Leading smart LGR – how to harness AI in Local Government Reorganisation

In this final part of the three-part series on AI and Local Government Reorganisation (LGR), Ross Murray explores the need for smart leadership that harnesses modern technology to support LGR.

It’s often said that technology projects succeed or fail based on the quality of leadership rather than the technology itself. This feels particularly true in the case of AI and LGR. Combining multiple district councils into a single unitary authority demands a change in management and culture which goes far beyond a new IT project.

In parts one and two of this series, I’ve argued for a pragmatic approach to AI within the context of LGR. This involves seeing AI as an important and helpful tool, which leaders should not forget about, while also avoiding seeing it as a magical cure for all challenges. AI will become more useful in the future, and therefore the discussion should also consider how to build the right foundations so that new unitaries are in a position where they can effectively use it.

The decisions senior leaders make today will dictate whether these tools actually help or just get in the way. In the remainder of this article, five practical areas leaders need to focus on are highlighted to support this decision making.

1. Lead from the front and own the AI agenda

AI is too important to leave entirely to your IT team or digital enthusiasts; it needs to be understood and steered by senior management. However, too few councils have the processes in place to maximise its use in a safe way. Last summer, the LGA found that only 38%of councils had a designated Senior Responsible Owner (SRO) for AI, and just 41% had an explicit AI governance policy. From my own conversations, even fewer councils have an AI strategy in place and it is rare for someone at the executive level to be directly accountable for how the technology is used. 

To make LGR a success, leaders need to drive the conversation. This doesn’t mean that everyone needs to be a technical expert (although some access to tech expertise is important). There is a need for someone to set clear goals, ask the hard questions about data and ethics, and make sure projects align with the council’s corporate plan. If leadership doesn't own the agenda, AI projects will remain fragmented and are less likely to deliver real value. 

2. Nail the basics

It may not sound glamorous, but the first job for any leader looking to use AI in LGR is to get the digital basics right. An advanced chatbot or predictive model is useless if your data is inaccurate or your databases cannot talk to each other. The MHCLG’s LGR Digital & Cyber Playbook (2026) advises setting a “clear, achievable baseline… positioning the organisation for longer-term transformation”.

In practice, that means treating Vesting Day as the starting point for a minimum viable council. The core operations must be safe, legal, and functional. There should also be a transition plan that maps out the different legacy systems, datasets, and software contracts across the merging councils to flag immediate risks, such as an important software contract expiring mid-merger. Clean data and secure infrastructure reduce the risks of a crisis and will help make future AI tools much more effective.

3. Invest in people and culture

The best software will fail if your staff do not trust it. Mergers are already disruptive, and introducing AI can cause extra anxiety about job security if it isn't handled openly. Leaders need to show staff that AI is there to support them, not replace them. 

Examples with real impact help to change mindsets. One of these is Lancashire County Council's work with Microsoft to automate the drafting and formatting of social care reporting that previously took up to two days to complete can now be produced in around three to four hours, releasing substantial staff capacity and reducing the equivalent workload of two full-time social workers each month. The result has been more time for direct engagement with residents, more consistent documentation, and the potential to save over 200,000 staff hours annually across social care and education services.

As mentioned in the second part of this series, skills is one of the biggest barriers to AI adoption across local authorities. Senior leaders should allocate resources for training and upskilling to ensure that the workforce is ready to make use of new tools as they become available.

4. Set the goverance and ethics guardrails early

The public expects councils to act ethically and transparently. This extends to their use of AI. If decisions start being influenced by AI, there needs to be clear rules from the start. New unitaries should ensure they have a straightforward AI policy or ethical guidelines in place early, as well as the appropriate governance arrangements.

The cost of getting this wrong is high. If an algorithm is deployed without human oversight and harms residents, it can spark profound legal challenges and public backlash, much like fraud detection tools which have been scrapped abroad following public outcry. Maintaining public trust should be non-negotiable, which might sometimes mean holding back on using AI in sensitive areas until you’re confident in its reliability and fairness.

5. Be strategic and focus on what matters

To get the most from AI, leaders need to acknowledge that everything can’t change at once, especially during a merger. There needs to be priorities and phasing of AI initiatives which matches the stages of reorganisation:  

• Short-term (0-2 years): Focus on simple wins that ease the immediate transition. This could mean a single website chatbot to give residents a consistent experience from day one, or using basic automation to combine straightforward back-office tasks like council tax billing across the old boundaries

• Medium term (3-5 years): Once the databases are stable and properly integrated, start using more advanced analytics and predictive models in high-impact areas like adult social care or housing.

• Longer term (5+ years): Explore more complex transformations, like digital twins to simulate policy changes, but only when your data ecosystem and talent base are ready.

  
  

This phased approach prevents overload and aligns with MHCLG’s advice of having a “five-year transformation roadmap” that is communicated clearly.

Leadership will make the difference

Leaders need to take accountability for the AI agenda, get the underlying data and cybersecurity sorted, and set clear ethical boundaries. Leaders who approach this shift deliberately will build smarter, more financially resilient councils. Those who ignore the foundations risk ending up with an organisation that is larger, more expensive, and harder to manage. 

At Mutual Ventures, we combine deep public sector expertise with practical AI transformation insights to support leaders to build resilient, future-ready councils. Schedule a meeting with Ross and Yannick today to consider where you are on your transformation journey.