In part two of our conversation with Nauto CEO Stefan Heck, we dig into what municipalities can do to increase transparency and trust in the use of AI tools, and how to initiate the deployment of these systems.

This interview has been edited for length and clarity.

Q: What safeguards are necessary to ensure responsible use of driver data in government fleets?

Heck: Ensuring responsible use of driver data starts with clear data governance and privacy-by-design.

Agencies should define what data is collected, what is processed in real time versus stored, who has access to it, and how long it is retained. Limiting data capture to meaningful safety events, rather than to continuous recording, is a key safeguard.

Q: What best practices help agencies introduce this technology while maintaining workforce trust and morale?

Heck: The most effective approach is to lead with transparency and clearly communicate the technology's purpose: to support safety and protect drivers.

Agencies should explain how the system works, what data is and is not recorded, and how it will be used to support drivers, with recording and retention limited to exoneration and coaching purposes. Emphasizing privacy by design and the absence of continuous recording is critical to building trust.

In addition, involving drivers early, providing training, and positioning the system as a safety tool that helps prevent incidents and even exonerate drivers in the event of a claim can significantly improve acceptance.

When technology is accurate, non-intrusive, and clearly aligned with driver safety, agencies can maintain strong workforce trust and morale while improving outcomes.

Q: How can agencies communicate the use of AI safety systems to the public in a way that builds trust?

Heck: Agencies should communicate AI safety systems to the public by focusing on outcomes, transparency, and purpose. The message should be simple: these systems are designed to make roads safer for everyone, including pedestrians, cyclists, and other drivers.

It is also important to clearly explain how the technology works, emphasizing that it is privacy-conscious, does not rely on continuous recording, and is used only to identify and prevent meaningful safety risks.

For the public, it’s also critical to have a privacy policy that spells out whether and when recording is happening, whether personal information (e.g., pedestrians' faces) is blurred or retained, and how long data is retained.

Q: What early data exists on AI’s effectiveness in reducing collisions in government fleets?

Heck: Early data show that AI has a meaningful impact in reducing collisions, including in public-sector and mixed-fleet environments.

Across the industry, fleets using AI-powered safety systems are seeing 20 to 35% reductions in incident rates within the first few months, with continued improvement over time, with the best fleets reaching 70-80% reductions in collision losses.

Q:What role should federal, state, or local governments play in accelerating AI adoption to reduce distracted driving nationwide? 

Federal, state, and local governments play a critical role in accelerating AI adoption by setting clear safety standards, including requiring driver distraction and drowsiness detection systems and pedestrian collision avoidance systems, as the EU requires as of 2025.

The U.S. is behind and has close to double the fatalities as a result. Governments can also help by providing funding and leading by example. At the federal level, this includes supporting programs and incentives that encourage the adoption of additional, proven safety technologies, or using incentives to phase in technologies that become cheaper as they scale, so they can then be mandated universally once costs come down.

State and local agencies can drive impact by integrating AI into their own fleets and demonstrating measurable safety improvements.

Additionally, governments can help establish guidelines around privacy, data use, and responsible AI deployment, which builds trust among drivers and the public.

By aligning policy, funding, and implementation, governments can accelerate adoption at scale and make meaningful progress toward reducing distracted driving nationwide.

Q: How can agencies use AI insights to improve accountability without creating a punitive culture?

Heck: Agencies can improve accountability by using AI insights to prioritize coaching and prevention over punishment.

The key is to position the system as a tool that helps drivers succeed, not one that penalizes them. By prioritizing in-the-moment coaching and highlighting improvements in positive behavior, agencies can reinforce safe driving habits without creating fear or resistance.

Q: How can smaller municipalities with limited resources successfully adopt these solutions?

Heck: Smaller municipalities can successfully adopt AI safety solutions by starting with a focused deployment and scaling over time or working through a leasing or fleet management company like Wheels.

Rather than a large upfront investment, many platforms are designed to be deployed quickly and cost-effectively, allowing agencies to begin with a subset of vehicles and demonstrate impact early.