Bernhard Schmaldienst unpacks four myths about AI in transportation and logistics
AI’s transformative influence on the transportation and logistics industry is significant, however, there are still many misconceptions that need addressing. This is common for new technology. Change can be challenging, and while it is an incredible tool that has helped businesses streamline operations, cut costs, and improve efficiency, it will take time before all AI myths are debunked.
Time is running out, businesses need to get to work so we can speed the process up. Myths and misinformation about AI lead to resistance, slowing the adoption process down, meaning the supply chain industry will lag behind and miss out on the real benefits AI has to offer. And with the industry grappling with mounting pressures, such as ever-changing fuel prices, increasing customer expectations and ominous sustainability targets, the need for accurate, data-driven decision-making has never been greater. Adopting AI empowers businesses to achieve greater operational efficiency and strengthen their competitive position in a rapidly evolving market. So, let’s tackle four common myths and set the record straight with real-world insights and evidence.
Myth 1: AI-powered transportation is expensive and doesn’t deliver measurable savings
The reality: Like any tool, AI-powered transportation solutions have a cost to start with, but they deliver rapid returns, often within weeks. By leaning on automation and data-driven decision-making, AI cuts costs and makes the whole operation significantly more efficient.
The proof: Companies using AI-driven freight procurement solutions have achieved measurable savings. AI-driven autonomous procurement tools integrate seamlessly with existing transport management systems, and for a leading FMCG customer, they have been proven to reduce freight costs by more than 10 percent while simultaneously cutting down on manual workloads by 80 percent. One global food and beverages company reported securing lower spot rates while reallocating team resources to higher-value tasks.
Myth 2: AI-powered transportation requires big internal changes
The reality: Quite the contrary. Over the past five years, the logistics and supply chain industry has seen a lot of changes, and AI has been a big part of that. Earlier-stage AI-powered solutions required time to adapt, though now they are designed to integrate seamlessly with existing systems for easy adoption.
The proof: Many businesses have implemented AI solutions without overhauling their existing processes. Autonomous procurement solutions, for example, can connect via APIs, facilitating quick adoption with minimal disruption. The “big internal change” in this instance would then be that the team spends less time on simple activities like accepting offers and more time on value-adding, strategic tasks. In other words, there is a degree of internal change – but it’s beneficial, not disruptive.
It is also important to note that the time it takes to implement AI into a business’s existing systems have shortened drastically. It no longer takes months of configuration and training. These short implementation times are vital for smaller and mid-sized companies who would previously assume AI adoption was reserved for enterprise-level organisations.
Myth 3: AI-powered transportation adds little value and can’t actively perform critical tasks
The reality: AI isn’t purely about automation anymore. It now actively improves decision-making, helping people optimise procurement, pricing, and carrier selection, resulting in better and faster decisions.
The proof: AI earned its place as an established tool in logistics. For instance, AI-driven procurement solutions identify the best transportation capacity at the most competitive rates, lowering cost and increasing efficiency. A logistics company using AI-powered tools saw a 7–12 percent reduction in freight expenses while increasing automation, letting their teams focus on important negotiations instead of day-to-day transactions.
As we move forward, expect to see AI move beyond tasks such as route optimisation and into the realm of autonomous decision-making. Advanced algorithms will analyse vast amounts of data, factoring in real-time conditions, driver availability, and cost fluctuations to optimise entire transportation networks. In fact, what seem as ad hoc delays, such as strikes or traffic jams, may be part of hidden patterns that are revealed when artificial intelligence models analyse data over time. This will also impact price negotiations. Instead of negotiating prices for each shipment individually with all the counterparts, companies with AI-powered procurement tools can process the negotiations autonomously.
This shift means pricing is no longer reactive or negotiated in silos. Instead, AI proactively manages pricing strategy within defined parameters, making instant, data-backed decisions at scale. It removes the guesswork and manual effort from negotiations entirely, aligning pricing with market conditions in real time and ensuring consistency across every transaction.
Predictive maintenance will also become more prevalent, with AI and machine learning algorithms analysing data from IoT sensors to anticipate equipment failures, minimising downtime and optimising maintenance schedules. Instead of relying on fixed service intervals, AI can determine the optimal time for maintenance based on real-world usage and performance data. This prevents costly breakdowns, extends asset lifespans, and reduces unnecessary servicing, delivering both environmental and financial benefits.
Myth 4: AI-powered transportation damages relationships with carrier partners
The reality: It’s the other way around. AI actually strengthens relationships with carriers by ensuring transparency, in-market pricing, and efficiency. It doesn’t replace human interactions – it strengthens them.
The proof: Many AI-powered procurement platforms provide carriers with instant visibility into available shipments and instant pricing. With features like “buy-it-now” options, carriers can accept shipments with confidence. One logistics leader noted that AI freed time up for the team to build stronger partnerships instead of being bogged down by manual negotiations and coordination activities.
Conclusion? AI is a strategic asset, not a liability
Companies in the transportation and logistics industry are under constant pressure to cut costs, improve efficiency, and adapt to shifting market dynamics. AI-powered solutions are not just another tech trend, they’re a tried and tested approach. Companies that embrace AI are already seeing considerable cost savings, streamlined operations, and strengthened relationships with carriers and partners.
Rather than fearing AI, businesses should see it as a tool that complements human expertise, automates routine tasks, and empowers teams to focus on strategic growth.
The key takeaway?
AI in transportation is all about helping people to work smarter, and achieve better results more efficiently. Beyond cost savings and productivity gains, AI also supports sustainability efforts. Optimised routing, fewer empty miles, and smarter capacity utilisation all contribute to lower emissions. This positions AI not just as a business enabler, but as a critical ally in helping the logistics industry meet environmental goals and regulatory requirements.
Bernhard Schmaldienst is the Senior Director Transport Execution and Visibility Products at Transporeon
