For many large companies, AI is on every agenda, yet many leaders are still trying to make sense of what to do next. A big reason for this uncertainty is that huge amounts of data are still locked away in separate departments or stuck in systems that don't talk to each other, making it hard to turn that data into real value.


The shift toward open collaboration

In 2026, the most forward-looking companies are starting to let go of the instinct to hold data tightly. Instead, they are focusing on what you might call a resilience advantage: working in open, collaborative networks that increase strength and flexibility instead of further isolation.

In Germany, this shift is taking shape through Manufacturing-X, a shared digital network that helps companies exchange data in a more secure manner. Manufacturing-X is an umbrella initiative dedicated to establishing open, security-enhanced, and sovereign data ecosystems across various industries. This exchange isn’t about giving away intellectual property or sharing trade secrets; it’s about building a common foundation that lets AI improve decision-making by providing a complete view of the business and its partners.

Manufacturing-X’s pioneering network, Catena-X, focuses on the automotive value chain and enables security-focused, end-to-end data exchange. As the flagship "X" project under Manufacturing-X, Catena-X is the blueprint for developing similar initiatives in other sectors, such as Aerospace-X and Factory-X.

Case study: The Catena-X network

You can see how this open collaboration approach works in practice in the Catena-X network, which connects companies such as Micron, DensoBMWIBM, and Bosch. Catena-X provides a standardized “highway” built with production-grade security in mind that allows every company in the automotive supply chain to contribute its verified data. At the core of Catena-X's approach is the principle of self-sovereignty. The ecosystem relies on a decentralized architecture rather than a central data repository. Every partner retains full control over their data, deciding exactly what information to share, when, and with whom. The network protects intellectual property and trade secrets, offering a vendor-agnostic environment. This allows companies to choose certified solutions that fit their needs, without sacrificing data ownership or security.

This framework of security-focused, sovereign data exchange provides the essential foundation for complex industry requirements, including Europe’s digital battery passport.

The battery passport

New regulations in Europe require a "passport" for every electric vehicle battery, a digital record that tracks its full lifecycle. That includes the source of a battery’s raw materials, its carbon footprint (PCF), and its eventual recycling. In the past, calculating a car battery's carbon footprint was mostly an educated guess based on spreadsheets. Without a shared, open data standard, achieving a passport-level of traceability across different companies is next to impossible. Collaborating in the Catena-X network provided a standardized highway that allows every company in this complicated supply chain to contribute its verified data.

By using an open system to share verified, up-to-date primary data across the value chain, companies were able to:

  • Improve accuracy: In an example, transparent emissions data exchange between an original equipment manufacturer (OEM) and suppliers increased the accuracy of carbon footprint calculations by an estimated 46%.
  • Make fact-based decisions: Teams move from assumptions and industry averages to decisions grounded in standardized primary data.
  • Achieve greater agility and defect management: Because they follow open, shared standards, teams can quickly spot faulty parts.

In the battery passport use case, the open data ecosystem not only satisfies regulatory requirements but also establishes a more trustworthy, cohesive view of a vehicle battery. Rather than solely relying on a supplier's assurance, an automaker can access up-to-date, auditable data. This kind of transparency allows an AI-driven system to instantly verify compliance, forecast recycling needs, and issue a warning to quickly halt a production line if it identifies faulty parts. That level of coordination can save these manufacturers and suppliers millions of dollars in potential recalls and wasted materials. 

The approach transformed a regulatory headache into a competitive advantage built on speed, accuracy, and shared trust. Because companies feel more secure in what they are sharing and how, they are willing to participate in multitier data exchanges that address joint industry challenges, leading to significant benefits, such as earlier error detection, faster root-cause analysis, reduced warranty costs, and scalable decarbonization.

Driving AI integrity

Working together on open data standards also enhances AI transparency. Rather than relying on "black box," third-party logic, an open system lets everyone see and verify the logic. That means a business joins a community that sets the standards. Openness and transparency transform regulatory compliance into a competitive advantage, fostering a supply chain that is faster and more resilient than those that don’t follow the same conventions.

An open system dismantles opacity. It operates on principles of freedom and transparency, allowing every stakeholder to see, verify, and audit the underlying logic, data sources, and training methodologies. This radical transparency transforms AI from a mysterious potential liability into a shared, auditable asset.

The path forward

Today, the most critical step for leaders is determining where internal barriers and gaps persist. If your data remains on an island, your AI capabilities will be equally isolated. Success will go to those willing to join a network and operate with transparency. As demonstrated by the leaders of the automotive industry, the most resilient and successful companies won't be the ones with the tightest secrets, but the ones that excel at working together on AI initiatives.

Ready to see how an open data ecosystem can transform your enterprise AI strategy? Join Red Hat at NVIDIA GTC 2026 to explore how open source is fueling the next generation of AI innovation, including Red Hat AI Factory with NVIDIA. From theatre talks on building cohesive, integrated AI components to an in-depth exploration into Red Hat AI, you’ll discover how a transparent, community-driven approach accelerates the path from raw data to actionable intelligence.

Recurso

La empresa adaptable: Motivos por los que la preparación para la inteligencia artificial implica prepararse para los cambios drásticos

En este ebook, escrito por Michael Ferris, director de operaciones y director de estrategia de Red Hat, se analiza el ritmo de los cambios y las disrupciones tecnológicas que produce la inteligencia artificial y a los que se enfrentan los líderes de TI en la actualidad.

Sobre el autor

Adam Wealand's experience includes marketing, social psychology, artificial intelligence, data visualization, and infusing the voice of the customer into products. Wealand joined Red Hat in July 2021 and previously worked at organizations ranging from small startups to large enterprises. He holds an MBA from Duke's Fuqua School of Business and enjoys mountain biking all around Northern California.

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