From AI Insight to Action in Municipal Energy Management

In brief

AI-driven energy analyses create value when the organization can act on them. Get concrete recommendations for management anchoring, organization, and resource prioritization, as well as a maturity model that helps municipalities choose their next steps.

Contents

Many municipalities have access to energy data and AI-based analyses that can highlight deviations and savings potentials. Nevertheless, there can be a long way from an insight on a screen to a change in a building's operation.

The path from data to action requires clear management anchoring, distinct roles, and resources to follow up. Based on experiences from five municipalities in the GreenInsight project, 4BC has compiled a series of recommendations in the Best Practice guide "From Data to Action". Here you will find the guide's most important points and inspiration to move forward in your own organization.

Management Must Set Direction and Follow Up

Energy management must have a clear place in the municipality's strategic governance. This requires political and administrative support, as well as a clear connection between energy goals, economy, and daily operations.

AI-driven analyses can support the work by highlighting deviations, potentials, and the effect of implemented initiatives. Management must also take responsibility for how this knowledge is used to prioritize and follow up.

Good starting points include:

- Linking energy goals to the municipality's climate plan or energy policy.

- Assigning clear management responsibility for goals, prioritization, and follow-up.

- Establishing fixed reporting routines that show consumption, initiatives, and results.

When energy work becomes a fixed part of the management dialogue, the foundation for sustaining efforts over time is strengthened.

Make Responsibilities and Collaboration Concrete

An analysis of abnormal energy consumption must have a clear recipient. It must be agreed upon who assesses the deviation, who investigates the conditions in the building, and who follows up on the chosen action.

Unclear roles and interfaces can make energy work person-dependent. Therefore, the collaboration between the energy team, technical services, and management should have fixed frameworks.

This includes, among other things, to:

- Define responsibility and mandate for the energy coordinator or the cross-functional energy team.

- Agree on workflows for alarms, operational tasks, and investment decisions.

- Create regular meetings and frameworks for knowledge sharing across buildings and disciplines.

AI analyses can provide a common overview. Clear agreements make it possible to use this overview in practice.

Allocate Time and Competencies for Action

Energy work needs to have a place in everyday life. Even relevant insights can remain unaddressed if the operations organization lacks time, competencies, or finances to follow up.

Automated analyses can reduce the manual analysis burden and support prioritization. At the same time, there must be employees who can understand the insights, investigate the causes, and implement changes.

Therefore, prioritize to:

- Allocate time for follow-up on energy data and concrete operational tasks.

- Strengthen competencies in data understanding, system usage, and operational optimization.

- Create a connection between energy goals and operational and investment budgets.

A common primary energy management system and training tailored to individual user groups can make the work more manageable. An annual cycle can help maintain energy reviews, follow-up, and reporting.

Choose the Next Step Based On Your Maturity

Municipalities have different organizational and professional prerequisites for using AI in energy management. The guide's maturity model describes three levels that can be used to discuss your starting point and prioritize the next steps.

1. Create Overview and Action

Gather an overview of energy consumption, identify clear deviations, and select a few buildings or facilities with a concrete need for action. Use the experiences to build competencies and organizational support.

2. Create Systematics and Impact

Integrate analyses into fixed workflows. Work with uniform prioritization, clear roles, and follow-up on initiatives, so that energy work becomes less person-dependent.

3. Create Strategic Management and Gains

Use the insights as a regular part of investment decisions, management dialogue, and political reporting. Systematically follow up on gains, and continuously adjust both processes and the use of AI.

The model is a dialogue tool. The same municipality can be at different levels across the organization. The next step must therefore fit both ambitions and capacity.

Turn the First Insight Into a Concrete Task

A practical place to start is to follow one insight all the way from analysis to follow-up. For example, choose a building with inexplicably high energy consumption outside of operating hours.

1. Define the problem. Describe the deviation and involve operations in investigating possible causes.

2. Assign responsibility. Agree on who investigates the conditions and decides the next steps.

3. Prioritize the action. Assess the expected effect in relation to time, finances, and competencies.

4. Agree on implementation. Make the task concrete and establish responsibility and timeframe for follow-up.

5. Follow up and share the experience. Investigate whether the change has had the expected effect and whether the solution is relevant elsewhere.

The process can also show where your workflows are effective and where clearer agreements or resources are needed.

Download the Best Practice Guide "From Data to Action"

The guide collects recommendations for implementing AI-driven resource optimization in municipal buildings. It includes both the three central areas of effort and the full maturity model, which can be used in dialogue between operations, the energy team, and management.

The guide was prepared by 4BC in February 2026 based on experiences from Ballerup, Rudersdal, Sorø, Rødovre, and Høje-Taastrup in the GreenInsight project. The project is supported by the Danish Agency for Digitisation.

Download the Best Practice Guide "From Data to Action" (PDF)