SUMMARY
At Inc42's AI Summit 2026, kAIgentic founder & CEO Ahmed Mazhari said that enterprise AI adoption is still in its early stages, requiring founders to educate customers and build trust
CoRover.ai founder & CEO Ankush Sabharwal argued that AI startups should prioritise rapid deployment, measurable outcomes and customer ownership from the outset
The panellists also discussed the importance of owning workflows, adding that value creation emerges when AI becomes embedded into operational processes
India’s enterprise AI market is projected to grow from $11 Bn in 2025 to $71 Bn by 2030, fuelled by adoption across sectors such as BFSI, manufacturing, healthcare, education and agriculture.
Yet, despite the growing enthusiasm around AI, kAIgentic founder and CEO Ahmed Mazhari believes most enterprises remain far earlier in their adoption journeys than most founders assume.
Speaking during a panel discussion titled ‘The Playbook For Turning Enterprise Interest Into Signed AI Contracts’ at Inc42’s AI Summit 2026, Mazhari argued that one of the biggest misconceptions in enterprise AI sales is that customers already know what they need.
According to him, enterprise buyers are often still evaluating which AI solutions to adopt, how to assess competing offerings and whether pricing structures are justified. As a result, AI founders need to spend as much time educating customers as they do selling their products.
“We must always know this: people buying on the other side have no idea what to buy. People buying on the other side don’t know how these solutions should be priced. If you are not able to teach your customers what they should be looking for, that is probably a point of deep reflection,” Mazhari said.
He suggested that founders must move beyond conversations focused solely on productivity gains and instead emphasise organisational transformation. In his view, enterprise AI adoption is ultimately about redesigning workflows and delivering measurable business outcomes rather than simply automating individual tasks.
Mazhari added that while trust can help open doors, long-term success depends on proving product-market fit and demonstrating tangible value within enterprise operations.
The discussion also explored how startups can reduce friction during enterprise adoption.
Ankush Sabharwal, founder and CEO of CoRover.ai, argued that AI vendors should prioritise rapid deployment, measurable outcomes and customer ownership from the outset. Rather than forcing customers into predefined workflows, he said startups should align AI deployments with the specific business objectives enterprises are already pursuing.
“You know your domain, you know your problem, you have your own purpose. Now let me prove it with our AI,” he explained.
Meanwhile, Gnani.ai cofounder and CEO Ganesh Gopalan questioned the industry’s reliance on proofs-of-concept (POCs), arguing that many fail because they lack commercial commitment from customers. Instead, he advocated structured field trials with budgets and timelines.
“I don’t want to do a POC, but let me do a field trial,” he said.
Gopalan also predicted that enterprise AI pricing models will increasingly shift towards outcome-based structures, with customers expecting vendors to share responsibility for business results rather than simply supplying technology.
Dushyant Garg, who leads strategy and enterprise growth at Nugget by Zomato, highlighted another recurring challenge – workflow ownership. Drawing comparisons with earlier waves of enterprise software adoption, including ERP deployments, he argued that lasting value is created when AI becomes embedded within operational systems rather than functioning as a standalone capability.
“The success of a POC depends on what sort of closed-looping is being done in a workflow-level system,” Garg said, adding that executive sponsorship and workflow redesign often determine if enterprise AI projects move beyond experimentation.
The panel, moderated by Sameer Dhanrajani, CEO of 3AI and AIQRATE, concluded that enterprise AI adoption is moving beyond experimentation. However, as the market matures, founders may need to spend less time pitching technology and more time helping customers understand how to evaluate, implement and derive value from it.