Papers
Five series, 37 papers, on what artificial intelligence actually changes inside organisations that carry accountability for their decisions, and what it does not. Every paper is here in full, free, with no registration. Each states the kind of evidence behind every substantive claim, and says plainly where that evidence is thin.
Ecaveo Responsible AI Series
Papers on deploying artificial intelligence inside organisations that carry accountability for their decisions. Each paper stands alone. Together they argue that durable advantage comes from decisions that can be reconstructed afterwards.
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The Known Safe State
artificial intelligence in critical national infrastructure and government
Abstract · PDF, 2.1 MB · RIS
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Partial Understanding
artificial intelligence in insurance, wealth management and financial services
Abstract · PDF, 2.0 MB · RIS
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Verified Authority
artificial intelligence in law firms and the duties it already tests
Abstract · PDF, 1.9 MB · RIS
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Responsible AI Adoption in Media and Film
rights, consent and provenance at delivery
Abstract · PDF, 4.0 MB · RIS
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The Protected Constraint
artificial intelligence in haulage, warehousing and distribution
Abstract · PDF, 2.0 MB · RIS
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Sufficient and Appropriate
artificial intelligence, audit evidence and professional scepticism
Abstract · PDF, 1.7 MB · RIS
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Responsible AI Adoption in Health Research
why evaluation capability sets the ceiling
Abstract · PDF, 3.4 MB · RIS
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Commensurate Confidence
artificial intelligence, assurance and airworthiness in aerospace and defence
Abstract · PDF, 2.3 MB · RIS
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The Traceable Thesis
artificial intelligence across the private equity investment lifecycle
Abstract · PDF, 1.7 MB · RIS
Enterprise AI, 2023 to 2024
Nine papers written month by month across the first two years of enterprise generative artificial intelligence. Each was written to what was known at the time and each stands alone. Read in order, they are a record of how the evidence moved, and of where the early claims did not hold.
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From Assistants to Early AI Agents
an enterprise operating model for action-taking AI
Abstract · PDF, 1.0 MB · RIS
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AI Regulation and Risk Readiness
a practical crosswalk between European law and voluntary risk guidance
Abstract · PDF, 1.0 MB · RIS
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From BYOAI to Business Value
channelling bottom-up adoption into enterprise impact
Abstract · PDF, 0.9 MB · RIS
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The Rise of the Chief AI Officer
mandate, operating model and first 100 days
Abstract · PDF, 0.9 MB · RIS
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Guardrails Before Scale
an enterprise governance blueprint for generative AI
Abstract · PDF, 0.9 MB · RIS
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From Pilots to Copilots
scaling enterprise generative AI with data, controls and measurable value
Abstract · PDF, 0.9 MB · RIS
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The Enterprise AI Skills Map
building workforce readiness for generative AI
Abstract · PDF, 0.9 MB · RIS
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Prompt Literacy at Work
a practical framework for better human and machine collaboration
Abstract · PDF, 0.8 MB · RIS
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From Curiosity to Capability
the early enterprise generative AI adoption playbook
Abstract · PDF, 0.9 MB · RIS
Ecaveo Working Papers, AI Adoption: The Higher-Order Issues
Six papers written across the first seven months of public generative artificial intelligence, on the questions that sit above any particular tool. How evidence decays, what assistance costs an expert, what an organisation actually adopts, who owns an outcome, what an approval is worth once the system changes, and what waiting costs. Each paper stands alone.
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The Cost of Waiting
precaution, Opportunity and the Ethics of Not Adopting AI
Abstract · PDF, 0.5 MB · RIS
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Approved Once, Changed Daily
from Point-in-Time Ethics to Continuous AI Assurance
Abstract · PDF, 0.6 MB · RIS
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Everybody's System, Nobody's Risk
accountability Gaps in Distributed AI Governance
Abstract · PDF, 0.7 MB · RIS
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The Unit of Adoption
why Organisations Adopt Configurations, Not Models
Abstract · PDF, 0.5 MB · RIS
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The Competence Paradox
when AI Makes the Team Better and the Expert Worse
Abstract · PDF, 0.5 MB · RIS
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Knowledge With an Expiry Date
evidence, Evaluation and Decision-Making When the AI System Keeps Changing
Abstract · PDF, 0.7 MB · RIS
Athleet.AI Performance Intelligence Series
Papers on the responsible use of artificial intelligence in performance sport. Each paper stands alone. Together they argue that advantage in sport comes from better decisions rather than more data.
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The Augmented Golfer
AI across technique, practice, strategy and player development
Abstract · PDF, 1.3 MB · RIS
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The Augmented Touchline
how responsible AI can transform elite football performance and player development
Abstract · PDF, 1.0 MB · RIS
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The Connected Endurance Athlete
integrating training, recovery and race execution in triathlon with AI
Abstract · PDF, 1.4 MB · RIS
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Casting the Net Wider
AI as a force multiplier for talent discovery in grassroots and academy football
Abstract · PDF, 0.9 MB · RIS
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Closing the Coaching Gap
how responsible AI can strengthen grassroots athletics without replacing the coach
Abstract · PDF, 0.9 MB · RIS
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The Intelligent Track
AI, event-specific expertise and the future of elite athletics coaching
Abstract · PDF, 0.7 MB · RIS
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The Responsible Performance System
governance, explainability and trust in AI for sport
Abstract · PDF, 1.3 MB · RIS
Athleet.AI Working Papers, AI in Coaching and Athlete Development
Six papers on artificial intelligence in coaching and athlete development, written alongside the enterprise series and addressed to coaches, pathways and governing bodies. Talent prediction, coaching judgement, children's data, developmental fairness, training load, and who receives the benefit. Each paper stands alone.
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Democratised or Stratified?
aI, Competitive Fairness and the Grassroots Coaching Gap
Abstract · PDF, 0.7 MB · RIS
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Load, Readiness and False Precision
the Limits of Algorithmic Training Prescription in Long-Term Endurance Development
Abstract · PDF, 0.6 MB · RIS
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Maturation, Bias and the Training Set
developmental Fairness in AI-Supported Athlete Development
Abstract · PDF, 0.6 MB · RIS
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The Measured Child
datafication, Consent and Autonomy Across the Athlete Pathway
Abstract · PDF, 0.6 MB · RIS
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The Coach in the Loop
tacit Knowledge, Professional Judgement and the Risk of Deskilled Coaching
Abstract · PDF, 0.6 MB · RIS
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Predicting the Unpredictable
why Algorithmic Talent Identification Struggles With Non-Linear Athlete Development
Abstract · PDF, 0.6 MB · RIS
