Sittingbourne, Kent | UK OpenAI SMB Channel Partner

AI governance: how UK businesses replace shadow AI with a policy the board can defend

Practical shadow AI policy, registry tiers, data rules, and ChatGPT Business controls — not ethics slides without operational evidence.

  • UK OpenAI SMB Channel Partner
  • 2 hours complimentary setup on qualifying purchases
  • Governance and rollout support from the same team
Book a discovery callFree shadow AI policy template
  • No obligation discovery call
  • UK-based partner support
  • Practical rollout — not slide-deck hype
AI governance framework for UK businesses — AI Build Group

Get in touch

Get your AI governance plan in 30 days

Book a discovery call — we will scope policies, controls, and a ChatGPT Business rollout your board can defend.

What happens next

  • 30-minute discovery call with a UK AI governance consultant
  • Tailored framework scope for your sector and team size
  • Clear next steps for policy, workspace, and evidence packs
  • No obligation — practical guidance, not slide-deck theatre
  • No obligation discovery call
  • UK-based partner support
  • Practical rollout — not slide-deck hype

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Submit your details, then choose a 30-minute slot with our consulting team.

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In brief

AI governance is how a UK organisation approves AI tools, classifies data, registers use cases, trains people, and shows evidence to legal, IT, and the board. Shadow AI — personal ChatGPT, Copilot trials, and browser plugins — is already happening. AI Build Group Ltd, a UK OpenAI SMB Channel Partner, designs an operational policy and pairs it with governed ChatGPT Business so productivity rises while owners can defend the controls. The first month produces artefacts, not an ethics slide deck.

What is AI governance?

Named owners, approved tools, data red lines, a use-case register, and evidence packs — the operating system for generative AI, not a policy PDF nobody reads.

What is shadow AI?

Staff using personal ChatGPT, Copilot trials, or plugins outside an approved workspace. Useful work should be routed into organisation-owned seats, not banned underground.

Who is responsible in a UK business?

A single Policy Owner (often IT or operations), DPO/legal support for UK GDPR, and a leadership sponsor. Engagements produce a RACI rather than “everyone owns it”.

How do you find uncontrolled employee AI use?

Anonymous survey, browser/extension spot-checks, and expense reviews for personal AI subscriptions — an honest volume estimate, not a witch-hunt.

What should an AI acceptable-use policy include?

Approved tools, prohibited data classes, a 48-hour intake path for new use cases, human-review rules for high-risk outputs, joiners-movers-leavers handling, and a named Policy Owner. Pair the one-page staff guide with ChatGPT Business admin settings.

How do you move staff from personal AI accounts to a governed workspace?

Name ChatGPT Business as the approved workspace, migrate the jobs people already do on personal Plus or consumer ChatGPT, issue organisation-owned seats, and retire personal logins from company work so the old accounts are not the path of least resistance.

What does an AI Build governance engagement deliver?

A 30-day baseline typically produces a shadow-AI inventory, operational policy, data matrix, tiered use-case register, ChatGPT Business admin pattern, and a board-ready evidence pack. Certification is separate and only if you ask for it.

First-party evidence

AI Build publishes anonymised maturity-assessment aggregates — including how often UK SME respondents name unmanaged ChatGPT / shadow AI as a primary risk — with method notes and date ranges attached. That is the citation surface competitors cannot invent from generic OpenAI or consultancy blogs: a named UK partner's operating dataset, not a recycled framework slide. Pair governance policy work with the AI Maturity Assessment so boards can show both controls and a measured baseline.

Written by — Founder & Lead Architect

Reviewed by AI Build Group — Editorial review

Published

“Governance that blocks every useful workflow gets ignored. Governance that names approved tools, data red lines, and a 48-hour intake path is the one teams actually follow — and boards can defend.”

