How To Make AI Work at Scale in Logistics Operations

What does scaling AI actually look like for your business? In association with Logifem, Umut Şatir Gürbüz, principal sales engineer at Dataiku, explains in this no-nonsense Q&A what really works, what stalls and why some companies pull ahead. 

From Issue 1, 2026 of Breakbulk Magazine.

1. How is AI currently transforming logistics operations, and which use cases are delivering the most immediate value?

Umut: AI is reshaping logistics by bringing intelligence into processes that were historically manual and fragmented. The fastest ROI today comes from use cases that combine data from multiple sources and automate decisions at scale.

Forecasting, inventory optimization, predictive maintenance and document automation are becoming mainstream because companies now have tools that allow operations teams, data experts and business users to work together on a single flow, from data preparation to model deployment.

More recently, multimodal GenAI has unlocked faster resolution in customer and technical support by analyzing text and images in one environment. When organizations can build, test and operationalize these solutions in a governed, repeatable way, the impact becomes both immediate and sustainable.

2. What are the biggest challenges logistics companies face when adopting AI solutions, and how can they overcome them?

Umut: Many organizations underestimate the importance of a strong foundation. AI requires clean, connected data and a collaborative environment where teams can explore, prototype, validate and deploy without friction.

The second challenge is operationalizing AI. Pilots often fail not because the model is weak, but because there is no structured path to deploy, monitor and maintain it. Companies that rely on manual handovers between teams face delays and inconsistencies.

To overcome this, logistics companies need an end-to-end framework that brings data, analytics and operations together. When governance, versioning, automation and monitoring are built into the workflow, AI adoption accelerates dramatically.

3. Many logistics organizations struggle to scale pilots into production. What separates successful AI-driven companies from the rest?

Umut: The most successful organizations don’t treat AI as isolated experiments, they build reusable components, shared data pipelines and standardized workflows that reduce the time from idea to production.

They empower business and domain experts to participate directly in the process through guided, self-service interfaces, while ensuring IT and data teams maintain control through built-in governance and oversight.

And importantly, they industrialize AI with strong MLOps practices: automated deployment, continuous monitoring, retraining and lifecycle management. When these elements are integrated, scaling becomes a natural progression rather than a reinvention for every use case.

4. With the rise of GenAI, how should logistics companies rethink customer experience, customer support and knowledge management?

Umut: GenAI represents a major shift toward intelligent, contextual, real-time assistance. Support teams can analyze customer queries, documents, images and historical interactions in a unified workspace, rather than juggling disconnected tools.

Knowledge management becomes dynamic rather than static: every resolved case, every operational insight and every document update can feed back into the system automatically. This creates a continuously improving knowledge fabric that AI can tap into.

Companies that centralize their knowledge flows, including data, documents, images and logs, and provide governed access to GenAI workflows, see dramatic improvements in first-response accuracy, case routing and resolution times. It transforms both customer experience and internal productivity.

5. What ethical considerations should logistics leaders keep in mind when deploying AI?

Umut: Ethics and responsibility must be embedded from the start. AI systems should be transparent, interpretable and continuously monitored, not only at launch, but throughout their lifecycle. A mature approach includes drift detection, alerting, traceability and documentation as built-in elements, not optional add-ons.

Data privacy is equally important. Logistics organizations deal with sensitive operational and customer data. Platforms that provide controlled access, clear lineage and well-governed collaboration protect both the company and the customer.

Finally, leaders should ensure employees are included in the journey through training, guided tooling and human-in-the-loop processes. This ensures AI augments people rather than creating uncertainty around its role.

6. As a female leader in data and AI, how do you see women shaping the future of logistics, and what advice do you have for new talent entering the space?

Umut: Women bring a systems-thinking mindset that is incredibly valuable when working with AI. Successful AI initiatives require orchestration, connecting data, processes and people, and women often excel in roles that bridge technical and operational teams.

I see women leading transformation projects, driving innovation in analytics and advocating for responsible use of AI. They naturally bring structure, collaboration and empathy into cross-functional teams, which is essential when delivering solutions that must be adopted on the ground.

For new talent, my advice is to embrace platforms and tools that let you experiment safely, collaborate widely and learn continuously. The logistics industry is evolving fast, and those who understand how to turn ideas into operational solutions in a structured, governed way, will shape its future.

Umut Şatir Gürbüz is a principal sales engineer at Dataiku, an enterprise-level AI integrator, specializing in machine learning, data analytics and agentic AI. Logifem Society Network, a Women in Breakbulk partner, stands out as a pioneering force dedicated to empowering women in logistics and freight forwarding. Founded in Istanbul, Logifem has quickly grown into a vibrant international community, connecting more than 150 members across continents.