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As organizations rapidly embed AI into business processes, one fundamental shift is often underestimated: AI systems are inherently probabilistic, not deterministic.

Unlike traditional applications where outcomes are predictable and rule-driven, AI introduces variability, ambiguity, and the real possibility of failure—even when everything appears to be working as intended.

This shift calls for a different way of thinking from Business Analysts.

In this session, we explore why AI failure is not just an exception to manage, but a design consideration from the outset, and how the BA role needs to evolve—from defining what should happen to also anticipating what could go wrong. We will look at where traditional requirement approaches fall short in AI-led initiatives, and how they need to adapt to incorporate guardrails, confidence thresholds, exception handling, and human oversight.

Agenda:
  • How to model uncertainty within requirements 
  • Designing human-in-the-loop vs. human-on-the-loop systems
  • Handling hallucinations, bias, and edge cases from a BA perspective
  • Moving from static specifications to “AI behavior contracts”
 
Speaker Profile

Vikas Mathad is a seasoned business transformation leader with 20+ years of experience turning complex business challenges into elegant, scalable solutions. Currently leading Business Systems Analysis & Product Management at Concentrix Catalyst, he helms a team driving conversational AI products that reshape customer experiences and streamline enterprise operations.

With deep roots in pre-sales, solutioning, and delivery, Vikas brings a rare combination of strategic vision and hands-on execution. From defining healthcare and retirement product roadmaps at Fidelity Investments to spearheading AI-powered process reengineering at Concentrix, he has consistently delivered measurable business impact — on time and on budget.

Vikas speaks on the intersection of AI, business analysis, and digital transformation — making complex ideas accessible, actionable, and inspiring for both technical and business audiences.

Attendees will leave with practical frameworks and actionable techniques to ensure AI-enabled solutions are not just intelligent, but also resilient, reliable, and responsible.
 
 
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