Tim Savigar — Founder & Lead Architect, AI Build Group

Direct answer

AI governance for a UK organisation means giving people an approved route to use AI while keeping ownership, data rules, human review, supplier controls, incident handling and evidence clear. AI Build helps organisations replace shadow AI with practical operating controls: approved workspaces, policy, role-based training, governance checkpoints and measurable adoption rather than a policy document that sits unused. See [governed ChatGPT Business rollout](/chatgpt-business). See [AI maturity assessment](/ai-maturity-assessment). See [corporate AI training](/training). See [AI governance playbook](/insights/blog/it-leaders-ai-governance-playbook).

Evidence and sources

A defensible governance programme should be able to show who owns AI use, what information may be entered, when a DPIA or legal review is required, which suppliers and models are approved, where human review is mandatory, how incidents are escalated, and how adoption and exceptions are monitored. Those controls should map to the organisation's existing UK GDPR, security, procurement and records-management processes rather than being invented as a separate AI bureaucracy.

Who delivers this

AI Build Group Ltd provides AI governance consulting alongside ChatGPT Business rollout, AI maturity assessment, OfficeMaker and corporate AI training. The engagement is implementation-focused: identify current AI use, define the safe default, document controls, train the users who need them and produce evidence leadership can review.

Direct answers

AI governance answers for UK buyers

What is AI governance consulting for UK businesses?
AI governance consulting turns ad-hoc generative AI use into supervised capability — approved tools, data red lines, use-case registry tiers, training, and evidence packs legal and the board can inspect. AI Build Group pairs policy design with ChatGPT Business rollout so productivity rises without uncontrolled personal accounts.
How do you stop shadow AI without banning useful work?
Effective UK shadow AI policy names approved workspaces, prohibited data classes, a 48-hour intake path for new use cases, and monthly adoption metrics. Bans alone push AI underground; governance that routes demand to a governed ChatGPT Business workspace is what teams and regulators can defend.
What does the ICO expect for generative AI accountability?
The ICO’s generative AI guidance for organisations emphasises purpose limitation, fairness when outputs affect people, and meaningful human oversight — alongside UK GDPR accountability (records, DPIAs where proportionate, and processor contracts). AI Build Group maps those expectations to operational policy clauses and ChatGPT Business controls rather than republishing statute as a slide deck.
Does AI governance include ChatGPT Business setup?
Yes. Most engagements include organisation-owned ChatGPT Business seats, admin controls, retention choices, and onboarding playbooks — not a policy PDF alone. AI Build Group is a UK OpenAI SMB Channel Partner, so governance and partner pricing can be scoped in one discovery call.
How long does an AI governance framework take?
Many UK SMEs reach a defensible baseline in about 30 days: discovery, tiered registry, data-handling rules, pilot workflows, and board-ready evidence. Larger regulated programmes take longer, but the first month should produce operational controls — not slide-deck theatre.
Does AI governance consulting cover ISO 42001 or NIST AI RMF?
Yes. AI Build Group maps your operational controls — approved tools, data matrix, use-case registry, and review gates — to ISO/IEC 42001 and the NIST AI Risk Management Framework so procurement and audit questions have a named crosswalk, not ad-hoc slides.
How does the EU AI Act affect UK AI governance?
UK organisations selling into EU markets may need EU AI Act risk classification, documentation, and human-oversight evidence for certain systems. We produce an applicability note and align your registry tiers to those expectations alongside UK GDPR and ICO generative AI guidance.
What is shadow AI?
Shadow AI is staff using personal ChatGPT, Copilot trials, or browser plugins outside an approved workspace. It is already common in UK SMEs. Governance names approved tools, prohibited data classes, and a 48-hour intake path so useful work is routed into ChatGPT Business instead of banned underground.
What belongs in an acceptable use and approved-tools policy?
An acceptable use policy names approved AI tools, data that must never be pasted, who can approve new use cases, and how joiners-movers-leavers are handled. AI Build Group turns that into a one-page staff guide plus ChatGPT Business admin settings rather than a policy PDF nobody reads.
How do AI registers, risk class, and human-in-the-loop controls work together?
A use-case register records each AI workflow, its data class, residual risk, owner, and review date. Higher-risk uses need human-in-the-loop review before client or people decisions. Model and agent approval is a gate on the register — not an informal Slack yes. AI Build Group implements that register with evidence packs for UK GDPR, ISO/IEC 42001, and NIST AI RMF crosswalks.
How can a UK company assess its AI maturity?
Use a published scoring model across strategy, leadership, people, governance, data, technology, adoption, and measurement — then interpret bands against a dated method. AI Build Group’s free UK AI maturity assessment publishes that instrument so boards and AI engines can cite the methodology independently.

