What is a Fractional AI Director?

Board-level AI leadership, without the full-time headcount. I work with your leadership team on strategy, governance, and implementation: the full scope of a Chief AI Officer, on a retained part-time basis. The difference from a consultancy is accountability. I stay responsible for what gets built, not just until the strategy document is finished. For most UK SMEs and councils, that costs 70-85% less than a permanent Chief AI Officer appointment.

How much does a Fractional AI Director cost?

Retainers start at £3,500 per month, covering two to four hours of strategic advisory work, and go up to £8,500 per month for a full fractional engagement where I'm in your organisation 16 to 20 hours a month. Standalone project work is £1,750 per day with a two-day minimum, fixed scope and fixed fee. Every retainer is monthly rolling with a 30-day exit clause. There is no lock-in.

What ROI can I expect from AI implementation?

That depends on your starting point, which is why every engagement begins with an audit rather than a promise. The Midlands council engagement delivered £780,000 in combined savings and recovered funding. Ninety days into a manufacturing SME engagement, operating costs were down 43%. The regional law firm freed 40% of senior fee-earner time and found £2.1M in new revenue through documents they already had. In each case the bottleneck was not the AI: it was data quality and governance problems that had been sitting there for years.

Do you work with local councils and government organisations?

Yes, and public sector work is a significant part of the portfolio. The Midlands council case study is the most detailed example: £300,000 saved, £480,000 in additional funding identified, zero GDPR incidents. Council engagements are built to be procurement-compliant from day one. That means data protection impact assessments, PSED alignment, and FOI considerations are dealt with as part of delivery, not bolted on at sign-off.

What makes AI-Si.com different from Big 4 consultancies?

The main difference is what happens after the strategy is written. Big 4 engagements typically conclude at that point, with junior consultants handling delivery. I stay through implementation personally, building working prototypes in your meetings rather than after them, managing the vendor relationship, and reporting outcomes to the board directly. Big 4 rates for that level of involvement start at £2,000 per day per consultant. My full fractional engagement starts at £8,500 per month.

How do you ensure AI implementations are secure and compliant?

Every engagement starts with a data quality and governance audit before any AI tool is selected or deployed. That is not a compliance formality: it is where most implementations fail. Prompt injection testing and data minimisation are built into delivery from week one, not treated as a sign-off exercise. Simon Steggles has held data protection responsibility at board level. ISO 42001 alignment and vendor contract review for data training rights are included in every governance engagement.

Can you help identify new funding opportunities through AI?

Yes. The Midlands council case study is the clearest example: £480,000 in additional grant funding the council was entitled to but had not been claiming, identified through AI-assisted analysis of the funding landscape. A West Midlands charity secured £220,000 in additional funding through the same approach. It works because AI can map a funding landscape in hours that would take a human analyst weeks, but only when the underlying data is in good enough shape to work with.

Do you provide staff AI training?

Yes. The training is built around your actual workflows, not a generic AI literacy curriculum. Executives get a different session to operational teams, and I run a structured AI champion programme for the people who'll carry this forward inside the organisation. We cover prompt engineering, what your staff can and can't share with AI tools under UK GDPR, and how to identify and report problems. Staff are already using AI whether a policy exists or not. The training means that use is documented and under control.

Public SectorAI Readiness

AI Readiness for Public Sector: Where Councils Actually Stand in 2026

5 October 2026Last reviewed 5 October 20265 min readBy Simon Steggles· Fractional AI Director Birmingham, UK

Who this is for:Chief executives, monitoring officers, digital leads and cabinet members at UK councils who need an honest view of their AI readiness.

TL;DR

UK councils are not equally ready for AI. A 2026 study of 208 councils found a mixed picture, and fresh research says deployment is outpacing governance. If you lead a council, you need to know which side of that gap you sit on.

