How to build a business case for AI adoption in local authorities

Artificial Intelligence (AI) is revolutionising industries, offering unparalleled opportunities for innovation, efficiency, and competitive advantage.

In our afternoon session at LGAi’s Unconference 2024, attendees to this session on ‘how to create a use case to explore AI capabilities within local authorities’ unanimously agreed that without a well-defined business case, AI projects lose momentum, focus, and funding, resulting in wasted time, resources, and missed opportunities. 

Attendees from various councils shared that tight budgets, procurement processes and a fear and misunderstanding of AI are holding LA’s back from harnessing its capabilities through new and existing software within their organisations.

This blog summarises our discussion with attendees from local councils and suppliers working closely with local authorities on digital projects.

We’ve also included a step-by-step guide on how you can build a successful business case drawing on the insights shared from successful projects in councils across the UK.

Contents

The importance of building a business case
Reasons for reluctance to adopt AI in local authorities
How to build a compelling business case
A step-by-step guide to creating a business case
KPIs, success metrics and measurables
Example KPIs
Conclusion

5 reasons why building a business case is important

Observing these principles is important because they lay the foundation for a well-organised, efficient, and successful project. Adhering to structured planning, clear accountability, strategic communication, stakeholder involvement, and measurable outcomes ensures that resources are used effectively and objectives are met. This approach minimises risks and uncertainties, promotes transparency and trust among stakeholders, and enhances decision-making.
Practising these principles is good business practice because it leads to better project outcomes, higher returns on investment, and sustained growth. It fosters a culture of responsibility and continuous improvement, ultimately contributing to the long-term success and competitiveness of the organisation by:

1. Clarifying the objectives and scope: A business case helps clearly define what the AI project aims to achieve. It sets the scope and outlines the value purpose and outcomes, ensuring all stakeholders are aligned and supportive of the project.
2. Securing funding and resources: Presenting a compelling business case, will be the difference between securing the necessary funding and support from stakeholders and a failure to launch. A detailed plan must justify the investment, showing the potential returns and benefits.
3. Mitigating risks: A well-thought-out business case identifies potential risks and challenges associated with the AI project. It includes strategies for mitigating these risks, ensuring the project has a higher chance of success.
4. Maintaining focus and momentum: With a clear business case, the project team remains focused on the end goals. It acts as a roadmap, guiding the project through various phases and helping maintain momentum even when challenges arise.
5. Demonstrating value: The business case showcases the value that AI will bring to the organisation. It includes key performance indicators (KPIs) and metrics to measure success, providing a clear understanding of how the project will impact the business.

Reasons for reluctance to adopt AI in local authorities

As we spoke about the appetite for AI within our various organisations, we also shared some factors we believed were contributing to hesitation around adopting AI. These challenges stem from fears, skill gaps, communication issues, policy immaturity, and operational hurdles. Understanding these reasons can provide insight into the reluctance and complexities involved in integrating AI into local governance. 

Here are some of the reasons we identified:

Fear of AI

• Employees’ fear of replacement by AI
• Fear of new technology
• Unions standing up for staff about fears of redundancy
• Losing the human element of decision-making

Skills and knowledge gaps

• Misunderstanding of AI, what it means and what it does
• Lack of understanding about the capabilities of AI
• Lack of skills within the organisation to properly use AI

Communication and Stakeholder Engagement

• Lack of communication with internal stakeholders about the value of new projects or software
• Bringing different departments on the journey
• Making sure all decision-makers and end users are aware or involved
• External communications and resident management about new projects and change

Policy and Governance

• The infancy of AI policies both internally, nationally, and globally
• Security fears
• The time it takes to review infosec processes

Implementation and Operational Challenges

• Understanding the intent of the product or project at the beginning
• Clearly defining value, purpose, and outcomes
• Lengthy procurement process and decision-making
• Maintaining momentum internally
• Onboarding staff onto new software

If you are considering using Large Language Models (LLMs) such as ChatGPT, Gemini and Co-pilot, read more on what the public sector needs to know about LLMs from our Lead Data Scientist, James Poulten.

How to build a compelling business case for AI adoption

When building a business case for AI and new software adoption, start with a structured implementation plan, meticulously outlining each step and assigning tasks to maintain clear accountability.

Developing a comprehensive internal and external communication strategy for stakeholders is key to engagement and momentum on a project. Actively involving stakeholders throughout the process will be crucial for their support and understanding. 

