Anat Baron

What part of the workflow is human, and what part is AI? Most organizations approach AI backwards, starting with tools instead of outcomes. Teams automate tasks and workflows without deciding who owns the consequences. This keynote introduces a repeatable three-step framework for determining the right blend of human judgment and machine capability for any task, workflow, or role. Leaders leave with clarity on what to automate, what must stay human, and who owns the outcome.

Key Takeaways:

• A three-step framework to audit which tasks and workflows should be human-led versus AI-augmented
• How to identify the human traits that increase in value as AI accelerates
• Explicit boundaries for automation to prevent culture erosion and accountability gaps
• A shift from tool-centric thinking to outcome-centric execution

Most AI pilots don’t fail because the technology is useless. They fail because organizations never redesign decision rights, workflows, or accountability for an AI-driven operating model. This keynote shows leaders how to move from experimentation to measurable operational value, covering the integration audit, outcome mapping tied to P&L, and the ownership handover that determines who is responsible when human judgment and machine output conflict.

Key Takeaways:

• Clear ownership for AI-driven decisions
• Fewer stalled pilots and faster operational impact
• A repeatable path from strategy to execution
• Reduced waste from disconnected AI initiatives

Your most experienced people are disengaging because the new workflow makes their judgment optional. When organizations automate work without protecting expertise, they create a hollow organization. The issue is not only compensation or perks. It is whether the work still values human judgment. This keynote shows leaders how to redesign roles so AI removes friction without stripping authority from the people who drive results.

Key Takeaways:

• How to reduce the loss of high-value experts driven by role erosion
• How to use AI to remove friction without stripping authority from experienced people
• A framework for redesigning roles around human judgment, not just speed
• How to protect the human fail-safe so the business survives an AI glitch

Most futurists speak in decades. Leaders operate in quarters. The risk isn’t missing the future. The risk is committing to the wrong one. This keynote reframes foresight as a discipline of prioritization within a three-year operating window. It helps leaders identify which changes demand immediate action, which require experimentation, and which should be ignored entirely. Updated continuously to reflect the shifting landscape.

Key Takeaways:

• How to identify permanent structural shifts versus hype
• A framework to reduce capital misallocation on trend-chasing
• Clear triggers for when to observe, test, or commit
• Disciplined ongoing experimentation as a replacement for long-range forecasting

Strategy without execution creates frustration. Most AI initiatives stall because teams never decide who is responsible when machines are involved. This hands-on workshop helps teams apply The Human + AI Equation to real workflows, producing concrete decisions, accountability maps, and an execution roadmap. Every AI-supported decision must have a clearly accountable human who owns the consequence. Most workshops generate ideas. This one generates decisions.

Key Takeaways:

• A completed accountability map for AI-driven workflows
• Clear human-in-the-loop rules for high-stakes decisions
• A prioritized execution roadmap teams can apply immediately
• Alignment across leadership and operational teams on AI ownership