Model or other apparent AI breakthrough.

It’s still early days for AI, Top reminded the audience: “The technology is ahead of where most people are at.”

That assessment was echoed in a recent study from the think tank Rand. Citing reports that more than 80% of AI projects fail, Rand recommends that industry leaders proceed cautiously with their AI projects—not just out of the usual governance concerns, but also to improve the prospects for success: “AI projects require time and patience to complete,” according to the research institute. “Before they begin any AI project, leaders should be prepared to commit each product team to solving a specific problem for at least a year.”

Rand goes on to note that, “Misunderstandings and miscommunications about the intent and purpose of the project are the most common reasons for AI project failure.”

In late 2022, few people seemed to think they had lots of time to work with. And indeed, it would have been unwise to react to ChatGPT by donning blinders and resolving to get around to Generative AI when your laundry list of other projects was finished.

AI may have changed the playing field. But it hasn’t changed the rules, at least not all of them. The rules say that risk still matters, and also that organizations move at a certain pace. If AI is meant to solve problems, not just be a shiny object, the enterprise needs to know the scope and nature of the problem, as well as all of its stakeholders and dependencies.

At Enterprise Connect AI next month in Santa Clara, CA, we’ll address both elements of the AI conundrum: The urgency that enterprises naturally feel when a fast-moving, transformative technology bursts onto the scene; and the realization that AI doesn’t negate everything you thought you knew about IT projects.

That’s why I’m particularly excited about our two enterprise keynotes, featuring David Glick of Walmart and Darrius Jones of USAA. Both speakers represent companies that have moved decisively on Generative AI, to ensure they don’t sacrifice competitive advantage. They’ll share with our audience the steps they’ve taken to capture near-term success while working within the enterprise environment. I hope you can join us!