Technology leadership and transformation
Leading technology through change: interim and fractional ownership, operating-model decisions, modernisation, and turning strategic intent into delivery.
Research sweeps
2026-07-15 · deep
Enterprise AI Transformation Programmes (2025–2026)
Enterprise AI transformation programmes from July 2025 to July 2026: reported success and failure rates and who measures them, delivery frameworks borrowed from and diverging from classic digital transformation, token cost economics and budgeting under consumption pricing, adoption strategy including leadership over-provisioning of access, and AI governance across AI-Ops, financial business cases, security and regulatory controls as they scale with sector risk tolerance, referencing MIT, McKinsey State of AI, DORA, ThoughtWorks Technology Radar, NIST AI RMF, ISO 42001, and the EU AI Act.
Claude Fable 5- financial
- tech
- academic
- +3
2026-06-16 · deep
Designing AI Operating Models Around Humans
How humans are adapting to AI between June 2024 and June 2026, weighing measured benefits and harms, and how organizations should design operating models around human cognitive load and behavioural patterns rather than forcing adoption, covering cognitive overload from supervising multiple agents at machine speed (context switching, automation complacency, vigilance fatigue), the poor budget and value outcomes of top-down AI mandates and token-maximizing usage, the gap between model welfare functions (such as Anthropic's) and any equivalent human or worker welfare function, and how much good human outcomes depend on model training versus orchestration and deployment design.
GPT-5.5- financial
- frontier
- academic
- +3
2026-04-09 · standard
Enterprise Agentic AI Adoption Criteria
Enterprise agentic AI adoption in operational processes November 2025–present: procurement criteria, model drift risk, version stability, availability SLAs, and how enterprises manage dependency on AI vendors in production workflows
Claude Opus 4.8- financial
- frontier
- academic
- +1
Explainers
- Research Explainer · Flyvbjerg et al. (2026)
Most IT projects stay near budget, but a small minority run spectacularly over
Across 5,360 IT projects, 59% finished on or below budget. But the severe-overrun group averaged 453% above budget, creating a fat tail: rare outcomes so large that ordinary averages become dangerously reassuring.
- Research Explainer · Acharya (2026)
Governance maturity makes agent fleets safer, but the evidence is still simulated
A 750-run multi-agent simulation finds that higher governance maturity sharply reduces agent sprawl and risk incidents while improving task completion and composite Net Business Value. Its pivotal claim is that Level 3 is the minimum viable standard, not a decorative middle rung.
- Research Explainer · Zhang et al. (2025)
Agile teams want AI to be a teammate, but the tools, skills, and rules aren't ready yet
A workshop of 30+ researchers and practitioners at XP2025 catalogued six categories of frustration with GenAI in agile software development and co-created a five-theme research roadmap to move from isolated experiments to human-centered integration.