Glossary
C
25 entries beginning with C, the same definitions the articles use.
Capability synergies
The way AI investment in one area (cleaned data, governance frameworks, skills) enables value in entirely different domains, a compounding effect entirely missed by project-based ROI calculations.
Related: Rethinking Business Cases in the Age of AI: What Boards Need to Know
Cascade effect
The compounding ripple of AI value across an enterprise once it takes root, reshaping workflows and unlocking possibilities through successive waves of increasing transformation.
Related: How Agentic AI Turns Your Biggest Tech Problem into Competitive AdvantageAI's Hidden ROI: Measuring Second and Third-Order Effects for Board Decisions
See also:First-order effectsSecond-order effectsThird-order effects
Chain-of-thought
A technique in which a model works through intermediate reasoning steps before answering, improving accuracy on multi-step problems.
Related: Agentic AI: Strip Away the Hype and Understand the Real Strategic Choice
Chart of Entities Concept
The governed set of core entity definitions that, like a chart of accounts, determines what every AI system in the organisation treats as true.
First introduced in: Ontologies and Knowledge Graphs: Why Structure is the Next Data Frontier
See also:OntologyKnowledge graph
Chief AI officer
An emerging executive role, distinct from Chief Data and Chief Technology Officers, accountable for AI strategy, governance, and value realisation as AI becomes a business capability spanning both data and technology.
Related: Return-to-Work Briefing: Five Forces Reshaping the Board AI Agenda in 2026
See also:AI centre of excellence
Cloud centre of excellence
An earlier centralised function, typically within IT, focused on technical excellence and standardisation during cloud adoption; used as a contrast to show why AI teams require broader, Board-level placement.
Related: Introducing the AI Stages of Adoption: A framework for understanding AI readiness in your business
See also:AI centre of excellence
Cloud computing
The on-demand provisioning of remote servers and infrastructure that lets businesses scale capacity up or down as needed, avoiding the overhead of maintaining unutilised physical hardware.
Related: Cloud computing: How to build a business case
See also:Shadow ITDigital transformation
Cloud financial management
The discipline of overseeing cloud expenditure so that development spend is matched to business value, improving transparency, flexibility and efficiency as an organisation migrates to the cloud.
Related: Accelerating innovation with Cloud Financial Management
See also:FinOps
Cloud-native practices
Ways of building and running applications that fully exploit cloud capabilities, enabling faster time to market, more efficient resource use, and easier integration of AI and automation.
CoE 90-Day Sprint Asset
The time-boxed execution method that launches an AI Centre of Excellence’s first pilot portfolio: initiatives scored and selected with the AI Initiative Rubric, run as a ninety-day sprint portfolio that balances quick wins against strategic bets, with governance mechanisms evolving alongside the work rather than ahead of it. Its purpose is to prove the CoE’s value inside a quarter.
Related: AI Centre of Excellence: Your First 90 Days With Well-Advised Value FocusAI Centre of Excellence: Scaling Beyond Pilots to Enterprise Transformation
See also:AI centre of excellenceAI Initiative RubricGraduation criteriaHub-and-spoke model
Cognitive atrophy
The genuine shrinking of critical-thinking abilities from excessive AI reliance, changing how people approach reasoning and judgement over time.
Related: The Redeployment Dividend: Why AI Will Unleash Your People, Not Replace Them
See also:Selective AtrophyIrony of automation
Cognitive computing
Systems that mimic human thought processes by combining machine learning, NLP and other AI techniques to analyse large data volumes and provide intelligent recommendations and decision support, for example in risk assessment and fraud detection.
Related: Introducing the AI Stages of Adoption: A framework for understanding AI readiness in your business
Collective responsibility / accountability
The Cadbury principle that all directors are equally responsible in law for the board’s decisions; experienced in practice as collective accountability, which the chair actively polices under AI conditions.
Related: AI and the Chair: Governing the Board Through The Great Remaking
See also:Agency versus accountabilityAccountability GapDuty of care
Communities of practice
Cross-functional groups of practitioners sharing experiences and solving AI challenges collaboratively through dynamic digital spaces rather than monthly meetings, forming the backbone of knowledge transfer at enterprise scale.
Related: Understanding the AI Stages of Adoption: A framework for business leaders
See also:AI championin-flow learning
Competition Commission
The former UK competition regulator, merged into the Competition and Markets Authority in 2014, whose enquiries could add months to acquisitions that took a buyer past market-share thresholds.
Related: Rumblings in the regional press
Complete AI Adoption Framework Asset
An integration of three mechanisms, the Five Pillars (what capabilities), the AI Stages of Adoption (where functions stand), and Well-Advised (why to invest), providing guiding policy for systematic AI governance.
Superseded by: Remake
Related: Orchestrating Multi-Speed AI: The Complete AI Framework as Guiding Policy
See also:AI Stages of AdoptionFive Pillars of AI CapabilityWell-Advised
Compound Advantage Concept
Self-reinforcing momentum where each coherent action creates conditions for the next to succeed, amnesty feeding the CoE, feeding portfolio decisions, building capability competitors struggle to replicate.
First introduced in: Orchestrating Multi-Speed AI: The Complete AI Framework as Guiding Policy
See also:Compound Loop
Compound Loop Concept
An agentic system that coordinates several AI disciplines running in parallel within a single loop, so their interaction effects multiply value and governance happens once at the coordination layer rather than per technology.
First introduced in: The Compound Loop: Why Agentic AI's Real Power Lies Beyond Generative AI
Related: The Compound Loop: Why Agentic AI's Real Power Lies Beyond Generative AI
See also:Agentic AILoop
Computer vision
The field of AI that allows machines to interpret visual information, from facial recognition and manufacturing quality control to retail inventory monitoring and medical image analysis.
Related: Harnessing AI for organisational change led from the Board
See also:Machine learningDeep Learning
Confidential computing
Hardware-enforced protection of data while it is being processed, not just stored or transmitted, using attested trusted execution environments; it lets sensitive workloads run on shared infrastructure without the provider seeing the data.
See also:Cloud computing
Constitutional AI
An alignment method that shapes model behaviour against a set of explicit written principles; alongside RLHF, one of the ways providers embed value choices into a model.
Context length
The amount of text a model can consider at once; Llama 3 supports an 8K context length, double that of Llama 2, improving its handling of longer inputs.
Counterfactual explanation
An explanation identifying what would have had to be different for an automated decision to reach the opposite outcome, closer to what a data subject actually wants to know than a probability score.
Related: The Reasoning Gap: The Capability the Law Now Demands of Boards
Credit crunch
The economic downturn of 2008, marked by falling house prices, rising food and energy bills, and dented consumer confidence, which reshaped where people spent money.
Related: Financial Times: Just an Illusion
Cultural Sovereignty Concept
The often-overlooked dimension where American, European and Chinese AI cultures embody different worldviews, disruption, deliberation and harmony, shaping architecture, governance and stakeholder engagement beyond regulation.
First introduced in: AI Sovereignty: A Board's Guide to Navigating Conflicting National Agendas
See also:AI Sovereignty Trilemma
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