It’s important to consider that not everyone may be up to speed with the project, so provide context and go back to the purpose, values and outcomes set at the beginning of the project to ensure understanding. 

Every stakeholder will want to see the key performance indicators (KPIs) that will be measured to track progress and success. Not every stakeholder will care for the same KPIs, so tailor the KPIs and any ROI estimations to the audience (see a list of examples below).

“AI is too big conceptually; breaking it down into doing AI and then ROI for different levels of management and departments is essential.” – Anthony Fawkes, Director, Actually Data Analytics

These KPIs will provide a quantifiable way to demonstrate the impact and value of AI initiatives, ultimately proving the return on investment (ROI) and ensuring that the project delivers tangible benefits.

A step-by-step guide to creating a business case

1. Understand the business problem: Start by identifying the specific business problem that AI can solve. Engage with different departments to understand their pain points and how AI can address these issues.
2. Define clear objectives: Outline the primary objectives of the AI project. Whether it’s improving customer service, optimising operations, or enhancing decision-making, make sure the goals are clear and measurable.
3. Conduct a feasibility study: Assess the feasibility of the AI project by analysing technical requirements, data availability, and organisational readiness. This step helps in understanding the practical aspects of implementing AI.
4. Evaluate the ROI: Calculate the potential return on investment (ROI) by comparing the costs of implementing AI with the expected benefits. Include both tangible and intangible benefits to provide a comprehensive view.
5. Develop a detailed implementation plan: Create a step-by-step implementation plan that includes timelines, milestones, and responsible parties. This plan should outline the stages of the project from inception to deployment.
6. Identify risks and mitigation strategies: List potential risks associated with the AI project and develop strategies to mitigate these risks. This might include data privacy concerns, technical challenges, or resistance to change within the organisation.
7. Gain stakeholder buy-in: Present the business case to key stakeholders and decision-makers. Use data-driven insights and real-world examples to demonstrate the potential impact of AI on the business.
8. Measure and monitor progress: Establish KPIs to measure the success of the AI project. Regularly monitor progress and make adjustments as needed to ensure the project stays on track.

This is our suggested approach to building a case for AI projects, however, if you’d like to learn more highly recommend you watch this on-demand recording from Laura Burnett, our Delivery Director, on how to build digital services that deliver for citizens and the business case.

Why KPIs, success metrics and measurables are so important

A well-structured implementation plan with defined accountability, coupled with an emphasis on data governance and safety, lays the foundation for successful AI integration. Demonstrating efficiencies without job losses, enhancing productivity, and maintaining a high quality of service are crucial to gaining buy-in from employees and residents alike. Highlighting the financial impacts, such as cashable savings and reduced hiring costs, further strengthens the business case.

Moreover, AI promises to enhance employee performance and job satisfaction, driving overall resident happiness and helping local authorities hit their targets more effectively. The potential for AI to accelerate and scale operations while promoting sustainability makes it an invaluable tool for the future.

Example KPIs for a business case for AI in local authorities

Efficiency and performance

• Impact on productivity
• Impact on headcount
• Backlog reduction
• Contributions to targets
• Channel shift
• Employee engagement
• Job satisfaction
• Quality of service
• Resident satisfaction

Financial impact

• Cashable savings this year
• Turnover
• Hiring costs

Scalability

• Viability
• Cost
• Sustainability of the project long term

Information security

• Safety
• Data governance

Conclusion

Adopting AI within local authorities is not just a fleeting trend but a fundamental shift that will continue to grow and evolve. Building a robust business case for AI adoption is essential to ensure these projects gain the necessary momentum, focus, and funding.

Project managers must work hard to communicate the benefits and returns to each stakeholder while outlining a clear plan of communication, risk assessments, goals and measurables to overcome the barriers to AI adoption.

As AI continues to evolve, local authorities must remain proactive, ensuring that they are not left behind. By building a comprehensive business case, they can confidently embrace AI, reaping its numerous benefits and driving continuous improvement in their services. AI is here to stay, and with careful planning and strategic implementation, local authorities can harness its power to transform their operations and better serve their communities.

We’re committed to supporting each of our clients with building their business case for our software. If you’d like to see what we’re doing for housing teams, check out our products page.

Special thanks to Datnexa and Outcomes Matter for hosting LGAi Unconference.

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