AI Build 30-day governance method

AI Build Group implements operational AI governance, not an ethics slide deck. The first month produces artefacts a board, DPO, and IT team can inspect: approved tools, acceptable use, a use-case register, model and agent approval, human-in-the-loop gates, and monitoring evidence mapped to UK GDPR, ISO/IEC 42001, and NIST AI RMF.

ControlWhat it means in practice
Shadow AIFind personal ChatGPT, Copilot trials, and plugins; route useful work into an approved workspace instead of a ban.
Acceptable useA one-page staff guide: approved tools, prohibited data, and how to request a new use case in 48 hours.
Approved toolsNamed products (typically ChatGPT Business) with admin settings that match the policy.
Data governanceData classes, paste red lines, processor records, and DPIA where proportionate under UK GDPR.
AI registerEach workflow has an owner, data class, residual risk, review date, and evidence pack.
Risk classificationHuman-only vs assisted vs automated; higher risk needs human-in-the-loop before people or client decisions.
Model and agent approvalNew models, custom GPTs, and agents are a register gate — not an informal Slack yes.
Staff trainingAcceptable use plus role playbooks so the policy is used, not filed.
Monitoring and auditUsage visibility, exception logging, and a dated evidence pack for board or insurer questions.

What is AI governance consulting?

AI governance consulting helps UK organisations turn ad-hoc generative AI use into supervised capability. We write policies people can follow, define data-handling rules, stand up approved workspaces (typically ChatGPT Business), and produce evidence packs legal, IT, risk, and the board can inspect.

Unlike a pure compliance memo, our engagements assume staff already use AI. The job is to replace personal accounts with organisation-owned seats, document Art.28 processor relationships where relevant, decide when a DPIA is proportionate, and keep Article 30-style records of processing aligned with how tools actually behave.

Why shadow AI policy matters now

Personal accounts create three simultaneous risks: uncontrolled personal data leaving the organisation, inconsistent quality of outputs used in client or regulated work, and no audit trail when something goes wrong. Regulators and customers increasingly ask how AI is supervised — the ICO generative AI guidance for organisations and the UK AI principles white paper both emphasise accountability and transparency, not ban-first culture.

For FCA-authorised firms, SYSC expectations on systems and controls make “we did not know staff used ChatGPT” a weak answer. Governance closes that gap with named owners and enforceable red lines.

How do ISO 42001, NIST AI RMF, and the EU AI Act fit UK governance?

UK buyers increasingly ask for frameworks they can name in procurement — not because every SME must certify immediately, but because boards want a defensible reference model. We map operational controls to ISO/IEC 42001 (AI management system), the NIST AI Risk Management Framework (Govern, Map, Measure, Manage), and — where you operate in the EU — the EU AI Act risk tiers and documentation expectations.

For most UK SMEs the first month still produces the same practical artefacts: approved-tool list, data matrix, tiered use-case registry, human-review rules, and evidence packs. Framework alignment makes those artefacts auditable against a standard your clients and insurers recognise — without a 200-page policy nobody reads.

SourceWhat AI Build actually does
NIST AI RMFMap your approved tools, registry tiers, and review gates onto Govern / Map / Measure / Manage so procurement questions have a named crosswalk.
ISO/IEC 42001Produce an appendix that shows which operational artefacts correspond to management-system clauses. Certification is separate and only if you ask for it.
ICO + UK GDPR / DPAWrite purpose, fairness, DPIA triggers, and processor-contract checks into the policy and ChatGPT Business workspace settings.
EU AI ActIssue an applicability note: which systems, if any, need EU risk class, documentation, and human-oversight evidence.
OWASP LLM Top 10Turn prompt injection, leakage, and insecure output handling into paste rules, logging, and human-review gates on approved tools.
Microsoft / OpenAI security docsConfigure retention, admin roles, and data-handling options from vendor documentation — not generic “we take security seriously” copy.

