Lindsey Wilkinson
5 min read
In This Article:
This story was originally published on CIO Dive. To receive daily news and insights, subscribe to our free daily CIO Dive newsletter.
Enterprises are honing their approach to identifying the right AI use cases — and demonstrating the accompanying business value.
For Kraft Heinz, the success of an initiative is measured by a mix of quantitative and qualitative assessments, according to Pat Nestor, head of decision intelligence products and platforms at the food and beverage giant.
“On the quantitative side, that’s where the business case assessment comes in,” Nestor told CIO Dive. Teams need to be able to tie use cases to broader business goals, like boosting sales or reducing costs.
The quantitative assessment is paired with qualitative value, such as impacts on its net promoter score and adoption levels.
“We measure and track NPS, adoption and engagement scores to provide a healthy feedback loop for us to then refine and evolve,” Nestor said. “That qualitative-quantitative balance is something that we really focus on here.”
With more C-suite, investor and board-level focus on AI and bigger budgets supporting the efforts, technology leaders are under pressure to get the formula right, from picking a scalable, beneficial use case to tracking its success post-deployment.
AI project failure rates are up this year as enterprises grapple with a battery of deterrents. Nearly all — 97% — of businesses have struggled to demonstrate generative AI’s business value, according to an Informatica report published in February.
Successful enterprises often credit use case alignment with broader strategic goals to support project prioritization and taking into consideration available resources and expected timelines.
“One of the most important things for us, from my vantage point, is that we do not view AI, or particularly generative AI, as a solution in and of itself, but rather as a critical ingredient that can allow us to supercharge a larger program,” Nestor said.
Before Kraft Heinz chooses where to make a big AI bet, there’s an upfront effort to pressure test use cases. This is also the stage where success criteria are established and mock-ups are created.
Nestor said teams try to initially answer the following questions:
-
Where does the company want the use case to go?
-
How could it potentially evolve?
-
How will it be measured?
-
How can we evaluate progress along the way?
“That assessment activity high funnel is critically important so that we have a well-rounded idea and a well-rounded business case before we actually commit material resources,” Nestor said.
