AI did not end the data literacy crisis. It changed it. As machines move from providing information to interpreting it and recommending what to do, the scarce skill is becoming judgment: knowing what to trust, what to question, and what decisions are still ours to make.
Evidence does not make decisions. People interpret it, weigh it, challenge it, and make judgments. A courtroom reveals what leaders can learn about evidence, expertise, confidence, and data-informed decision-making.
Feeling sure doesn't mean you're right. Learn five simple ways to question what feels true, spot what might be influencing you, and make better decisions about what to believe.
2025 was not a failure of AI capability. It was a year of recognition.
Organizations invested heavily, experimented widely, and proved that AI can work in isolated contexts. Yet most initiatives stalled before delivering sustained business impact. Pilots multiplied. Dashboards improved. Decisions did not.
This webinar explores what 2025 revealed about the real constraints to AI scale and why the limiting factor was rarely technology.
Drawing on cross-industry research, real organizational patterns, and leadership case examples, we’ll examine why capability consistently outpaced readiness, how well-intentioned AI efforts broke down at scale, and what leaders must fix in 2026 to move beyond experimentation.
This session is not about tools, platforms, or hype. It is about organizational design, decision-making, accountability, and the human systems AI depends on to create value.
Date: Tuesday, February 10, 2025
Time:
Duration: 1 hour
Platform: Zoom (link will be provided upon registration)
Why AI stalled in 2025 despite massive investment
Understand the recurring patterns that caused pilots to multiply while impact remained elusive and why this was not a technology failure.
Why readiness matters more than maturity
Learn the critical difference between having AI capabilities and being able to use them, and why traditional maturity models failed to predict success.
The five preconditions that enable AI scale
Explore the organizational conditions that consistently separate scalable AI efforts from those trapped in pilot purgatory.
The hidden failure modes that block progress
Identify the structural breakdowns like decision ambiguity, workflow fragility, governance theater, weak measurement, and misaligned incentives that quietly undermine AI initiatives.
What leaders must fix in 2026
Leave with a clear sense of where to focus first, how to assess readiness honestly, and what changes enable AI to move from experimentation to sustained value.
This webinar is designed for leaders and practitioners who are responsible for outcomes, not just adoption:
If your organization experimented with AI in 2025 but struggled to scale impact, this session is for you.
