AI Adoption in Freight Forwarding: Practical Insights from the Frontlines

As an AI leader in freight forwarding and across industries, I’ve led transformations where artificial intelligence (AI) and machine learning (ML) have delivered measurable business impact.

With the global AI in logistics market projected to reach $20.8 billion by 2025 at a 45.6% CAGR (McKinsey), the opportunity is undeniable. But I’ve also seen how this potential is often lost when adoption is driven by hype rather than strategy.

The reality? AI success isn’t just about models and algorithms—it’s about clear business goals, stakeholder alignment, and change management. In this article, I share practical lessons and recommendations from my work with freight forwarders and logistics leaders to help you move from AI buzzwords to bottom-line results.

 1. Identify the Right Opportunities and Quantify the Impact

Many AI projects start with technology looking for a problem. Instead, start with the business challenge and quantify the transformation potential.

For freight forwarding, AI can directly drive:

• Sales Transformation – B2B freight sales are relationship-driven. Researching new customers or preparing for meetings with existing ones can take 30–60 minutes manually. Conversational AI can cut prep time to minutes, enabling sales teams to shift from transactional selling to consultative, trust-based engagement—improving win rates and margins.
• Operational Efficiency – Freight forwarders process thousands of invoices and shipping instructions in varied formats. AI and GenAI can automate document workflows, reducing verification costs and turnaround times. In one case, automation cut processing costs by 20% while accelerating throughput—saving millions annually.

Recommendation: Launch each AI initiative with a clear, quantified target—e.g., “Increase Q3 revenue by 20% via AI-enabled sales transformation.” Share this target widely to secure buy-in and accountability.

2. Secure Executive Sponsorship and Cross-Functional Alignment

AI transformations need more than funding—they need leadership champions who can align teams, clear roadblocks, and sustain momentum through inevitable challenges.

For customs department of a government entity, progress stalled until functional leaders were fully engaged. Their involvement ensured the solution was relevant, practical, and embraced by end-users.

Recommendation: Map stakeholders early, co-create the vision, and keep alignment alive with regular updates and visible wins.

3. Win the Frontline and Manage Change Proactively

Technology adoption succeeds or fails at the frontline. Users balancing daily targets will only embrace AI if they see clear value and feel supported.

In a freight ops rollout, we embedded Transformation Champions from operational teams. They gathered feedback, tested workflows, and acted as trusted advocates, leading to smoother adoption and higher satisfaction.

Recommendation: Roll out in phases, communicate benefits clearly, and adapt quickly based on feedback.

4. Design AI Solutions for Real-World Complexity

Freight forwarding is too complex for “one-size-fits-all” AI. The most successful solutions combine automation with human judgment:

• Hybrid Models: AI handles 80% of standard quotes, while humans tackle hazardous cargo or unique shipments.
• Human-in-the-Loop: AI automates tracking and data entry; humans validate critical updates for reliability.

Recommendation: Start with an MVP, incorporate feedback loops, and plan manual fallbacks for exceptions.

Final Thoughts

AI in freight forwarding isn’t about chasing trends—it’s about using technology to grow revenue, improve resilience, and deliver exceptional customer experiences.

With the AI in logistics market projected to hit $549 billion by 2033 at a 46.7% CAGR, now is the time to act. Start small, iterate fast, keep people at the center—and measure every step.

Question for you: What’s the single biggest AI opportunity or challenge you see in your freight forwarding business? Let’s shape the future together.