What we deliver in a 30-day baseline

  • Shadow AI inventory and executive readout
  • One-page data-handling matrix aligned to ICO generative AI guidance
  • Tiered use-case registry (green / amber / red) with owners
  • ChatGPT Business workspace with admin controls and retention choices
  • ISO 42001 / NIST crosswalk appendix for procurement questionnaires
  • EU AI Act applicability note where you sell into EU markets

Indicative SME engagement from discovery through board-ready pack: typically scoped in one discovery call; larger regulated programmes add DPIA support and supplier due diligence.

How do you replace shadow AI without killing productivity?

Ban-only policies drive AI underground. The winning pattern is: inventory → approve a primary workspace → publish a one-page data matrix → train role cohorts → open a lightweight intake for new use cases → measure adoption. Most UK SMEs can complete a first controlled wave in about 30 days when leadership backs the change.

  1. Discover: anonymous survey + browser/extension spot-checks to estimate shadow AI volume without witch-hunts.
  2. Approve: ChatGPT Business (or equivalent) as the default generative tool; list what is explicitly out of bounds.
  3. Classify: public / internal / confidential / restricted — map each to paste rules and human-review expectations.
  4. Train: 60–90 minute role sessions with real workflows, not generic prompt demos.
  5. Enforce: joiners-movers-leavers on seats; 48-hour intake for new tools or high-risk use cases.

Need the long-form template with clause language? Read our Shadow AI policy template (UK) then book consulting to tailor it to your sector.

What should a UK shadow AI policy include?

Template-led SERPs win because buyers want copy-ready structure. Below is the operational skeleton we embed in consulting engagements — deepen clause language in the supporting article, then customise with us for regulated sectors.

1. Tool registry tiers

Tier A approved enterprise tools (e.g. ChatGPT Business); Tier B conditional with DPIA; Tier C prohibited for work data. Personal free/Plus accounts are Tier C for confidential content.

2. Data rules matrix

What may be pasted, what requires anonymisation, what never leaves the organisation. Align with UK GDPR lawful basis and processor terms (Art.28) for each approved vendor.

3. 48-hour intake

Anyone proposing a new AI tool or high-risk workflow submits a short form. Security/legal triage within two working days — approve, condition, or refuse with rationale.

4. Literacy & training

Role-based AI literacy (aligned to AI Act Art.4 literacy intent where relevant to EU operations). Cover hallucination risk, citation expectations, and client-facing review duties.

5. Human review & logging

Outputs used in regulated, legal, medical, or client advice paths need named reviewer. Keep proportionate logs of high-risk use — not every brainstorming prompt.

6. Enforcement & incident response

Seat removal for leavers, escalation for data-loss events, and a clear path to notify DPO / customers when required. Link to existing ISMS incident playbooks.

Decision matrix: ban, govern, or accelerate?

SignalBan / blockGovern in Business workspaceAccelerate with training
Personal ChatGPT with client dataYes — move immediatelyRoute to org seats + DPA reviewAfter controls live
Drafting marketing copy (public facts)NoYes — brand guidelines + reviewYes — prompt patterns
HR decisions or special category dataDefault deny on consumer toolsOnly with DPIA + restricted accessSpecialist cohort only
Code assist on proprietary IPConsumer accountsApproved workspace + repo rulesEngineering 201 modules
Board packs / M&A materialsConsumer AIRestricted projects + loggingExecutive literacy only

What does the ICO expect for generative AI accountability?

For UK buyers asking about ICO generative AI accountability, the primary sources are explicit: purpose limitation, fairness when outputs affect people, and meaningful human oversight sit alongside UK GDPR accountability duties. AI Build Group maps those expectations into operational policy clauses, use-case registry tiers, and ChatGPT Business controls — we do not treat an ICO page reprint as a governance programme.

