Glossary
P
22 entries beginning with P, the same definitions the articles use.
Personal AI agent
An always-on AI system owned and trained by an individual that learns their workflows and encodes their professional judgement and decision-making patterns, forming a portable, individually owned repository of capability that travels with the person when they change employer.
Related: The Personal Agent Economy: When Your Best AI Isn't On Your Balance Sheet
See also:AI agent
Physical AI
AI embodied in machines such as robots and autonomous vehicles that act in the material world, moving AI’s economics from software margins into hardware capital cycles.
Related: AI Centre of Excellence: Future-proofing Through Continuous Evolution
See also:Embodied AI
Pilot purgatory
A stalled state where organisations run AI pilots but fail to convert them into scaled value, remaining stuck while early adopters that invested in talent and governance compound returns.
Related: AI Centre of Excellence: Scaling Beyond Pilots to Enterprise Transformation
See also:Pilot Success TrapAI Maturity Mirage
Pilot Success Trap Concept
Isolated pilot wins that create a seductive appearance of advancement while revealing nothing about systemic readiness across an organisation whose functions sit at different stages.
First introduced in: The AI Maturity Mirage: Diagnosing the Gap Between Investment and Readiness
Platform thinking
Reimagining AI delivery so shared capabilities, data access, model development, deployment, measurement and knowledge, are built as reusable platforms rather than bespoke project solutions, transforming the economics and governance of scaling.
Related: AI Centre of Excellence: Scaling Beyond Pilots to Enterprise Transformation
Pod
The unit of forward deployment: a small, self-contained team pairing forward deployed engineers with domain experts, the people who know the work being remade inside out, and the operators who own it, embedded in a single business area to take one problem from ambiguity to working software. Pods scale by multiplying rather than growing, so the Board-level questions are how many are running, where they sit, and who is accountable for what each one changes.
Related: Remake
Poison Tokens
Data points inserted into AI training data to corrupt it, skewing or distorting the model’s outputs.
Related: Harnessing AI for organisational change led from the Board
See also:Training
Portfolio orchestration
Strategic concentration of resources where they generate maximum leverage, mapping initiatives against the framework and sequencing them for compound value, turning multi-speed adoption into competitive strength.
Related: Orchestrating Multi-Speed AI: The Complete AI Framework as Guiding Policy
See also:LeverageMulti-Speed Adoption
Post-quantum cryptography
Encryption designed to withstand attack by future quantum computers; standards and migration timelines are already set, making harvest-now-decrypt-later exposure a present governance question rather than a distant one.
Signal: Post-Quantum Cryptography
See also:Quantum computing
Pre-mortem
An exercise imagining in advance why a proposal might be rejected, used to prepare concise, evidence-based responses to likely board objections before the presentation.
Related: Rethinking Business Cases in the Age of AI: and Securing Buy-In from the Board
Pre-training
The initial, compute-intensive phase where a foundation model learns general patterns from a very large, broad dataset.
Related: Ethical AI: When the Model Imposes Values Your Organisation Did Not Choose
See also:Foundation modelTraining
Predictive analytics
Using historical patterns and synthetic scenarios to forecast future trends, listed as an operational enhancement path for extracting value from enterprise data assets.
Related: Demystifying AI: My Chief Wine Officer Talk
See also:Decision Analytics
Predictive indicator
A forward-looking measure that models possible futures under explicit assumptions rather than reporting what has already happened. It offers a Board structured probability, not certainty, and its worth depends entirely on the assumptions being stated and open to challenge.
Related: Transforming the Board: Using Decision Analytics for Strategic Advantage
Principled Standardisation Concept
A strategic stance applying the strictest global standard, typically European, everywhere, betting that trust and consistency create durable advantage in sectors such as healthcare and finance where trust determines access.
First introduced in: AI Sovereignty: A Board's Guide to Navigating Conflicting National Agendas
probabilistic system
A model trained on patterns in historical data whose internal logic of weights, activations and correlations cannot be inspected for an individual case, so explainability must be engineered in at design time.
Related: AI and the Director: A Practical Playbook for Governing What You Can't Fully See
See also:Reasoning Gaprule-based systemData (Use and Access) Act 2025
Process Audit Asset
The per-process evaluation applied one process at a time: what the work is for, how it is done today and whether it is still needed, and why it needs the technology at all, returning a verdict on the Stop, Keep, Remake scale with every reading graded by indicator type. For a Board, it means each verdict in a transformation plan traces to evidence rather than to opinion.
See also:Stop Keep Change ModelMaximum FidelityWell-AdvisedSix Board ConcernsRemake
Process Redesign Loop Concept
The institutional capability for redesign itself: accumulated knowledge, cross-functional relationships, and governance that make each successive restructuring of work around AI faster, compounding organisational learning capacity rather than just productivity.
First introduced in: The Great Remaking: Why Fast Following Does Not Work When the Gap Compounds
Related: The Great Remaking: Why Fast Following Does Not Work When the Gap Compounds
See also:Compound Loop
Project thinking
Treating each AI initiative as unique, requiring bespoke solutions for data access, model development, governance and value measurement; workable for pilots but unsustainable at scale, creating redundancy and ungovernable complexity.
Related: AI Centre of Excellence: Scaling Beyond Pilots to Enterprise Transformation
Project-ROI
A return-on-investment calculation that stops at the attributable benefit of a single project, and therefore cannot register AI value that accumulates and crosses functions.
Prompt engineering
The practice of designing and refining the instructions given to a model to elicit more accurate, useful or reliable outputs.
Related: Selecting your enterprise LLM: Moving beyond the hype to make the right choice
See also:Large language model
Prompt Injection
A method of injecting harmful prompts into AI input to manipulate its responses, similar to SQL injection in databases; secure and monitored inputs can prevent such attacks.
Related: Harnessing AI for organisational change led from the Board
See also:Poison TokensGuardrails
Prosumer
An entity that both produces and consumes electricity; data centres absorbing excess renewable generation at peak and exporting during low-demand periods exemplify this dual producer-consumer role.
See also:Virtual power plant
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