In the interview with Patrick Thoma, Managing Director at scieneers GmbH

Artificial intelligence is on everyone’s lips – yet between impressive demos and real business success, there are often worlds apart. Why do so many AI and data projects fail despite major investments? What role do high-performance data and cloud architectures, the right corporate culture, and a realistic view of AI’s capabilities play?

We address these and other exciting questions in an exclusive interview with Patrick Thoma, co-founder and CEO of scieneers GmbH. As an industrial engineer with many years of experience at the interface between business and IT, he pursues a clear mission: to help companies create measurable business value from data and artificial intelligence – pragmatically, securely, and ready for production rather than as a short-lived hype.

In the interview, Patrick Thoma explains why the apparent simplicity of modern AI solutions often leads to a “self-service illusion,” why data quality and governance are crucial to success, and why even the best analytics solution can fail without a solid cloud and data foundation. He also discusses the importance of agile working methods, cultural change in companies, and why technology alone does not create innovation.

Look forward to exciting insights from practice, clear positions on current AI trends, and valuable impulses for decision-makers who not only want to discuss digitalization but implement it successfully. An interview about data, innovation, corporate culture – and how to turn visions into sustainable competitive advantages.

Silicon Valley Europe: Mr. Thoma, artificial intelligence is currently one of the most hotly debated topics in business. Many companies are investing in AI projects, yet not all are achieving the desired success. Why is this the case, and what sets apart companies that actually create measurable business value with data and AI?

Patrick Thoma: Many companies start with AI by focusing on the technology rather than the business value. This leads to exciting demos, but not to solutions that are truly embedded in processes, responsibilities, and systems. The companies that succeed are those that begin with a clear question: Which specific problem are we solving, what added value are we creating, and how do we measure it? When data quality, the specialist department, and implementation work together from the outset, real business value is created—not just attention.

Silicon Valley Europe: You often talk about companies needing to take the step from “playing around” to the productive use of AI. What does this mean in concrete terms, and what typical mistakes do you observe in practice?

Patrick Thoma: Productive use means: a solution runs stably, is actually used by people, is integrated into processes, and delivers reliable results. The typical mistake is that companies are dazzled by an impressive demo and underestimate the last 20 percent—such as data integration, quality assurance, governance, operations, and change management. It is precisely at this point that it is decided whether a prototype becomes a product.

Silicon Valley Europe: Data is considered the foundation of any successful AI strategy. What role do scalable cloud and data architectures play, and why do many analytics and AI initiatives fail at this very foundation?

Patrick Thoma: As you say: they are the foundation. If data is trapped in silos, pipelines are unstable, or responsibilities remain unclear, analytics and AI initiatives are almost certain to fail. A scalable architecture ensures that data is available, consistent, and securely usable. Only then can AI truly unleash its potential.

Silicon Valley Europe: With scieneers, you support companies in building modern data platforms. How do you bridge the gap between technical excellence and the concrete requirements of the business?

Patrick Thoma:

We don’t start with tools, but with goals. We look at what needs to be achieved in terms of business outcomes and build the technical solution to match—pragmatic, clean, and production-ready. Our strength lies precisely in this connection: we understand the business side but also have the technical depth to implement data platforms, analytics, and AI reliably.

Silicon Valley Europe: Many companies believe that modern AI tools can be used almost entirely in self-service mode. You speak of a “self-service illusion.” What do you mean by that, and what risks does it pose for businesses?

Patrick Thoma: Modern AI often seems as though anyone can use it securely and productively right away. That’s the illusion. Getting started is easy, but delivering reliable results in a corporate context is significantly more demanding. Without clean data, clear guardrails, professional oversight, and technical understanding, incorrect answers, security risks, or a deceptive sense of false security can quickly arise. AI democratizes a lot—but responsibility and quality cannot be clicked away.

Silicon Valley Europe: Topics like data quality, governance, and security are becoming increasingly important in the AI era. What prerequisites must companies establish to effectively prevent AI systems from producing hallucinations, incorrect decisions, or even misuse?

Patrick Thoma: You need multiple layers of safeguards. First: clean data and clear responsibilities. Second: governance—rules for access, usage, approvals, and quality. Third: technical mechanisms such as evaluation, monitoring, guardrails, and human-in-the-loop. And fourth: a realistic understanding of what AI can—and cannot—do. If you want to use AI productively, you must lead it—not just turn it on.

Silicon Valley Europe: Digitalization is far more than just technology. What role do corporate culture, agility, and the right mindset play in ensuring that data-driven innovations succeed in the long term?

Patrick Thoma: A big one. Technology can enable a lot, but it doesn’t change an organization on its own. Data-driven innovation works sustainably when teams take responsibility, collaborate across disciplines, and are willing to learn iteratively. Agility, to me, isn’t about method romanticism—it’s the ability to learn quickly, prioritize cleanly, and make progress measurable.

Silicon Valley Europe: Many companies face the challenge of bringing their employees along on this journey. What experiences have you had with this, and what recommendations do you give to leaders for successful cultural change?

Patrick Thoma: By not overwhelming them with buzzwords, but by taking them along. People want to understand why something is changing, what it means for their work, and how they themselves benefit. Leaders should provide guidance, enable participation, and create space for learning. Whoever imposes cultural change only gets resistance. Whoever makes it understandable and leads by example gets momentum.

Silicon Valley Europe: scieneers GmbH consciously stands out from standard solutions and focuses on individual, tailored approaches. What defines the DNA of your company, and why do customers choose scieneers specifically?

Patrick Thoma: Our DNA is bespoke craftsmanship rather than standard fare. We combine genuine technical depth with pragmatism and a highly collaborative work style. We don’t aim to produce slides, but solutions that work in everyday life. What clients appreciate about us is that we work on equal terms, make complex topics understandable, and are equally consistent in implementation.

Silicon Valley Europe: As an employer, scieneers also positions itself with a clear profile. What can talented individuals joining your team expect, and which qualities are particularly important to you?

Patrick Thoma: An environment with plenty of responsibility, substance, and little pretence. We work on relevant data and AI topics with high professional standards and a strong sense of pragmatism. We value people who are curious, willing to take on responsibility, collaborate effectively, and committed to turning good ideas into truly effective solutions.

Silicon Valley Europe: You don’t just operate at the highest professional level in your career, but are also a passionate triathlete and Hawaii Ironman finisher. What experiences from endurance sports shape your leadership style and entrepreneurial mindset?

Patrick Thoma: Triathlon teaches you to focus on the “sustainable pace”: a pace that is ambitious yet remains viable over the long term. This is also crucial in corporate management. Growth must be challenging, but it must not overwhelm the organization—neither culturally nor structurally. And just as in sports, success in business is not achieved through isolated highlights, but through consistency, discipline, and consistently good work, especially in customer projects.

Silicon Valley Europe: Finally, let’s look ahead. What developments do you expect in the field of Data & AI over the next three to five years, and what advice would you give to companies that want to set the right course for their digital future today?

Patrick Thoma: We will see a clear professionalization. AI will move from the experimental phase into robust business processes. Issues such as data quality, governance, integration, and operations will become even more important because that’s where the wheat will be separated from the chaff. At the same time, the pressure to not only use AI but also demonstrate its value will increase. My advice to companies: start small enough to learn quickly—but with a foundation large enough to scale later.

Silicon Valley Europe: Thank you very much for these well-founded answers and for your time.