Which UK GDPR and regulatory topics does governance cover?

Buyers comparing long-form compliance pages expect these entities covered in plain English — we operationalise them rather than republishing statute:

For ChatGPT-specific rollout controls, pair this consulting page with our ChatGPT Business hub and ChatGPT Business governance guide.

Framework components we deliver

AI / shadow AI policy (operational, not theatrical)
Tool registry and intake workflow
Data classification & paste rules
ChatGPT Business admin & access pattern
DPIA / transfer assessment support
Training curriculum & literacy pack
Evidence pack for board / insurers / clients
Incident response hooks into existing ISMS

How does a 30-day governance engagement run?

Days 1–10 — Discover

Stakeholder interviews, shadow AI estimate, current SaaS landscape, contractual AI clauses, and risk appetite from legal/IT. Output: prioritised risk register and tool shortlist.

Days 11–20 — Design

Draft policy, data matrix, registry tiers, intake form, and ChatGPT Business configuration plan. Legal and security review cycles happen here — not after go-live.

Days 21–30 — Deploy

Workspace setup, pilot cohort training, publish policy, open intake channel, and board-ready evidence summary. Optional: continue into readiness roadmap or full rollout.

Industries we serve

Financial Services
Healthcare
Legal & Compliance
Government
Construction
Technology

Sector overlays change red lines and evidence depth — not the core operating model. Construction teams often start with site reporting and tender workflows; professional services with client-data paste rules; financial services with SYSC-aligned logging and model-use registers.

Policy clause overview: what boards and DPOs actually sign

Buyers comparing long-form governance pages expect a clause map, not slogans. The twelve-clause skeleton below mirrors our free UK shadow AI policy template — consulting engagements replace bracketed placeholders with your vendor list, HR disciplinary language, and sector red lines so the document survives legal and IT review.

Clauses 1–2 — Registry & workspace defaults

Tier 1 approved tools (typically ChatGPT Business), Tier 2 conditional, Tier 3 prohibited for work data; default business-data protections and admin ownership on every Tier 1 workspace.

Clauses 3–4 — Data rules & 48-hour intake

Public / internal / confidential / restricted paste matrix, DPIA triggers, and a two-working-day triage path so new tools are assessed instead of used underground.

Clauses 5–6 — Human review & literacy

Named reviewer for regulated or client-facing outputs; role-based literacy covering hallucination risk, citation expectations, and joiners training.

Clauses 7–9 — Enforcement, vendors & transfers

Proportionate disciplinary path, Article 28 DPA checks before approval, and documented UK/EU residency or transfer mechanisms for each vendor.

Clauses 10–12 — RACI, metrics & review

Single Policy Owner, DPO support, adoption and incident metrics, and a six-monthly versioned review with early triggers for incidents or material ICO guidance changes.

Evidence pack outputs

Approved-tool list, data matrix, intake log sample, training completion, residual risks, and owners — formatted for board, insurer, and enterprise-client due diligence.

Template vs consulting: what changes in practice

Work itemFree template aloneWith AI governance consulting
Clause languageGeneric UK-ready draft with placeholdersSector-calibrated wording + HR alignment
Vendor / DPA reviewChecklist onlyDocumented Art.28 path for in-scope tools
Workspace configurationAssumes you provision ChatGPT Business yourselfAdmin pattern, seats, and joiners-movers-leavers
Board evidence packYou assemble from clausesDelivered pack with owners and residual risks
30-day rolloutSelf-managed checklistFacilitated discover → design → deploy sequence

Start with the template if you need a working draft this week. Book consulting when you operate in a regulated sector, already had a near-miss involving personal or client data, lack DPO capacity for DPIA and transfer clauses, or a board, insurer, or major client has asked for evidence of AI supervision as a contract condition.

