Defining Cost of Failure for AI Systems
Defining the Cost of Failure for AI Systems
AI systems are moving from experiments into real business workflows. But when an AI system fails, the impact isn’t always obvious. A wrong answer, missed decision, unreliable automation, or silent failure can create costs far beyond the technology itself.
In this webinar, we’ll break down how to think about failure in AI systems, not just whether something fails, but what that failure actually costs the business.
What we’ll cover
Failure that doesn’t look like failure - how AI systems can appear to work while creating hidden risks.
Defining the “cost” of failure - understanding the business, operational, financial, and customer impact of AI failures.
Preventing failures - practical ways to identify failure points and design AI systems that are more reliable from the start.
This session is designed for founders, product leaders, technology leaders, and teams building or deploying AI systems who want to move beyond simply asking “Can we build it?” and start asking “What happens when it goes wrong?”
Speakers
Dhaval Patel - Co-founder, AtliQ Technologies; Founder, Codebasics; 1.5M YouTube subscribers
Karandeep Singh Grover - CEO, AtliQ Technologies, has advised 55+ AI, technology, and product startups
Wednesday, 16 September | 10:30 AM EST | Virtual
Free webinar.