Key takeaways

AI readiness across UK councils is uneven. The 2026 study of 208 councils found some running live services and others still working on digital foundations.
Council size does not decide readiness. Leadership priorities, legacy systems and the pace of guidance do.
Research published in August 2026 warns that councils are deploying AI faster than they are building the governance to match.
Failures seen in practice came from procurement and data handling, not from the algorithms.
Start with an honest readiness check on accountability, data, skills and supplier controls before you scale anything.

A study of 208 UK councils, published in March 2026 by Heriot-Watt University and GoLLM, found a mixed picture of AI readiness. Some councils are running live AI services. Others are still fixing basic data and legacy systems.

Your council is somewhere on that spread. This article shows how to work out where, and what to fix first.

What the 2026 research shows

The Heriot-Watt University and GoLLM study covered 208 councils across England, Scotland, Wales and Northern Ireland over 18 months. It reported a mixed picture. Some councils are advancing quickly. Others remain at an early stage of digital development.

The pattern differs by nation. Scotland benefits from coordinated national approaches and university partnerships. England shows the widest gap, with advanced councils sitting next to those at the earliest stage. Wales is focused on data and digital foundations, with cautious pilots of chatbots and AI scribes. Northern Ireland is held back by funding pressure and limited internal capacity.

The researchers say size alone does not decide readiness. Leadership priorities, legacy systems and the pace of guidance shape the variation. Leadership ambition, governance discipline and data capability separate the front-runners from the rest. You can change all three.

What councils are already doing

The study lists real use cases. Fife and Glasgow City use AI to help sort waste and recycling. Surrey County uses automated pothole detection. Bridgend County Borough runs AI-powered resident chatbots. Belfast City Council uses generative AI to support communications.

These are narrow, defined tasks with a clear owner and a measurable result. That is the pattern to copy. None of them started with a council-wide AI programme.

The governance gap

Research published by Resultsense in August 2026, covering five countries, concludes that councils are deploying AI faster than the governance needed to make that deployment responsible. That matches what you will find if you look inside most councils.

The same research points to two UK examples of governance failure. Angus Council spent £240,000 on an AI procurement. North Lanarkshire had a data handling failure. The research treats both as governance failures, not algorithm problems. The tool did not fail. The controls around it did.

It also found that trust shaped how risk was perceived in every jurisdiction studied, ahead of technical performance. If residents and staff do not trust how you use AI, accuracy figures will not rescue you.

Six checks to run in your council

Run these checks before you approve another AI project. Each one maps to a priority the August 2026 research identifies.

Accountability: name one officer who owns each AI system and answers for it.
Capability: confirm that leaders, not only IT, understand what they are approving.
Data and technical safeguards: check where resident data goes and who can access it.
Transparency: give residents a route to a human review of any AI-assisted decision.
Community input: ask the people affected before you launch, not after.
Workforce: train staff to work alongside AI so it supports their roles.

What to do now

Take four actions this month. First, list every AI tool in use in your council, including free tools staff use without approval. Second, name an owner for each one. Third, review the contract and data terms for any AI procurement above your spending threshold before you renew it. Fourth, run a structured readiness assessment and record the result.

Do not wait for perfect governance. Do not scale without basic governance either. Pick one narrow use case, put an owner and a review route around it, and measure the result. Use the AI Readiness and Governance Framework for UK Public Sector Organisations on this site to structure the assessment.

About the author

Simon Steggles - Fractional AI Director

Simon helps UK SMEs and councils put AI to work safely. Royal Navy 1984–90 (Cat 3 PV at the time, now superseded by DV); current NPPV3 Police vetting for public-sector work; ISACA AI Governance certified. Based in Birmingham. £300K+ recovered for councils, 43% cost reduction in manufacturing, zero data-protection incidents across every engagement.

More about Simon

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Use this framework next

AI Readiness and Governance Framework for UK Public Sector Organisations

A twelve-part AI readiness and governance framework for UK public sector organisations covering strategy, data, procurement, compliance and oversight.

Open framework

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