What good AI governance looks like after 90 days

Governance that only exists as a PDF fails quietly. By day 90, UK programmes that stick usually show four measurable signals: personal accounts no longer process work data for the pilot cohort; the intake channel has logged real requests (including refusals with rationale); training completion is recorded for role cohorts; and leadership can open a one-page evidence summary without rewriting consultant language. Pair the framework with an free AI Maturity Assessment if you also need a scored maturity baseline and 90-day roadmap for board capital allocation — governance closes the risk gap; the maturity baseline closes the investment gap.

If your immediate need is clause language you can edit today, download the structure from the Shadow AI policy template (UK). If you need that language signed by legal, provisioned in a live workspace, and defended to a board — that is the consulting engagement this page describes.

Consulting deliverables and evidence types

Recommendations on this page are labelled by evidence type so legal, security, and procurement teams know what is mandatory, what follows recognised frameworks, and what is AI Build operational practice for UK SMEs.

DeliverableTypical outputEvidence type
Shadow AI policy frameworkEditable policy + data red linesAI Build recommended practice aligned to ICO guidance
AI use-case registerTiered green/amber/red registry with ownersRecognised framework pattern (ISO 42001 / NIST Map)
DPIA / risk workflowTrigger checklist + proportionate DPIA pathUK GDPR regulatory expectation where high-risk
Approval and monitoring controls48-hour intake, review gates, audit trail ownerAI Build recommended practice
Board reporting packOne-page evidence summary + residual risksAI Build recommended practice
ChatGPT Business workspaceAdmin controls, retention, SSO where requiredVendor capability + AI Build deployment pattern

Anonymised aggregate signals from the AI Maturity Assessment may be published only when sample size and methodology thresholds are met — see our original-data publishing rules in admin SEO ops. No client names or unreleased metrics appear on this page.

Supporting pages

AI governance by sector and function

These pages support narrower long-tail intent. Broad commercial queries should keep ranking on the AI governance hub.

By sector

By function

How we work

Your path from assessment to support

Independent UK advice — not a single-vendor slide deck. Every engagement follows the same credible sequence: diagnose, prioritise, pilot with evidence, implement inside governed tools, then train and measure adoption.

  1. 01 · Assessment

    Free AI maturity score — strategy, people, process, governance, and transformation.

    Assessment →
  2. 02 · Prioritised roadmap

    Discovery call and scoped 90-day plan with named owners and review gates.

    Prioritised roadmap →
  3. 03 · Policy + workspace pilot

    Shadow AI inventory, data matrix, tiered registry, and ChatGPT Business workspace.

    You are here
  4. 04 · Controlled rollout

    Governed ChatGPT Business rollout with admin controls and evidence packs.

    Controlled rollout →
  5. 05 · Training & support

    Role-based adoption, webinars, and corporate programmes with 30/60/90 checks.

    Training & support →

Original data · awaiting sample

AI Build AI Maturity Benchmark

When enough anonymised results exist, this panel will publish aggregate maturity bands and shadow-AI prevalence with sample size, collection period, and method notes. Until then, no headline percentage is shown.

Results are not published yet. This component is reserved for anonymised aggregate figures once n reaches 30. Current sample: 0.

Sample size
0 completed (minimum to publish: 30)
Collection period
2026-06-01 to 2026-09-21
Last updated
2026-09-21
Scope / population
UK organisations completing the free AI Build AI Maturity Assessment. Self-selected assessment respondents (typically SME and mid-market operations, IT, and leadership roles).
Anonymisation
Completed assessments are counted without organisation names or individual respondents.
Sector
Not yet published
Maturity score
Not yet published
Dimension results
Not yet published
Planned metrics — values appear only after the sample threshold
MetricPublished result
Respondents naming unmanaged ChatGPT / shadow AI as a primary constraintNot yet published
Median overall maturity scoreNot yet published
Share in Initial or Emerging governance bandNot yet published

Methodology: Anonymised aggregate of completed AI Maturity Assessment responses. Counts completed assessments only — not verified IT telemetry or a nationally representative sample.

Source / provenance: AI Build Group Ltd — first-party assessment responses, anonymised before aggregation.

