One of the most rapidly advancing areas in fleet management is the powerful combination of connected car data and artificial intelligence. Through connected fleet solutions, vehicles continuously generate data on everything from engine performance, energy and fuel management to driver behaviour, safety and vehicle location. But the real value of connected car data lies in how it is interpreted and applied. When combined with intelligent software, this can support a wider range of operational improvements – from automated mileage to predictive maintenance and energy efficiency and route optimisation. AI analyses patterns in connected car data to identify early breakdown warning signs, recommend actions for upkeep, and even schedule servicing automatically. This marks a shift from reactive problem-solving to proactive, data-led decision-making – and tools such as Alphabet Connected Fleet empower this sustainable optimisation. As integration with enterprise systems and digital platforms grows, the collaboration between connected car data and AI is helping fleets become more efficient, reliable, and better aligned with long-term road safety & sustainability goals.
How can fleet managers move beyond passive monitoring to actively use connected car data for measurable sustainability and CO2 reduction amid growing regulatory and stakeholder pressure?
At Geotab, we’ve seen that the transition from basic telematics to trusted data and fleet intelligence is where the real transformation happens. It’s not just about more data, it’s about making that data useful. To move beyond passive monitoring, fleet managers are integrating trusted data into their core decision-making processes. For example, instead of just managing fuel consumption, we can use connected car data to implement predictive models to help optimise routes, match the right vehicle to the right job, and flag maintenance needs before they become problems. By leveraging AI to analyse patterns, managers can proactively support vehicle performance and health. This kind of efficiency is what actually moves the needle on emissions and costs and helps meet regulatory requirements and sustainability goals. To support this further, our Geotab CSRD report is also certified by TÜV - enables companies to accurately measure their fleet’s environmental impact, establish a baseline, and track improvement over time using Connected Fleet data.
What strategies can businesses use to balance the benefits of data-driven insights with respecting driver privacy and building a culture of trust?
The key strategy is transparency and clear communication. Businesses should be explicit about what data is being processed and, more importantly, why: focusing on safety and efficiency. Building a culture of trust means involving drivers in the process, perhaps by using the data to reward safe and efficient driving rather than just flag problems. It’s about shifting the mindset from ‘tracking’ to ‘protection’. There are so many serious injuries and fatalities on our roads today that the public and private sectors need to come together to ensure we are leveraging data and AI for good, with privacy by design built in.
What underlying factors have made data overload, system integration, and driver resistance persistent challenges in connected car data adoption despite technological advances?
The primary challenge is often the lack of education and what a unified platform can help with: to distil vast amounts of data from different vehicles and brands into actionable intelligence. Without intelligent software and AI to interpret the data, managers are simply overwhelmed by “data overload”. Furthermore, many fleets struggle with legacy systems that don’t communicate well with new technology, making integration difficult. The challenge is often a ‘siloed’ approach to data. To overcome integration challenges, businesses need to treat connected car data not as a standalone fleet tool, but as a vital part of their broader operations and enterprise resource planning (ERP) strategy. Finally, driver hesitation often comes from not yet seeing the direct benefits, like increased safety, less paperwork, or faster support in an emergency. Once those benefits become real, the conversation shifts.
Looking ahead, we see a future where AI agents from partners like Geotab and Alphabet communicate seamlessly - sharing insights on driver wellbeing, passenger safety and vehicle health, and feeding that intelligence directly into enterprise systems to enable decision-making in near real time.
In your experience, what KPIs or metrics are most underutilised in connected car data, and how can they unlock hidden value for fleets?
Throughout my time working with diverse fleets, I’ve observed that predictive maintenance indicators and “idling impact” metrics are often underutilised. While most focus on basic fuel usage, understanding patterns like idling time and component wear can extend vehicle lifespan and significantly cut operational costs. These insights are readily available through standard fleet intelligence tools, requiring no complex setup. By shifting from reactive to proactive maintenance through near real-time diagnostics, fleets can avoid costly downtime and improve overall reliability.
As vehicle tracking expands beyond location to diagnostics and driver behaviour, how should fleet managers decide to keep, upgrade, or replace legacy trackers?
Fleet managers should evaluate their current needs versus what is available in the market. Today, there are organisations like Geotab that have agreements across the OEM landscape that can seamlessly deliver telematics data into a fleet’s environment. That data can be harmonised, but we have to take into account that not all OEMs are on the same curve in the software-defined car lifecycle. Basic solutions are available today, but companies in last mile delivery may still benefit from supplementing with advanced telematics hardware. That hardware should support advanced AI and integration with modern digital platforms. If a legacy tracker only provides basic location data, it acts as a bottleneck to achieving the proactive, data-led decision-making that tools like Alphabet Connected Fleet enable. The decision to upgrade should come down to whether one needs deeper diagnostics and richer data to improve efficiency long-term and meet modern sustainability goals. Ultimately, moving to connected fleets isn’t just a tech stack upgrade: it’s a strategic step toward running a safer, more sustainable and efficient operation.