Until 2025, AI in Schaeffler’s Aftermarket division essentially consisted of nothing more than Copilot licenses, so Lina Eddis decided to tackle a real AI strategy. And just as she began, all budgets were cut… Okay, so, change of plan: an AI strategy that costs (almost) nothing…

With the successful SAP S/4HANA RISE Cloud go-live in April 2024, the fischer group has taken a significant step toward a modern, scalable IT landscape. In parallel, the infrastructure was renewed and a manufacturing execution system (MES) was introduced for digital production control. Building on this platform, the fischer group is now driving numerous AI initiatives: from Microsoft Copilot in everyday work, to the automation of SAP delivery schedules with SAP Joule, to data-driven use cases based on a data lake for machine data. The talk offers insights into our experiences so far, first successes, and the challenges of connecting SAP, production, and artificial intelligence in an internationally operating industrial company.

The role of the Chief Information Officer (CIO) has changed fundamentally: from a purely technical administrator in the IT “engine room” to the CEO’s strategic co-pilot and a driver of digital processes. Increasingly, the CIO acts as a Chief Transformation Officer, radically rethinking business processes through technology and leading the shift toward becoming an agentic AI enterprise. In doing so, the CIO directly secures the company’s profitability, digital reputation, and long-term competitiveness.

Artificial intelligence is changing companies on three levels: it increases productivity within the company, becomes an integral part of digital products, and opens up new B2B business models. Using concrete examples from the MHK Group, the talk shows which strategic fields of action arise for IT leaders and what role IT plays in this transformation.

The bottleneck is rarely the model. It is data quality, process maturity, and governance. Topics in the conversation:

• Why sequence beats leapfrogging: adoption, scalable GenAI, embedded agents, without skipping stages, and why you start where data and processes are most mature, not where the hype is loudest.
• “Layer over Lock-in”: AI as a layer on top of the leading systems rather than embedded in every vendor, and what that means for a CIO’s reversibility and optionality.
• Governance as an operating system, not a policy document: enabling power users quickly while maintaining guardrails (data classification, human-in-the-loop, cost accountability) instead of a culture of prohibition.
• What really drives adoption: a community of practice, real use cases presented by their owners, and sponsorship from the top, instead of mandated tools.
• The honest part: what is really running today and what has deliberately not been built yet.

Many companies invest in data and AI but struggle to translate the technology into sustainable business results. This session offers practical insights into building a data and AI organization that enables scalable innovation, data-driven decision-making, and AI-based ways of working. Learn how the right operating models and a clear business focus can turn data and AI from isolated initiatives into a strategic capability that delivers measurable business value.

Artificial intelligence is regarded as a key technology for the future of healthcare. But how can it be successfully deployed in a highly regulated environment such as statutory health insurance? The talk shows how AI applications can be taken from the initial idea, through legal and organizational guardrails, into productive operation. The focus is on concrete experiences in automating administrative processes, dealing with the requirements of the AI Act, and the question of how efficiency gains, skilled-workforce retention, and better care for the insured work together. Practical examples make clear which opportunities, challenges, and success factors shape AI transformation in healthcare, and why setting the right course now is crucial.

The keynote covers the following key aspects:

• ERP transformation as a strategic realignment rather than a technical migration.
• Reassessing the ERP core in light of AI and modern software architecture.
• From a monolithic platform to modular business services.
• Best-of-breed, custom developments, and AI as building blocks of a future enterprise platform.

Hardly any company can foresee the consequences of adopting AI in advance, as both experience and metrics are lacking. Software development is the first field to gather both. This keynote shows what AWS is observing among its customers: where AI reduces costs, where it creates complexity, and where faster teams put quality at risk.