This panel will explore what it takes to move beyond pilots and proofs of concept to operationalizing AI responsibly—across architecture, governance, security, data strategy, and business alignment. Leaders will discuss the technical, organizational, and risk-management challenges that emerge as AI adoption scales across the enterprise

As the winner of the 2022 Orbie Leadership Award and past Orbie and other awards, Al Lindseth has been a thought leader within the energy sector and IT profession for many years. Incredible risk and disruption are driving the need for companies to adapt and drive transformational and change efforts, but the track record and return on these investments are horrible.  Success requires different skill sets.  Traditional approaches are not transformative or agile enough.  Focusing on technology-driven disruption or change efforts and using a specific example around AI, Al will posit five specific reasons why these larger efforts and general attempts to wrestle with change and risk fail - with a goal for attendees to learn how to avoid these issues with the right approach.

Manufacturing doesn’t fail because of bad data. It fails because the right person didn’t have the right answer at the right moment.

Plant floors generate more data than almost any other environment on earth yet most of it ends up in a dashboard that a VP opens three days after the decision already had to be made. The gap between data and decision is where margin disappears, downtime compounds, and capital gets misallocated.

Yatharth Sejpal, Founder & CEO of KNOWIDEA Technologies, built a system to close that gap. In this session, he shows how manufacturers are replacing reactive reporting with predictive intelligence AI systems that anticipate equipment risk before failure, flag supply chain exposure before it becomes a disruption, and surface capital allocation signals before the window closes.

This is not a BI upgrade. It’s a fundamentally different way of running operations.
You’ll leave with:
• A framework for moving from descriptive analytics to predictive and prescriptive intelligence at the executive layer
• A practical approach to embedding AI-driven forecasting into existing BI environments without ripping out legacy infrastructure
• A blueprint for designing decision workflows that deliver the right insight to the right operations leader at the right moment
• Clear metrics for measuring faster, more confident decision-making acros

This panel will explore how AI agents are reshaping workflows, decision-making, operating models, and workforce expectations. Leaders will discuss where agentic AI is creating real enterprise value, where organizations are overestimating readiness, and what must change to scale these capabilities responsibly.

As organizations accelerate modernization and AI adoption, leaders face increasing pressure to innovate faster while managing cyber risk, operational complexity, talent shortages, and economic uncertainty (e.g. cloud costs). This panel will explore how top organizations are making investment decisions, prioritizing initiatives, and aligning technology strategies to measurable business outcomes.