Artificial intelligence is everywhere — in software, underwriting models, maintenance diagnostics, and even recruiting. But for transportation companies, the question isn’t whether or not to use AI, but rather how to use it in a way that reduces risk, enhances safety outcomes, and boosts operational efficiency.
Right now, too many fleets are chasing shiny objects: vendor dashboards claiming “AI-powered insights,” safety alerts that overwhelm without context, or predictive analytics that don’t connect back to meaningful action. The result is tech fatigue, confused users, and diluted ROI. AI is only as valuable as the decisions it enables — and how well those decisions are executed in the field.
Here’s what’s working and what isn’t.
Vendors like Netradyne, Samsara, and others are getting closer to true behavior prediction. But unless predictive driver scoring is integrated into performance management — with measurable coaching goals, driver incentives, and real consequences — it’s just data with no actionable use.
Automating incident reporting, triaging severity, and initiating claims workflows are examples of real ROI, especially in reducing litigation tail risk and compressing time-to-resolution. Fleets using AI to accelerate First Notice of Loss (FNOL) processes are not only saving money, they’re strengthening their legal defensibility.
Machine learning models that track component failure based on route, terrain, and climate are revolutionizing preventive maintenance. This is a game changer for uptime, repair costs, and avoiding on-road breakdowns that could trigger late deliveries, or worse, roadside crashes.
Insights buried in a portal that no one opens don’t reduce risk. You need embedded intelligence, pushed directly into workflows, that alerts dispatch in real time, nudges safety managers on priority interventions, and aligns with KPI dashboards.
Drivers don’t want to be managed by a robot. AI-based coaching only works when it’s humanized and tied to outcomes drivers care about, such as bonuses, home time, or career progression. Fleets that blast drivers with alerts without context are undermining morale and missing the point.
AI should simplify, not complicate. It should empower managers to act faster, give drivers tools to succeed, and drive measurable safety and cost outcomes. If your AI investment isn’t creating faster decisions, reduced claims, or happier drivers, it’s time to rethink the strategy, not just the software.
