Adopting AI in Local Government: A Comprehensive Framework for Councils

Both the private and public sectors are seeing a widespread adoption of AI tools. Artificial intelligence has the potential to create immense value across a range of council functions, from taking meeting notes and synthesising data to automating functions at scale and predictive maintenance. At CivicRisk Mutual, we’ve already seen member councils produce profound value with the use of AI.

However, when a business or council introduces AI without a strong governance structure and data integration, it opens the door to critical risks. Vulnerabilities are exacerbated by the increased attack surface AI introduces, alongside the proliferation of automated attacks.

In this guide, we explore:

• Key use cases for AI in the public sector.
• Critical risks resulting from AI.
• Governance and policy best practices.
• Implementation and post-deployment risk management.

We’ll also cover how to align your AI implementation with national frameworks to guide the safe adoption and use of AI.

Key Use Cases for AI in Local Government

Local councils and municipalities leverage artificial intelligence across multiple areas to better serve their communities. Here are some of the ways AI tools are already taking hold in the public sector:

Internal Administration

Large language models (LLMs) can automatically transcribe council meetings, summarise action items and draft public-facing reports or correspondence. These features save teams time, although any AI-generated text requires thorough review to catch hallucinations and human discernment to add expertise before it reaches publication.

Citizen Services

AI-powered chatbots on municipal portals help field routine service requests and connect residents directly to the right departments. Portugal has implemented an AI virtual assistant to help local residents access information about 2,300 public services in 12 languages via its gov.pt portal.

Closer to home, one of our members, Cumberland Council, offers residents DAISY (Development Applicant Intelligence SYstem). This is an AI-powered chatbot to help users with development applications and related questions.

Public Works and Urban Planning

Using computer vision, regions can monitor traffic patterns, optimise waste collection routes and detect issues like potholes or structural wear early. Blacktown City Council has already delivered the Brains in Drains project, which leverages AI to prevent stormwater flooding. Shellharbour Council also developed an AI-Assisted Road and Pathway Risk Management Program, pioneering AI-driven road inspections and accelerating defect detection and repair accuracy.  

Emergency Response

GeoAI is helping teams across the world rapidly assess damages and provide real-time intelligence for disaster recovery and crisis management. Following the 2024 Noto Peninsula Earthquake in Japan, AI tools also analysed social media and environmental data to deliver real-time insights to crisis management teams.

Social Services

Predictive analytics can help caseworkers identify vulnerable populations, help citizens access social support and intervene before health and social care issues reach a crisis point.

While the value of artificial intelligence spans the breadth and depth of public services, there have been clear examples of AI’s shortcomings in the space, too. For instance, the city of Rotterdam in the Netherlands implemented an AI program in 2017 to assess how likely welfare recipients were to commit fraud. After analysing the data, the system developed biases against a certain population, and the program was shut down following an external ethics review in 2021.

AI is not yet a perfect system. A lack of predictability stretches as far as the value these tools offer — and that lack of predictability can introduce critical risk into the public sector without sound, human-led AI governance and policies.

Risks of Using AI in Local Government

Of course, cybersecurity is already a growing risk for councils. AI is accelerating that risk, both by making cybercriminal activity more sophisticated and by introducing new potential gateways for data breaches.

This doesn’t mean governments should avoid using AI altogether. It means they should take an eyes-wide-open approach and implement solid AI governance frameworks and operational policies to manage these risks effectively.

Below are some of the key risks AI can introduce into council operations:

• Algorithmic bias: AI systems trained on historical data can reflect and reinforce existing inequities.
• Communication misalignment: Generative AI can frame messaging through its “persona,” which may not be appropriate for public sector messaging.
• Data privacy and breaches: There is an increased attack surface for breaches and misuse, as well as the risk of sensitive data leaks.
• Cyber risk acceleration: Phishing, social engineering and ransomware attacks are faster, cheaper and harder to detect — and councils are known targets.
• Lack of transparency: Automated decisions made by AI systems can create accountability gaps and erode public trust.
• Over-reliance on automation: Removing human judgement from sensitive decisions risks outcomes that are technically correct but contextually wrong.
• Staff displacement and morale: Without clear internal communications from leadership, AI adoption can create anxiety among employees about job security.
• Governance lag: AI capabilities are evolving faster than the policy frameworks designed to regulate them.
• Inconsistent procurement: Without a centralised AI policy, different departments may adopt tools independently, creating fragmented risk profiles and data across the organisation.

What exacerbates these risks across the public and private sectors alike is the siloed use of AI tools by either teams or individuals to automate tasks in their workflows. This application is not inherently bad or wrong, but without effective guidelines and oversight, it can go south fast. 

Siloed, unmanaged use of AI tools introduces risks that fly under the radar, which is where solid AI governance and policies can guide fair, safe adoption.

