“Most AI Work Fails Because People Oversell It”: A Sit-Down With Sai Krishna Meka
In an ecosystem increasingly dominated by AI buzzwords and exaggerated claims, Sai Krishna Meka stands out for a different reason—restraint. Founder of iHub-Data, Meka has spent years building applied AI systems for enterprises and public institutions from Hyderabad, largely outside the spotlight. In this sit-down conversation with BharatCEOs, he speaks candidly about realism, responsibility, and why hype is dangerous in AI.
Q: AI is everywhere right now. What frustrates you most about the current discourse?
Sai Krishna Meka:
The overselling. AI is powerful, but it’s not magic. Many founders sell outcomes before understanding the problem deeply. That works briefly in presentations, but reality always catches up.
In real deployments—especially in government or large enterprises—data is messy, assumptions break, and models fail. If you haven’t planned for that, the system collapses.
Q: You chose to build iHub-Data from Hyderabad. Was that a conscious decision?
Sai Krishna:
Yes. Hyderabad allows you to work without constantly performing entrepreneurship. There’s less pressure to appear successful and more room to focus on execution.
For AI work, that matters. You need time to iterate, test, fail, and correct. This city gives you that mental space.
Q: Your company works with enterprises and public-sector systems—areas many startups avoid. Why?
Sai Krishna:
Because those are the hardest problems. Scale, diversity, legacy infrastructure, compliance—nothing is clean or ideal.
But if your AI systems work there, they’re genuinely robust. Consumer demos can hide flaws. Public systems expose them immediately.
Q: What do younger founders misunderstand most about building AI companies?
Sai Krishna:
They confuse tools with understanding. Knowing how to use a framework isn’t the same as understanding data behaviour, bias, or long-term system drift.
AI requires discipline—data hygiene, feedback loops, and continuous monitoring. Without that, models degrade quietly, which is far more dangerous than visible failure.
Q: How do you think about leadership in a technical organisation?
Sai Krishna:
Leadership is about reducing uncertainty. Teams don’t need constant inspiration—they need clarity. What problem are we solving? What assumptions are we making? What happens if we’re wrong?
If leaders can answer those honestly, teams perform better.
Q: Many founders chase visibility. You’ve largely avoided it. Why?
Sai Krishna:
Visibility doesn’t equal credibility. In AI especially, exaggeration damages trust.
We prefer to let systems speak for themselves. If something works consistently, reputation follows—quietly, but sustainably.
Q: What does success look like for you, personally?
Sai Krishna:
Building systems that last beyond trends. AI cycles will come and go. What matters is whether what you built continues to be useful five or ten years later.
If that happens without noise, that’s perfectly fine.
Editor’s Note:
Sai Krishna Meka represents a class of Hyderabad founders building deeply technical companies with restraint and responsibility. In a sector where hype often outpaces reality, his insistence on realism feels not conservative—but necessary.