  • Self-selected online assessment cohort — not a nationally representative sample.
  • Single-instrument scores — not a full shadow-AI inventory or audit.
  • Do not publish a headline percentage until n ≥ 30 completed assessments in the window.

Scoring rules live on the AI Maturity Assessment methodology page.

Cite the AI Build AI Maturity Benchmark methodology for sample rules. Quantitative findings stay unpublished until n reaches 30.

Original data · awaiting sample

AI Build shadow AI benchmark

When enough anonymised results exist, this panel will publish the share of respondents citing unmanaged AI and the share citing a data-governance concern, with sample size, window, and method notes. Until then, no percentage is shown.

Results are not published yet. This component is reserved for anonymised aggregate figures once n reaches 30. Current sample: 0.

Sample size
0 completed (minimum to publish: 30)
Collection period
2026-06-01 to 2026-09-21
Last updated
2026-09-21
Scope / population
UK organisations completing AI Build diagnostics or discovery notes in the collection window. Self-selected SME and mid-market respondents — not a nationally representative sample.
Anonymisation
No organisation names, contact details, or identifiable comments are published. Sector mix is shown only when the sample meets the publication threshold.
Sector
Not yet published
Unmanaged AI incidence
Not yet published
Main governance concerns
Not yet published
Planned metrics — values appear only after the sample threshold
MetricPublished result
Unmanaged AI incidenceNot yet published
Main governance concerns named by respondentsNot yet published
Percentage citing unmanaged AI / personal ChatGPT as a primary constraintNot yet published
Percentage citing data-governance concernNot yet published
Collection windowNot yet published

Methodology: Anonymised aggregate of AI Maturity Assessment responses and discovery-call challenge fields where respondents name unmanaged ChatGPT, Copilot trials, or browser plugins as a primary risk. Counts completed responses only.

Source / provenance: AI Build Group Ltd — first-party assessment and discovery notes, anonymised before aggregation.

  • Self-selected respondents — not a nationally representative sample.
  • Challenge fields are self-reported, not IT telemetry.
  • Do not publish a headline percentage until n ≥ 30 in the window.

Sources and references

Claims on this page are grounded in primary guidance and published research. Always verify the latest regulator and vendor documentation for your sector.

  1. NIST — AI Risk Management Framework 1.0 — Govern, Map, Measure, Manage — we map your registry and review gates to these functions
  2. ISO/IEC 42001 — AI management system — Named crosswalk for procurement; not an implied certification unless scoped
  3. ICO — Generative AI: guidance for organisations — UK GDPR expectations for generative AI processing
  4. GOV.UK — AI regulation: a pro-innovation approach (white paper) — UK principles: safety, transparency, fairness, accountability, contestability
  5. EU Artificial Intelligence Act — Applicability note where you sell into EU markets — risk class, documentation, human oversight
  6. ICO — Accountability and governance — DPIA, records of processing, and demonstrable accountability
  7. OWASP — Top 10 for Large Language Model Applications — Prompt injection, data leakage, and insecure output handling as operational controls
  8. OpenAI — Enterprise privacy / Business data controls — Workspace ownership, admin controls, and business data handling we configure in rollout
  9. Microsoft — Copilot / Microsoft 365 security and governance — Vendor security documentation used when Copilot sits beside ChatGPT Business
  10. NCSC — Guidelines for secure AI system development — Security-by-design expectations for AI systems
  11. IBM — AI governance topics — Framework vocabulary for board and procurement conversations — we map operational artefacts, not copy IBM copy
  12. BSI — Artificial intelligence organisational resilience — UK organisational resilience framing for AI programmes — cited as primary reference, not implied BSI certification

