AI Growth Lab: regulated AI trials for planning, health and core services
The government has outlined plans for a regulated testing programme, the "AI Growth Lab," to let organisations trial AI products in live settings with certain rules relaxed. Early pilots will focus on planning approvals and housing, where delays are common and paperwork is heavy.
Announced at industry events in London on Tuesday, 21 October, the proposal creates sector "sandboxes" across health, planning, professional services, transport and advanced manufacturing. The aim: speed up safe adoption, gather evidence, and cut friction without losing safeguards.
Why planning is first in line
Planning officers face huge workloads. A typical housing application can reach 4,000 pages and take up to 18 months from submission to decision.
Within the Growth Lab, AI tools could help triage documents, flag policy conflicts, auto-generate summaries, and support consistent decisions. Ministers link this to the target of 1.5 million new homes by the end of the current Parliament.
How the sandboxes would work
- Time-limited trials with defined objectives and reporting duties.
- Regulatory requirements modified or suspended for fixed periods to test outcomes.
- Licensing regime overseen by technical and regulatory experts.
- Regulators able to pause trials and apply penalties if conditions are breached or harms emerge.
- Clinical use remains subject to human oversight.
Health: where AI could help now
Sandboxes could test AI for diagnostics support, triage, and admin tasks to ease pressure on NHS waiting lists. The MHRA is being offered a £1 million pilot fund to trial AI that supports drug discovery, trial assessment and licensing processes.
Any deployment would keep clinicians in control, with clear accountability and audit trails.
What this means for public sector leaders
This is a chance to run tightly scoped trials that cut paperwork and improve throughput while keeping control of risk. It's also a prompt to get your house in order: data, procurement, and governance will decide who moves first.
Practical steps to get sandbox-ready
- Prioritise high-volume, rules-based tasks with measurable outcomes (turnaround time, error rates, appeals).
- Map your data: sources, quality, retention, legal basis, and access controls. Create small, well-labeled pilot datasets.
- Set guardrails: model cards, risk registers, DPIAs, fairness checks, and human-in-the-loop thresholds.
- Tune procurement: outcome-based contracts, clear exit criteria, IP/data terms, and vendor security requirements.
- Define decision rights: who signs off trials, who monitors performance, who can pull the plug.
- Plan change management: staff training, process updates, and communications with stakeholders and unions.
Example metrics to track
- Median time from application to decision (planning) or referral to outcome (health).
- Percentage of documents auto-classified and summarised with human acceptance rates.
- Policy conflict flags caught pre-submission vs post-submission.
- Appeal/reversal rates and reasons, before vs after pilot.
- Cases per officer per week and administrative hours saved.
- Data incidents, model drift alerts, and bias tests passed/failed.
Safeguards you can point to
- Time-boxed licences, defined scopes, and independent oversight.
- Transparent documentation: data lineage, evaluation methods, and known risks.
- Human oversight for consequential decisions, with clear escalation paths.
- Red-team testing, incident reporting, and kill-switch procedures.
- Public accountability: publish pilot goals, metrics, and post-trial reports.
Open questions under consultation
- Who runs the programme: a central team or sector regulators?
- How licences are awarded and renewed, and what evidence is required.
- Baseline requirements for transparency, data protection, and citizen redress.
- How local authorities and NHS trusts access support, funding, and technical expertise.
Why now
AI uptake by UK firms sits at around 21%, yet independent analysis suggests responsible deployment could lift productivity. Ministers argue sandboxes reduce uncertainty and move good ideas from trials to service delivery faster.
Selected industry reaction
- Liz Kendall, Technology Secretary: "This isn't about cutting corners - it's about fast-tracking responsible innovations that will improve lives and deliver real benefits."
- David Wakeling, A&O Shearman: An agile approach that removes needless red tape and breaks down silos can keep UK businesses competitive.
- Luther Lowe, Y Combinator: Faster time to market with appropriate oversight sets a strong model for governments.
- Paul Murphy, Lightspeed: Regulatory speed influences where breakthrough companies scale.
- Antony Walker, TechUK: A pro-growth regulatory approach can help companies safely develop, scale and deploy AI in key sectors.
- Hugh Milward, Microsoft: Flexible regulation will support faster UK AI innovation across the economy.
- Tim Bazalgette, Darktrace: Monitored sandboxes can prove real-world value and speed deployment across critical areas.
- Nigel Toon, Graphcore: A forward-looking approach can drive AI adoption, echoing lessons from the fintech sandbox.
How planning authorities could pilot AI
- Automated document intake: classify, de-duplicate, version, and summarise large submissions.
- Policy checks: flag likely conflicts against local plans and national policy before case officer review.
- Geospatial validation: compare proposals against flood risk, protected sites, and transport access layers.
- Public engagement summaries: plain-English digests of key issues raised during consultation.
- Case officer support: structured decision templates with citations and evidence trails.
What happens next
The government will gather consultation responses, finalise governance, and select pilots. Regulators will set licence terms, metrics, and enforcement powers. Departments, local authorities and NHS bodies that prepare now will be first in the queue.
Useful references
- FCA Regulatory Sandbox (precedent for live testing)
- Medicines and Healthcare products Regulatory Agency (MHRA)
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