‘You can apply AI to everything and anything, but it’s about whether you’re actually getting a good return,’ says Nitin Jain, vice president of corporate strategy at Conduent. ‘Sometimes you’re looking for something that’s very manual in nature. Sometimes it’s something with very high volume. You take those business problems and then you come up with a plan.’
As small and medium-sized businesses grapple with AI use, and where to start, executives at one solution provider said the next phase of AI adoption won’t be about chasing shiny tools, but about picking the right problems to solve.
“You can apply AI to everything and anything, but it’s about whether you’re actually getting a good return,” said Nitin Jain, vice president of corporate strategy at Florham Park, N.J.-based solution provider Conduent, which is on CRN’s 2025 Solution Provider 500 list. “Sometimes you’re looking for something that’s very manual in nature. Sometimes it’s something with very high volume. You take those business problems and then you come up with a plan.”
He said the strongest AI use cases revolve around heavy or manual workloads that are bogged down by information that humans have to read, interpret and re-enter. And AI plans often start small rather than a full rollout, Jain said.
“Maybe we run a small pilot and see, can we apply the technology to solve an area?” he told CRN. “If that works, what does the next stage look like? How do we take it to a real production solution?”
For SMBs, that tiered approach is critical as AI doesn’t operate in isolation. Expecting it to work “in a vacuum” is also a common mistake, according to the executive.
“You’re going to connect it to all the existing systems, all the different systems that you have,” he said. “So it’s about sitting with clients, understanding their technology environment and understanding what’s already there.”
But once the technology is in place, the work isn’t over. The third stage is where businesses revisit what worked and what didn’t, then adjust where need be. This step is typically overlooked but is essential to pinpointing the AI tool’s value, according to Jain.
“Sometimes, if things don’t work out, you just exit,” he said. “That’s part of being realistic.”
As for where AI is headed next, both Jain and Tony Marino, Conduent’s chief administrative officer, predict environments where machines can handle information that’s “messy, inconsistent or unstructured.”
“There’s a common thread. Unstructured information like documents, call transcripts…things like that. Wherever you have that, that’s where the true power of generative AI shines,” Jain said.
Marino said manufacturing remains a strong candidate for AI because of its highly repeatable processes. However, he sees it differently for SMBs, particularly those run by a single owner, where adoption is being driven more by consumer-facing AI tools used for sales, marketing and other roles. In these cases, AI is used not as an automation system but as a creative assistant.
“They might be leading the charge,” he said.
