Business outcomes, not AI models, will decide enterprise deals: Gnani.ai CEO Ganesh Gopalan

Enterprises are moving past experiments and increasingly judging artificial intelligence (AI) deployments on whether they improve revenue, collections or productivity, according to Ganesh Gopalan, cofounder and chief executive of Gnani.ai.

“The only proof here is did the customers’ outcomes improve or not?” Gopalan told The Economic Times in an interview. “You can talk price, you can talk various other things, but sooner or later you get caught out,” he added.

The Bengaluru-based startup is pitching its systems against the technology that companies already use rather than against other AI vendors, Gopalan said. In banking, for instance, customers often run a new AI system alongside an incumbent platform and gradually shift volumes based on their performance, he added.


“Did you collect more money? Did you disburse more loans using the new system versus the old?" Gopalan said. "The smarter companies are not taking their decisions purely on cost. It is the business outcomes which are far more important,” he added.

Existing systems are the real rival

Gopalan said the biggest challenge to enterprise AI adoption was not other AI companies, but the systems businesses already use.

“The real competitor is existing systems,” he said. “If you look at it from the perspective of AI adoption in enterprises, it is less than 1% today. The 99% is the existing systems.”

Gopalan claims that Gnani has added 10-15 customers a month over the past eight months, driven by its focus on measurable business outcomes. In some cases, the company also links its pricing to the outcomes it delivers.

“We tell customers, ‘Let us measure business outcomes after three months and take it from there,’” he said. “We often even price on business outcomes in many cases.”

Gopalan stressed that AI makes sense when it delivers clear results. For an automaker, that means selling more cars. For a gold-loan company, it means disbursing more loans. For lenders, it could mean recovering more overdue payments, he said.

“It is all about the end outcomes rather than talking about models,” he said. “When it comes to an enterprise, some of the IT people may ask which models you use, but did their outcomes improve, and how much did they improve, is the only factor on which companies will base their decisions.”

AI moves into core business processes

The focus on outcomes is also taking AI deeper into enterprise operations, Gopalan said. Companies earlier approached AI vendors for outsourced or relatively low-risk functions but are now bringing the technology into underwriting, insurance claims, sales training and other core processes, he added.

“Companies are approaching us today on their core problems,” he said. “A year back, we never engaged with companies on some of their core use cases, like underwriting or claims. But now companies say, ‘You help us with this.’”

Also read: India’s Agent AI Revolution: How Gnani.ai Is Transforming Enterprise Automation

Banking and financial services currently lead adoption for Gnani, which works with more than 100 customers in the sector, Gopalan said.

In lending, AI agents can handle routine underwriting tasks, including optical character recognition checks, signature verification and matching documents against property rules, Gopalan said. The aim is not to replace a lender’s underwriting logic but to help its employees process more applications, he added.

Home-finance companies are also looking at AI to train field staff, reduce mis-selling, monitor sales teams and improve their performance, he said.

“At the end of the day, it might involve voice or some other mode, but the objective is to solve a problem,” Gopalan said.

Sovereignty moves to the corporate level

Gopalan said that sovereignty will increasingly extend beyond national governments and regulated sectors to individual companies seeking control over their AI systems and data.

“More and more companies are going to say that they want to own their own intelligence,” Gopalan said. “It is no longer restricted by demarcations of country or industry. It is going to be at the corporate level as well.”

Gnani also plans to announce new speech-to-speech models over the coming months and launch more sovereign models in the coming years, Gopalan said.

“You will hear some announcements in the next couple of months on some of our models,” he said. “In the subsequent years, we will be launching a bunch of other sovereign models as well.”

Earlier in March, the company raised $10 million from Aavishkaar Capital in its ongoing Series B round, with existing investor Info Edge Ventures also joining for an undisclosed amount.