Insights
Perspectives from the front lines of enterprise change.
Research, points of view and case notes from our engagements with global enterprises. Written by our consultants and faculty.
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5 Reasons Your AI Training Is Not Translating to Workforce Performance
When AI training does not change performance, the problem is usually structural rather than motivational.
Read the pieceAI-Augmented Professions: Are Your Teams Ready for Human-AI Collaboration?
The future of work is not humans versus AI. It is humans working with AI better than others do.
Read the pieceThe Hidden Barrier: Why Only 20% of Senior Employees Get AI Training
The AI capability gap is not evenly distributed. Uneven access to upskilling across generations and seniority levels creates a dangerous mismatch.
Read the pieceBeyond Tools: Why AI Readiness Is a People, Culture, and Governance Problem
Organizations often assume AI readiness is mainly a technology issue. In practice, the harder problems are social and organizational.
Read the pieceFrom Pilot to Production: The 3-Step Enterprise AI Transformation Blueprint
Many enterprises can launch an AI pilot. Far fewer can scale one. The difference usually has less to do with model quality than organizational readiness.
Read the pieceBayer's 3-Tier AI Academy: The Model Every Enterprise Should Study
Bayer’s tiered learning approach illustrates how AI capability can be structured as an enterprise system rather than a one-off training initiative.
Read the pieceAI's $15 Trillion Prize Will Be Won by Learning, Not Just Technology
The long-term prize will go to organizations that learn faster than competitors, not just to those that buy more technology.
Read the pieceDesigning the AI-First Workforce: Building for Judgment, Not Just Efficiency
The most important workforce question is no longer how to make people better at using AI. It is how to redesign work so human strengths become more valuable.
Read the pieceThe BFSI AI Capability Crisis: Why Banks Are Training Thousands But Transforming Nothing
Banks face one of the sharpest versions of the AI capability gap because they operate under heavy regulatory pressure, legacy process complexity, and low tolerance for error.
Read the pieceIT/ITES and the Capability Paradox: The Industry That Builds AI Can't Always Use It
Technology and services firms are expected to lead on AI, yet many struggle with their own internal adoption.
Read the pieceProfessional Services in the AI Age: When Billable Hours Meet Machine Efficiency
Professional services firms face a subtle AI capability challenge: their value proposition depends on expertise, trust, and billable time, yet AI creates pressure to deliver more efficiently.
Read the pieceThe AI-Ready CXO: What Separates Leaders Who Transform From Leaders Who Delegate It
Executive leadership quality is one of the strongest predictors of whether enterprise AI programs scale effectively.
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