Prioritizing GenAI Use Cases Is The Path To Success: Dell Exec

Solution providers are playing a leading role in the effort to ‘make AI real’ for customers, according to Dell Technologies’ Justin Carver.

When it comes to implementing generative AI, solution providers are playing a leading role in the effort to make it “real” for customers, according to Dell Technologies’ Justin Carver.

But with such a vast array of potential uses for GenAI, the key for solution providers will be to focus on helping customers to aggressively prioritize, Carver said Monday during a session at the XChange August 2024 conference, which is hosted by CRN parent The Channel Company and being held this week in San Antonio.

[Related: MSPs Are Driving GenAI Adoption But Security, Data Hurdles Persist For Customers: Panel]

The reality is there are “a ton of use cases out there. Most organizations have 200-plus use cases,” said Carver, an advisory systems engineer at Dell Technologies. “The most success is going to be found in prioritizing these use cases.”

The ultimate goal when it comes to use cases, he said, should be to help customers with “utilizing the ones that are most relevant to their business.”

Without a doubt, prioritization around GenAI use cases is imperative—both from the customer and solution provider perspectives, said Travis Adair, principal partner and vice president at InfiniTech Consulting, a Dell partner based in Columbia, Mo.

For starters, trying to explain broad use cases to customers is not going to get you very far, Adair noted.

“You can’t send a prospect a laundry list of use cases and say, ‘Hey, what can I help you with?’” he said. “You need to try to target the market on one or two specific use cases.”

This is equally crucial from the vantage point of the solution provider, according to Adair.

“You really have to pinpoint what your expertise is going to be in the market, and what use case you’re going to focus on,” he said. “You can’t focus on all of them—you’ve got to find your specialty.”

Regardless of the specific use case, however, there are some components of implementing GenAI that are generally important for solution providers to look at, Carver said. Assisting customers with the feasibility criteria and data readiness, for instance, are two key areas no matter what the use case is for GenAI, he said.

Critical questions to answer, he said, can include: “’Do we have the right data? Is it labeled correctly? What solutions do I actually need in place to make sure that the data is labeled correctly, so that the AI tool can actually be utilized in my environment?’”

The bottom line for solution providers is that “services [are] honestly the most important aspect of any AI and generative AI discussion for customers,” Carver said. “We are nothing without the ability to go in together [with a] collaborative approach and carry a conversation—and make AI real for our customers.”