By Rachel Hugo and Marc Bayer

For capital goods manufacturers, service is the highest-margin segment in the portfolio – yet most organizations are still failing to capture its full commercial potential. A new Roland Berger study examines how advanced agentic AI is fundamentally changing this equation, and why the window for decisive action is narrowing.

From invisible asset to commercial engine

The installed base is the largest untapped profit pool in manufacturing. Aftermarket operations can generate multiples of the gross margins produced by new equipment sales. Yet for most OEMs, this asset remains commercially opaque: pricing defaults to portfolio averages, service intelligence rarely reaches commercial decision-makers, and post-warranty revenue migrates steadily to third-party providers.

Advanced agentic AI addresses this directly. Unlike earlier AI paradigms, it is a qualitatively different category of digital labor – planning, acting, and learning autonomously across CRM, ERP, PLM, and IoT systems. It assembles a continuously enriched view of every asset, contract, and customer relationship, enabling asset-level pricing, systematic commercial signal capture, and hyper-personalized service propositions that third parties cannot replicate.

Freeing capacity and scaling expertise

Expanding service revenue requires productive capacity. Today, approximately 40% of total service capacity is consumed by non-chargeable administrative work. Advanced agentic AI eliminates this burden systematically: generating service reports in real time, optimizing technician deployment dynamically, and acting as a unifying intelligence layer across disconnected legacy systems – without requiring full platform replacement.

But capacity alone is not sufficient. The most binding constraint on service growth is talent. Germany alone faces a shortfall of 50,000 skilled service experts, and onboarding a new technician takes 12 to 24 months. Agentic AI changes this equation by enabling less experienced technicians to perform tasks previously reserved for specialists, accelerating competence development, and converting institutional knowledge into a permanent, searchable organizational asset. Every expert who retires before this process is in place represents an unrecoverable loss.

A self-reinforcing competitive advantage

The three strategic levers – commercial value capture, operational efficiency, and workforce empowerment – compound over time. Revenue growth funds investment in efficiency; efficiency gains free capacity for higher-value work; an empowered workforce delivers superior service that drives further revenue.

We believe the manufacturers who will lead in the decade ahead are those making these decisions now – not as technology pilots, but as strategic commitments at the highest level of the organization. The Roland Berger study provides a detailed framework for C-level executives to prioritize investment, sequence deployment, and measure impact across all three dimensions.