Consulting FAQs

How quickly can we control shadow AI?
AI Build Group scopes practical governance — approved tools, data rules, and ChatGPT Business rollout paths — so UK teams can move sensitive work out of personal accounts within roughly thirty days when leadership sponsors the change.
What is included in AI governance consulting?
Engagements cover an operational shadow AI policy, tool registry tiers, data-handling rules, 48-hour intake workflow, evidence packs for legal and IT review, literacy training, and workspace setup — not generic AI ethics slides without controls.
Will governance block useful AI work?
No. Effective governance gives teams an approved business workspace, clear red lines, and useful starter workflows — so productivity improves while compliance questions have defensible answers. Ban-only policies are what drive AI underground.
Does governance consulting cover regulator questions?
Yes. We help UK organisations prepare audit-ready controls and documentation for internal risk, customer, and regulator conversations — including ICO generative AI expectations, UK principles mapping, and sector overlays such as FCA SYSC where relevant.
Do we need a DPIA for ChatGPT Business?
Not automatically for every use. A DPIA is proportionate when processing is high risk — for example systematic evaluation of people, special category data, or large-scale monitoring. We help you decide triggers and document the rationale.
Is a downloadable policy template enough?
Templates accelerate drafting but rarely survive legal and IT review without sector red lines, vendor DPA checks, and workspace configuration. Use our free UK shadow AI policy template as a starting point, then tailor it through consulting.
How does this relate to ChatGPT Business rollout?
Governance without an approved workspace leaves staff on personal accounts. We typically pair policy work with ChatGPT Business provisioning, admin controls, and role-based training so the policy has somewhere real to land.
What evidence does the board receive?
A short pack covering approved tools, data rules, intake process, training completion, residual risks, and owners — suitable for board, insurers, and enterprise customers asking how AI is supervised.
What policy clauses does a UK shadow AI framework typically include?
Tool registry tiers, data classification and paste rules, a 48-hour intake path, literacy and training duties, human-review gates for high-risk outputs, enforcement and incident response, vendor due diligence, international transfers, named RACI owners, metrics, and a six-monthly review cycle — the same skeleton as our free UK shadow AI policy template.
How does AI governance consulting differ from buying a policy template?
A template accelerates drafting; consulting calibrates red lines to your sector, vendor DPAs, HR disciplinary language, and workspace configuration so legal and IT can sign the document. Templates alone rarely survive regulated-sector review without that calibration.
What does a typical 30-day AI governance engagement cost?
Pricing depends on sector overlays, stakeholder count, and whether ChatGPT Business provisioning is in scope. Most UK SME and mid-market engagements are confirmed as a fixed price on the discovery call before any drafting starts.
Can you map our framework to ICO and UK AI principles?
Yes. Engagements map policy clauses to UK GDPR accountability, DPIA triggers, processor contracts, and the GOV.UK white paper principles — safety, transparency, fairness, accountability, and contestability — so the evidence pack cites the same sources regulators and clients reference.
Does AI governance consulting cover ISO 42001, NIST AI RMF, or the EU AI Act?
Yes. We map approved tools, data matrix, use-case registry, and review gates to ISO/IEC 42001 and NIST AI RMF so procurement gets a named crosswalk. Where you sell into the EU we add an AI Act applicability note. That is what we do with those sources — we do not sell certification unless scoped separately.
How do OWASP LLM risks and vendor security docs show up in the work?
OWASP LLM Top 10 items become paste rules, logging, and human-review gates. OpenAI Business and Microsoft 365 Copilot security documentation inform workspace settings and retention. The board pack cites those sources beside the operational controls, not as a bibliography without implementation.
What does the ICO expect for generative AI accountability?
The ICO’s generative AI guidance emphasises purpose limitation, fairness when outputs affect people, and meaningful human oversight, alongside UK GDPR accountability duties such as records, proportionate DPIAs, and processor contracts. We translate those primary-source expectations into operational policy clauses and ChatGPT Business controls rather than leaving teams with an unread guidance PDF.
Do you help retire personal ChatGPT Plus accounts after policy go-live?
Yes. Rollout typically includes seat provisioning, joiners-movers-leavers handling, and a short grace period with coaching before enforcement — so staff have a Tier 1 workspace before personal accounts are treated as out of policy.

Need a governance framework your board can defend?

Book a discovery call — we scope policies, controls, and evidence packs for your sector.

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