Research Reports
Published reports and long-form analysis.
- When Technology Creates More Work Than Value
Technology investments are usually justified by what a new capability makes possible. This report examines what the organization must do to support that capability, why automation often changes where work occurs rather than eliminating it, and five considerations for evaluating the full consequences of a technology decision.
- The Carrying Cost of More: Why Good Decisions Accumulate Into Burden
Organizations are good at calculating what the next addition will deliver and poor at calculating what it will have to carry. This follow-up to the Enough Point essay examines why individually rational features, metrics, automations, and AI capabilities accumulate into organizational burden, and why AI is likely to accelerate the pattern.
- AI Disproved an 80-Year-Old Conjecture. Should We Be Asking a Different Question?
In May 2026 an AI model disproved a conjecture in discrete geometry that had held since 1946. The real question for leaders, this essay argues, isn't what AI can do next, but how to tell when the next increment of capability stops being worth the burden it brings.
- Technical Workforce Concentration as a Correlate of AI Adoption Across Industries
An industry-level analysis linking U.S. Census BTOS 2026 AI adoption data with BLS OEWS workforce composition data across 19 NAICS sectors. Finds that digital technical employment concentration is the strongest workforce correlate of sector-level AI adoption, with implications for benchmarking, strategy, and policy.
- From Pilot to Production
An operational guide to scaling AI initiatives beyond the proof of concept. Synthesizes research from McKinsey, AWS, Deloitte, and Concentrix on the five root causes of pilot stall, with a seven-step framework and production readiness checklist.
- Building Leaders Through Co-Intelligence: From Strategy to Practice
A practical framework for moving from AI ambition to managerial practice by strengthening judgment, capability development, and co-intelligence leadership behaviors across the enterprise.
- The Middle Management Challenge: Leading Through AI Transformation While Learning It Yourself
An analysis of the credibility paradox facing middle managers as they lead AI transformation while learning the technology themselves, with practical strategies for managing uncertainty, role strain, and team adoption.
- Why Enterprises Can't Automate Their Way to Profitability
A strategy report arguing that sustainable AI profitability comes from human-AI collaboration, operating model redesign, and innovation-led growth rather than automation-only cost reduction programs.