09/10/2025 | News release | Distributed by Public on 09/10/2025 00:02
If you're involved in driver safety management there's a high chance that one of the most challenging aspects of your job is driver engagement. I've had many conversations with risk and safety managers who've shared ongoing attempts to change the mindset of the driver.
Many people in such roles believe they've explored all the different options in terms of driver technology and are left frustrated when they struggle to engage drivers in their safety programs. But, with developments in technology - such as AI - that uncover deeper driver risk insights than ever before, does driver engagement become easier?
Studies show that most drivers, whether professionals or private individuals, genuinely believe they are safer and more skilled than average - despite many admitting to taking risks on the road. This means that drivers often overestimate their abilities behind the wheel.
In a professional setting, this belief is often magnified. People who drive for work often see themselves as experienced, capable, and already operating at a high level. Feedback that challenges this view, especially when it's focused solely on errors, can be met with resistance or defensiveness. Traditional coaching methods that emphasize what went wrong can fail to resonate because they don't align with the driver's self-beliefs.
AI offers a more balanced view of driving behavior. Unlike traditional methods that only flag rule violations or predefined events, AI-powered solutions can analyze the full spectrum of behaviors, both positive and negative. And it's not just significant behaviors, but all the small decisions that contribute to safe trip outcomes.
By highlighting what drivers are doing right as well as where there is room for improvement, AI fosters more constructive conversations. It removes subjectivity from feedback and gives drivers real-time insights based on their personalized driving patterns over time. This balanced approach helps drivers to feel seen and understood, not just criticized.
For AI-driven safety tools to truly shift mindsets, drivers must trust the insights they receive. Transparency in how data is collected, analyzed, and used is crucial. Drivers want to know: Is this fair? Is this accurate? Will it be used against me?
Organizations that implement AI solutions successfully are those that involve drivers from the outset. They clearly communicate the goals (e.g. supporting safer driving, reducing fatigue and stress, improving well-being), and encourage drivers to engage with their data themselves. When AI is seen as a coach, not a critic (or worse, a surveillance tool), drivers are more likely to accept the insights and even seek them out proactively.
One of the most powerful levers for changing behavior is positive reinforcement. AI enables personalized, data-driven recognition programs that reward drivers for consistently safe behaviors. This could be through league tables, monthly awards, or even simple messages of appreciation.
Importantly, recognition should be designed to be meaningful for drivers. It's not just about being the "best" driver but about showing continuous improvement, maintaining good habits, or helping peers. When drivers see their efforts acknowledged, they're more likely to stay engaged and strive for even better performance.
While AI alone doesn't prevent crashes, it contributes significantly by creating a culture of continuous awareness and accountability. When drivers are more engaged, informed, and motivated, risk-reducing behaviors become second nature.
Real-world data shows that fleets using AI-based driver behavior analysis often see measurable improvements, including fewer crashes, claims and costs. But more than that, they witness higher engagement from drivers, which ultimately helps to shift mindsets and sustain improvements over time.
Step up driver engagement in your organization. Schedule a demo of our solutions today.