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Episode 55: Predicting Strategy: How AI Forecasts Are Shaping Executive Decision-Making
In this episode of AI Ignited, host Elif Baser welcomes returning guest speaker Mehmet Efe Gurkan to explore how predictive analytics is transforming strategic management—from forecasting demand to guiding executive-level decisions under uncertainty.The conversation dives into the technical backbone of modern strategy, including time-series forecasting models, reinforcement learning, and scenario simulations used in pricing, capacity planning, and long-term resource allocation.
Drawing on research from Stanford University and University of California, Berkeley, the episode examines how probabilistic model outputs are translated into actionable strategy without removing human judgment from the decision loop.Rather than promising certainty, predictive analytics reframes strategy as a risk-managed, adaptive process—one where executives learn to act on distributions, confidence intervals, and evolving signals instead of single forecasts.A must-listen for anyone interested in the technical reality of AI-driven strategy, not just the buzzwords.
Drawing on research from Stanford University and University of California, Berkeley, the episode examines how probabilistic model outputs are translated into actionable strategy without removing human judgment from the decision loop.Rather than promising certainty, predictive analytics reframes strategy as a risk-managed, adaptive process—one where executives learn to act on distributions, confidence intervals, and evolving signals instead of single forecasts.A must-listen for anyone interested in the technical reality of AI-driven strategy, not just the buzzwords.
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By Elif BaşerIn this episode of AI Ignited, host Elif Baser welcomes returning guest speaker Mehmet Efe Gurkan to explore how predictive analytics is transforming strategic management—from forecasting demand to guiding executive-level decisions under uncertainty.The conversation dives into the technical backbone of modern strategy, including time-series forecasting models, reinforcement learning, and scenario simulations used in pricing, capacity planning, and long-term resource allocation.
Drawing on research from Stanford University and University of California, Berkeley, the episode examines how probabilistic model outputs are translated into actionable strategy without removing human judgment from the decision loop.Rather than promising certainty, predictive analytics reframes strategy as a risk-managed, adaptive process—one where executives learn to act on distributions, confidence intervals, and evolving signals instead of single forecasts.A must-listen for anyone interested in the technical reality of AI-driven strategy, not just the buzzwords.
Drawing on research from Stanford University and University of California, Berkeley, the episode examines how probabilistic model outputs are translated into actionable strategy without removing human judgment from the decision loop.Rather than promising certainty, predictive analytics reframes strategy as a risk-managed, adaptive process—one where executives learn to act on distributions, confidence intervals, and evolving signals instead of single forecasts.A must-listen for anyone interested in the technical reality of AI-driven strategy, not just the buzzwords.