Five Predictions from Trimble for the Coming Year

As we look ahead to the upcoming new year, we see new opportunities but also ongoing challenges. Economic uncertainty and geopolitical volatility persist, while technology advances at a rapid pace. Christopher Keating, Senior Vice President, Transportation and Logistics Segment at Trimble, highlights five predictions for the new year in his report.

By: Christopher Keating

(Westminster/Ulm) In this environment, adaptability has become the new competitive advantage. Those companies that combine human expertise, digital innovation, and operational resilience will lead the way in successfully shaping the next chapter of global logistics.

Here are five predictions for the coming year.

1. AI: From Hype to Data-Driven Collaboration

The industry’s relationship with AI is maturing. The focus has shifted from experimentation to actual implementation. The gap between small and medium-sized enterprises is narrowing as AI makes access to technology easier for all.

By 2026, AI will be integrated into mainstream applications such as predictive maintenance, network optimization, and dynamic pricing. Discussions about full autonomy are already taking place at the operational level and are no longer limited to IT discussions.

The term “AI as a colleague” is replacing “AI as a tool.” Companies are no longer asking whether AI can help. The standard question from logistics managers is now, “Can AI do this, and how quickly can it deliver results?” – not to eliminate human tasks, but to free people for higher-value work.

However, the biggest hurdle remains data quality. Data quality, a long-time favorite topic in the industry, is finally being recognized as the true enabler of automation. Economic pressure is forcing companies to face the reality: those who want autonomous AI must first invest in the data that drives it. Without clean data – where do we stand?

2. The Human Factor: The Challenge of Change

The driver shortage remains severe. Safety, comfort, and inclusion are at the forefront. However, the greater challenge for the workforce is change management itself. “We have someone who has been doing this job for 30 years, and I don’t know how he will handle it,” is a common objection from leaders evaluating the introduction of AI. A deeper integration of AI depends on employees accustomed to established processes embracing these fundamental changes.

Successful companies recognize the importance of appointing change ambassadors within their teams. These experienced employees can bridge the gap between old processes and new technologies, helping their colleagues navigate the transition with credibility and empathy.

The customer experience is evolving into a key differentiator. The “human plus AI” model proves essential for successful implementation. There are already practical examples: digital assistants that identify languages, translate communications, route inquiries, and report issues are already speeding up response times.

Customer expectations have risen sharply as they have become accustomed to the immediacy and simplicity of retail and banking. Where they once wanted notifications about issues, they now expect proactive solutions and autonomous actions.

Ultimately, technology is evolving rapidly, but companies must keep pace with their employees just as quickly. Investing in them is inseparable from digital transformation; it forms its foundation.

3. Sustainability and Intermodality: Progress Through Pragmatism

The shift to alternative fuels will continue. However, progress in the adoption of electric and low-emission heavy-duty vehicles will continue to be hampered by infrastructure gaps and economic factors. Nevertheless, there are certain segments where the transition is already occurring sooner: local delivery companies in parts of Europe are finding that electric vehicles are becoming increasingly cost-effective, creating opportunities in niches where the economics make sense. In the broader market, however, companies prioritize measures that simultaneously yield cost savings and sustainability gains: route optimization, tire pressure monitoring, digital documentation. In short: sustainability and profitability are now the same goal.

Meanwhile, intermodality is struggling with complexity. In road freight, three players are involved; in intermodal transport, there are at least seven. The obstacle? Once again, it’s the data. Sea, road, and air transport operate differently and have incompatible standards. AI could help bridge these gaps through smarter planning tools. In all regions, outdated infrastructure and ongoing maintenance, from European rail bottlenecks to roadworks in North America, continue to impact capacity and reliability.

4. Resilience and Volatility: Here to Stay

Geopolitical tensions and multipolarity will continue to have unpredictable impacts on supply chains. Even if tariff volatility may have peaked – or companies have learned to take protective measures against short-term fluctuations – structural uncertainty is likely to remain more permanent than temporary. Companies can benefit from joining flexible, data-driven networks that are truly ready to adapt.

The threat of cybersecurity is rapidly professionalizing. A larger global incident involving data leaks due to insecure AI usage seems inevitable in the coming years – a wake-up call to implement appropriate AI security standards and collaborate with trusted technology partners.

Cargo fraud and cargo theft are also on the rise, particularly in North America. There, criminal groups are using fake domains and identity fraud. This underscores the need for better verification and AI-driven oversight of transport companies to avoid costly disruptions.

By transitioning to AI-driven, cloud-based platforms and collaborating with trusted technology partners, companies can strengthen their security framework without incurring exorbitant costs. Large companies are no less vulnerable: outdated IT systems make no one immune. Key are investments in cloud infrastructure and shared data standards.

5. Connected Ecosystem: From Data to Action

A significant part of the barriers in the industry stems from stakeholders not sharing data. While openness varies by region, competition fosters collaboration on a global scale. Transport companies still guard certain data as competitive advantages, but the potential for industry-wide gains drives transparency forward.

Connected ecosystems that enable seamless data exchange will unlock the true value of digitization: real-time transparency that drives smarter, faster, more sustainable, and ultimately more economical decisions across the entire supply chain. The more integration progresses, the more all stakeholders benefit.

Ready for 2026

If 2025 was the year of experimentation, then 2026 will be the year of acceleration. AI will mature and move beyond pilot projects to drive profound organizational changes. Sustainability will be more focused on pragmatic, profit-oriented strategies, and building resilience will equally depend on leveraging cloud infrastructure and investing in high-quality data. Ultimately, the future belongs to companies that leverage connected ecosystems, prioritize data integrity, and take their employees along on this journey.

Christian Keating: „If 2025 was the year of experimentation, then 2026 will be the year of acceleration. AI will mature and move beyond pilot projects to drive profound organizational changes. Sustainability will be more focused on pragmatic, profit-oriented strategies, and building resilience will equally depend on leveraging cloud infrastructure and investing in high-quality data. Ultimately, the future belongs to companies that leverage connected ecosystems, prioritize data integrity, and take their employees along on this journey.”

Photo: © Trimble

Title Photo: © Loginfo24