AI Governance Best Practices

AI models have well-known flaws that can undermine the performance and effectiveness of AI-related activities. These flaws are manageable when systematic, consistent human oversight is integrated into the workflow. However, when human oversight is not consistent and thorough, or councils implement multi-agent AI teams, these defects can scale. They are:

• Hallucinations: When AI generates false, misleading or completely fabricated information to fulfil a request.
• Drift: The gradual degradation of an AI model’s performance over time because the real-world data or its operational environment has changed, making its original training data obsolete.
• Sprawl: The uncontrolled proliferation of AI tools, models, integrations and agents across an organisation, with no central oversight or governance.

The best and only way to keep AI processes from colouring outside the lines is to ensure you have a solid governance framework, a clear line of public accountability and supporting policies that provide guardrails for AI processes.

What To Include in Your AI Governance Frameworks

AI governance frameworks follow the full lifecycle of establishing, implementing, maintaining and continually improving AI tools within an organisation. Similar to a risk management plan, AI governance frameworks should include:

• A clear line of accountability: Establish an AI Governance Officer or committee to oversee procurement, usage, transparency and consistent monitoring.
• AI risk and impact assessments: Before deployment, identify potential risks in areas like privacy, bias, cybersecurity and public transparency, as well as a clear plan if anything goes awry.
• Fair use guidelines: Depending on the use case, tool and department, establish guidelines that clearly delineate appropriate and inappropriate AI use.
• Transparent AI registers: Create a centralised inventory documenting tools and usage parameters across departments, including generative AI and software integrations.
• Supply chain accountability: Thoroughly vet providers to ensure that privacy and data security align with the public interest.
• Incident management: Establish a clear pathway for staff and the public to report any AI safety concerns.
• Internal training and communication: Educate staff about the tools, fair usage expectations and the risks associated with AI tools through training and internal communications. Ensure there are communication channels for staff to raise challenges and feedback with leadership.

Implementation Frameworks To Reduce Risk

Adopting AI successfully relies on following a structured, phased strategy. Real-world implementation will be unique to each council, depending on the AI tools and use cases that add value to operations. There are, however, areas each council should consistently address as they build out their AI governance protocols and policies:

Data Governance

Before deploying AI, ensure clean, structured datasets and strict privacy and data protection frameworks are in place to handle sensitive information. Standardising datasets across the council can be a time-consuming process, but it supports centralised, council-wide integrations for AI-assisted public services and helps prevent both data and risk silos. 

Upskilling the Workforce

Effective adoption requires training employees to use AI tools with a risk-conscious mindset. That way, staff can focus on policy and complex, human-centric tasks. Communicating the specific human value employees add to AI processes helps teams understand their roles in AI-human hybrid workflows and can reinforce the message that AI is a supportive tool, not a replacement.

Phased Pilots

Rather than deploying systems universally, pilot tools in specific departments and scale them incrementally based on performance metrics and employee feedback. Any risks or challenges that arise during pilot phases will scale alongside adoption if they’re not addressed.

Consistent Monitoring

Ensure continuous monitoring of AI use within the council to encourage safe usage, assess privacy and security and identify emerging risks. Continue rolling out training and internal communications where necessary.

AI Adoption Enablers and Accelerators

If you’re looking to expand your AI adoption, below you’ll find a few foundations to ensure the process runs more smoothly.

• Leadership and governance: Senior council leadership can champion adoption and align cross-agency priorities to enable strong, coordinated delivery.
• An agile tech stack: Customised services require interoperable layers across identity, payments, data exchange, orchestration APIs and user interfaces. Each layer should be able to scale with demand while remaining flexible enough to operate across multiple use cases.
• Flexible acquisition: Procurement should prioritise software-driven services and evolving technologies to ensure the tech supporting AI use remains relevant as AI capabilities advance.
• Operational reforms: Rethink workflows to support new AI processes, data protection and tool onboarding.

Key National Frameworks To Guide AI Adoption

For further guidance on the safe implementation and governance of AI in council operations, national frameworks provide helpful additional information. They include:

• The Policy for the Responsible Use of AI in Government, which follows accountability, transparency, strategy and staff training.
• The National Framework for the Assurance of Artificial Intelligence in Government, set forth by the Data and Digital Ministers Meeting. This advises on the practical application of Australian AI Ethics Principles across Australian state and territory governments.
• ISO/IEC 42001:2023, which provides guidance for entities utilising AI-based products or services to ensure the responsible development and use of AI systems.

Each of these frameworks offers guidance on balancing the operational use of AI with public accountability and centralised governance within councils.

Safely Integrate AI Into Your Council Practices

Generative and agentic AI have the potential to provide immense value to the public sector. To translate that value for residents while protecting public trust, councils must be fully aware of the risks and lay the necessary foundations to govern and manage the use of AI tools.  

For more information about safely integrating AI into your council operations, reach out to CivicRisk Mutual to book a bespoke training session.