In today’s unpredictable economic landscape, transportation and logistics leaders are under pressure to deliver faster, smarter, and more sustainably, often with fewer resources and tighter margins. From fluctuating demand and rising fuel costs to labor shortages and extreme weather events, the challenges are mounting. Yet amid this volatility, one thing remains clear: agility is no longer a luxury; it’s a necessity.
But agility doesn’t have to necessitate a full-scale supply chain overhaul. Instead, it demands smarter use of the data already flowing through logistics networks. By strategically applying AI and cloud-based data management, companies can unlock efficiencies, improve visibility and build resilience without reinventing the wheel.
Here are four practical strategies the transportation industry can employ, using data and AI, to ride out uncertainty and emerge stronger.
1. Be proactive with your AI strategy
AI is no longer a futuristic concept; it’s a practical tool for solving real-world logistics problems. But not all AI investments are created equal. The most successful organizations apply AI strategically, targeting areas where it can deliver immediate impact.
For example, predictive routing powered by AI and real-time location data can help logistics providers avoid traffic delays, reduce fuel consumption, and improve delivery accuracy. Similarly, dynamic ETA calculations, based on live traffic, weather, and historical patterns, can enhance customer satisfaction and reduce missed delivery windows.
Another emerging use case is the rollout of Agentic AI assistants in commercial vehicles. These digital agents leverage small language models (SLMs) in vehicle to deliver near real time natural language-powered, location-aware guidance. The SLM can also leverage connected capabilities of cloud-based large language models (LLMs) and other agents. Commercial drivers can use AI assistants to optimize routes based on time or cost constraints and quickly adapt to changing road conditions – all through natural language, helping drivers stay focused on the road ahead and improving safety.
2. Buy vs. build
In times of uncertainty, building custom solutions from scratch can be risky, expensive and slow. Instead, logistics leaders should look towards existing platforms and partnerships that offer proven capabilities and faster time-to-value.
For example, when a steel company approached a location-sharing technology provider with a navigation optimization problem, the provider tapped into a combination of location services and cloud infrastructure to transform the disorganized industrial space into a streamlined hub. The solution resulted in a web-based turn-by-turn navigation solution uniquely built for heavy industry yards.
The decision to collaborate and integrate rather than build on its own significantly reduced the project complexity, accelerated planning, minimized inefficiencies and ultimately, improved the customer’s service reliability.
This real-world example demonstrates how strategic integration can be smarter, more scalable and better aligned with business continuity goals, especially when speed and precision are critical.
3. Find cost savings through efficiency gains
When budgets are tight, efficiency becomes a strategic imperative. Fortunately, AI and location intelligence offer powerful levers for reducing operational costs.
Take the last mile, for example. The last mile – and more specifically, the last meter – is the most complex and costly part of logistics. Inaccurate, missing or unclear delivery addresses and access information can be a massive cost drain on organizations, wasting fuel, time and trust. Precise and accurate data, dynamic mapping and real-time visibility help drivers navigate complex urban environments, reducing costs and improving the customer experience.
Predictive analytics can also help logistics teams anticipate disruptions and reallocate resources proactively. These efficiency gains reduce costs while improving service reliability and accuracy – crucial to customer satisfaction and differentiation in a competitive market.
4. Improve supply chain visibility
Visibility remains one of the most elusive goals in supply chain management. A 2024 study found that only 68% of U.S. companies believe they’re making progress toward achieving real-time supply chain visibility, and fewer than a quarter feel they’ve made significant strides.
The challenge lies in fragmented data, siloed systems and legacy infrastructure. But with the right systems that can bring siloed data and insights together with AI for a single source of truth, end-to-end visibility is within reach.
Real-time tracking of assets, vehicles and shipments - combined with centralized data platforms - can help logistics providers respond to disruptions faster and plan more effectively. Federated data systems, which allow companies to share and analyze data across partners without compromising security, may be beneficial in breaking down silos and improving collaboration.
Improved visibility not only helps companies respond to disruptions faster, but it also enables better forecasting, inventory management, customer communication and decision making. In short, it’s a cornerstone of resilience.
Resilience without disruption
The transportation and logistics sector is no stranger to change. In today’s environment, resilience requires more than reactive firefighting; it demands proactive, data-driven strategies.
By investing in targeted AI applications, leveraging strategic partnerships, driving efficiency and improving visibility, logistics leaders can build supply chains that are agile, cost-effective and future-ready.
Because in times of uncertainty, the smartest move isn’t to start from scratch; it’s to make better use of what you already have.
