The Level AI Strategy: Building for Infrastructure Reality vs AI Hype

The Level AI Strategy: Building for Infrastructure Reality vs AI Hype

While most AI startups rush to announce their latest generative AI features, Level AI faced a sobering reality: 75% of their target market was still running on legacy infrastructure. In a recent episode of Category Visionaries, founder Ashish Nagar shared how this insight shaped their entire go-to-market strategy.

The Infrastructure Reality Check “More than 75% of all contact centers are run on premise systems… they are not on cloud,” Ashish reveals. This reality creates a stark disconnect between AI vendors’ promises and customers’ capabilities. “It’s not as if you can’t take calls anymore. It’s keeping your lights on, but it just doesn’t make you ready for the modern customer.”

Practical Over Trendy Rather than pushing the latest AI buzzwords, Level AI focused on solving immediate customer problems. “Were using Generative AI for many years before it became cool,” Ashish notes. “And there are many other techniques which we use which just solve customer problems.” This pragmatic approach resonated with enterprises struggling to modernize their operations.

The Customer’s Perspective Enterprise buyers care about solutions, not technology labels. As Ashish explains: “Often customers don’t even know the difference between the two. And I’m not saying because they are ill informed, it’s just because it’s not their job.” This insight helped Level AI cut through the noise in sales conversations.

Building for Transformation Reality Digital transformation isn’t a switch you flip – it’s a journey. Ashish observes: “You’ll be amazed… the amount of work it takes to have a digital transformation effort like that, it’s ridiculously big and it takes five years or three years sometimes to replace some of this stuff.”

The Integration Challenge The real challenge isn’t just technical capabilities – it’s integration with existing systems. “No one in the ecosystem is incentivized to make it faster and cheaper. Everyone wants their slice of the pie,” Ashish notes. Level AI designed their platform to work within these constraints rather than demanding complete system overhauls.

A Balanced Approach to Automation Looking ahead five years, Ashish predicts: “If I had to pick a number, somewhere between 50% to 70% of the work would still be done by humans.” This realistic view of automation’s potential helps Level AI build solutions that enhance rather than replace human capabilities.

The Results This infrastructure-first approach has helped Level AI succeed where many AI startups struggle: enterprise adoption. By acknowledging and building for infrastructure realities, they’ve created solutions that deliver immediate value while supporting customers’ longer-term transformation goals.

For B2B tech founders, Level AI’s story offers a crucial lesson: success in enterprise AI isn’t just about having cutting-edge technology – it’s about understanding and working within the constraints of your customers’ infrastructure reality. Sometimes, the most innovative solution is the one that actually works with what customers have today.