Combining advanced AI and robotics: aligning technology, people and processes

What role do robotics currently play in Schiphol’s operations, and how do you see this evolving?

Robotics already play a significant role in Schiphol’s operations, particularly within baggage handling and selected ramp activities. Looking ahead, we foresee a continued shift towards end-to-end automation of airside processes, including aircraft docking and further automation across baggage operations. This evolution is driven not only by the need to reduce physically demanding work and improve working conditions for our people, but also by the growing pressures airports face worldwide, such as structural labour shortages, increasing passenger demand, and capacity constraints. Robotics will be a key enabler in ensuring that Schiphol can continue to operate safely, efficiently and sustainably at scale.

Which airport processes benefit most from robotic automation?

Airport processes that involve heavy lifting and physically demanding, repetitive tasks stand to benefit the most from robotic automation. These are areas where robotics can significantly reduce physical strain, improve safety, and enhance overall workforce wellbeing. At the same time, advances in physical AI create opportunities that go beyond simple task automation. By intelligently orchestrating systems, robotics enable airports to deploy human and technical resources more effectively – reducing manual labour where possible while optimising efficiency, resilience and operational performance across the entire process chain.

What challenges have you faced in scaling robotics solutions across the airport?

Scaling robotics solutions across an operational airport environment presents a distinct set of challenges. While deploying robotics in controlled or pilot settings is relatively straightforward, transitioning these solutions into live operations introduces significant complexity. At Schiphol, we therefore assess robotics initiatives through three interconnected lenses: the product itself, the people involved, and the organisational context. Sustainable success lies at the intersection of these three domains. One of the primary challenges is testing and validating robotics in an operational setting. Innovation timelines are often extended due to the need for regulatory approvals, permits, and the availability of operational capacity. These constraints can significantly slow down experimentation and learning in live environments. A second challenge relates to technology maturity. Many airport‑specific challenges are highly contextual and opaque, and while airports worldwide face similar issues, they do so at very different scales and levels of complexity. As a result, there is a limited availability of proven, market‑ready robotic solutions that can be reliably deployed in a brownfield airport environment.

At the same time, suppliers need real‑world airport exposure to mature their technologies – something that is not always easy to facilitate – creating a persistent gap between innovation needs and available solutions.

Additionally, many airport operations rely heavily on human intuition and situational judgement. Expecting robotics to fully replicate these capabilities often proves unrealistic and is a common point of failure.

The greater opportunity lies in rethinking end‑to‑end processes and adapting operations in a way that enables robotics to complement human expertise more effectively.

Finally, change adoption remains a significant challenge. Even when robotics do not replace jobs but instead introduce new ways of working, there can be resistance from employees. Building trust, ensuring transparency and actively engaging people throughout the implementation process are therefore critical to achieving successful and lasting adoption.

What technologies do you see complementing robotics to create a fully automated airport ecosystem?

Artificial intelligence (AI) and data are the most critical technologies complementing robotics in the journey towards a fully automated airport ecosystem. While robust robotic hardware is essential, it is AI and data that enable these systems to operate intelligently, adaptively, and at scale. The real value emerges when robotics are embedded within an orchestrated system – where advanced analytics, AI‑driven insights, and increasingly agentic AI models support decision‑making around capacity management, resource allocation, predictive maintenance, and overall operational optimisation.

At the same time, we do not envision a future in which AI and robotics fully replace humans in the workplace. Rather, the role of people will evolve.

In the near term, humans will act as sparring partners to AI systems.

Agentic models will process large volumes of data, analyse scenarios, and present a small number of well‑reasoned options, while humans retain the final decision‑making authority, drawing on experience, contextual understanding, and judgement. Over time, as AI systems continue to learn from these interactions and operational outcomes, they will become increasingly capable of handling complex, recurring situations autonomously. This human‑in‑the‑loop approach ensures that automation enhances operational performance while maintaining trust, accountability and resilience across the airport ecosystem.

How do you ensure seamless integration between robotics and existing operational systems?

Seamless integration between robotics and existing operational systems is achieved through a structured, stage‑gated approach. We begin with a proof of technology to validate the technical feasibility, followed by a proof of concept, a proof of operations, and ultimately a proof of implementation and scale. This methodology ensures that at each stage gate we can design an appropriate solution, define and validate relevant KPIs, and conduct targeted, pragmatic testing to determine whether the initiative is ready to progress or requires further refinement. This iterative approach allows us to integrate new technologies into complex legacy systems in a controlled and reliable manner, minimising operational risk while accelerating learning. A critical success factor is close collaboration with expert stakeholders from operations, ground handling and other relevant domains. Together, we test solutions in real‑world contexts, co‑design new operational concepts, and ensure shared ownership throughout the journey. Importantly, integration is not limited to adapting new technology to existing systems. We are equally willing to challenge and refine legacy processes where necessary. By continuously asking “why” and reassessing established ways of working, we create space for more effective, future‑ready operations that fully leverage the potential of robotics and automation.

What cultural or organisational changes are needed to embrace advanced AI and robotics together?

Embracing advanced AI and robotics together requires a fundamental shift in both organisational mindset and culture.

First and foremost, organisations must move from viewing AI and robotics as standalone technologies to treating them as strategic capabilities that reshape how work is designed, decisions are made, and value is created.

This demands strong leadership sponsorship and a shared vision that clearly articulates why automation is being introduced and how it supports long‑term operational resilience and workforce sustainability.

Culturally, there needs to be a shift towards experimentation and learning. Advanced AI and robotics evolve through iteration, and organisations must be willing to accept a certain level of uncertainty, failure and continuous improvement. This means creating safe environments for testing, encouraging cross‑functional collaboration, and rewarding learning outcomes rather than only immediate success.

From an organisational perspective, new skills and roles are required. As AI and robotics take on more operational tasks, human roles increasingly shift towards supervision, exception handling, decision‑making, and system orchestration. Investing in upskilling and reskilling is therefore essential – not only to build technical literacy, but also to empower employees to confidently work alongside intelligent systems. Equally important is trust and transparency. Employees must understand how AI systems make decisions, where human judgement remains critical, and how accountability is maintained. A clear human‑in‑the‑loop governance model helps build confidence and ensures that technology augments, rather than replaces, human expertise.

Ultimately, organisations that succeed in combining advanced AI and robotics are those that align technology, people and processes. By fostering a culture of openness, adaptability and shared ownership, airports can unlock the full potential of automation while maintaining a resilient, human‑centred operational model.

We will be discussing how airports are combining human intelligence with artificial intelligence to enable smarter, more efficient operations and a workforce that can focus on high-value interactions with passengers at the International Airport Summit taking place in Rome this November (11-12). Senior airport leaders can attend the summit for free so make sure you register for your place now so you can network, learn and knowledge-share with your international colleagues in Rome.

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