Munich, Frankfurt, London — Between late 2025 and spring 2026, Prof. Dr. Stefan Gröner delivered three keynotes and workshops for the global IT consultancy SoftServe, each built around the question that decides every AI initiative: not what the technology can do, but whether an organization is ready to use it. At the Global Operations Workshop in Munich, the EMEA Sales Kickoff in Frankfurt and the SoftServe Executive Summit in London, AI keynote speaker and futurist Prof. Dr. Stefan Gröner showed executives why most AI projects stall long before the technology becomes the problem — and what separates companies that scale AI from those that keep piloting it.
About the AI Keynote / Workshop
Artificial intelligence has arrived in the enterprise. Budgets are approved, pilots are running, and almost every leadership team can name a use case. Yet a striking gap has opened between ambition and impact: many organizations are experimenting broadly while scaling narrowly. In his sessions for SoftServe between late 2025 and spring 2026, AI Keynote Speaker Prof. Dr. Stefan Gröner traced that gap back to its real causes — and they are rarely technical.
Why do so many AI projects stall? Gröner’s answer is consistent across all three events: because companies treat AI as a technology rollout rather than a transformation of how work is organized, decided and led. The tools are available to everyone. What is not available off the shelf is the organizational capability to redesign processes around them, the data foundation to feed them, and the trust that makes employees willing to use them. AI does not fail in the model. It fails in the middle management layer, in unclear ownership, in data that was never built for reuse, and in a workforce that has not been told what the technology means for their role.
The keynotes opened with a realistic view of the technology curve. Generative AI, agentic systems and AI-supported decision-making are advancing faster than most planning cycles are designed to absorb. Gröner illustrated with concrete cross-industry examples how the value chain shifts when knowledge work becomes partially automatable: not through the wholesale disappearance of jobs, but through the redistribution of tasks — and the resulting need to rethink roles, skills and quality control.
From there, the sessions turned to the opportunity side. Gröner outlined where measurable value is being created today: in engineering and software delivery, in customer service and sales support, in analysis-heavy functions where AI compresses the distance between question and insight. The recurring pattern in successful deployments, he argued, is focus. Companies that pick a small number of business-critical use cases, instrument them properly and hold them to a business KPI outperform those running dozens of disconnected experiments.
The challenges received equal attention — deliberately so. Data quality and data governance remain the most underestimated bottleneck. Regulatory requirements, particularly in Europe, demand traceability that many hastily built pilots cannot deliver. And the question of trust runs through everything: employees who fear being replaced do not become power users, and customers who cannot understand a decision do not accept it.
The strongest resonance came from the theme Gröner calls the human factor. Technology adoption, he argued, is ultimately a leadership question. Executives must be able to explain what AI changes, where the boundaries lie and which decisions remain human. That requires leaders who understand the technology well enough to be credible — without becoming engineers.
In the workshop formats, particularly at the Global Operations Workshop in Munich, participants moved from impulse to application. In moderated breakout sessions, teams assessed their own processes for AI potential, identified obstacles and worked toward concrete next steps. The consistent conclusion: the technology is ready. The decisive work is organizational — and it starts at the top.
About the Client
SoftServe is a global IT consulting and digital services provider, founded in 1993 in Lviv, Ukraine, with headquarters in Austin, Texas, and Lviv. With more than 10,000 employees and locations across Europe, North America and South America, the company supports enterprises in digital engineering, data and analytics, cloud, and AI/ML. SoftServe serves industries including high tech, financial services, healthcare, life sciences, retail, energy and manufacturing, and partners with major technology providers such as Google Cloud, AWS, Microsoft Azure, Salesforce and NVIDIA. With over 30 years of experience, SoftServe is among the established players in enterprise digital transformation.
About the AI Keynote / Workshop
Artificial intelligence has arrived in the enterprise. Budgets are approved, pilots are running, and almost every leadership team can name a use case. Yet a striking gap has opened between ambition and impact: many organizations are experimenting broadly while scaling narrowly. In his sessions for SoftServe between late 2025 and spring 2026, AI Keynote Speaker Prof. Dr. Stefan Gröner traced that gap back to its real causes — and they are rarely technical.
Why do so many AI projects stall? Gröner’s answer is consistent across all three events: because companies treat AI as a technology rollout rather than a transformation of how work is organized, decided and led. The tools are available to everyone. What is not available off the shelf is the organizational capability to redesign processes around them, the data foundation to feed them, and the trust that makes employees willing to use them. AI does not fail in the model. It fails in the middle management layer, in unclear ownership, in data that was never built for reuse, and in a workforce that has not been told what the technology means for their role.
The keynotes opened with a realistic view of the technology curve. Generative AI, agentic systems and AI-supported decision-making are advancing faster than most planning cycles are designed to absorb. Gröner illustrated with concrete cross-industry examples how the value chain shifts when knowledge work becomes partially automatable: not through the wholesale disappearance of jobs, but through the redistribution of tasks — and the resulting need to rethink roles, skills and quality control.
From there, the sessions turned to the opportunity side. Gröner outlined where measurable value is being created today: in engineering and software delivery, in customer service and sales support, in analysis-heavy functions where AI compresses the distance between question and insight. The recurring pattern in successful deployments, he argued, is focus. Companies that pick a small number of business-critical use cases, instrument them properly and hold them to a business KPI outperform those running dozens of disconnected experiments.
The challenges received equal attention — deliberately so. Data quality and data governance remain the most underestimated bottleneck. Regulatory requirements, particularly in Europe, demand traceability that many hastily built pilots cannot deliver. And the question of trust runs through everything: employees who fear being replaced do not become power users, and customers who cannot understand a decision do not accept it.
The strongest resonance came from the theme Gröner calls the human factor. Technology adoption, he argued, is ultimately a leadership question. Executives must be able to explain what AI changes, where the boundaries lie and which decisions remain human. That requires leaders who understand the technology well enough to be credible — without becoming engineers.
In the workshop formats, particularly at the Global Operations Workshop in Munich, participants moved from impulse to application. In moderated breakout sessions, teams assessed their own processes for AI potential, identified obstacles and worked toward concrete next steps. The consistent conclusion: the technology is ready. The decisive work is organizational — and it starts at the top.
About the Client
SoftServe is a global IT consulting and digital services provider, founded in 1993 in Lviv, Ukraine, with headquarters in Austin, Texas, and Lviv. With more than 10,000 employees and locations across Europe, North America and South America, the company supports enterprises in digital engineering, data and analytics, cloud, and AI/ML. SoftServe serves industries including high tech, financial services, healthcare, life sciences, retail, energy and manufacturing, and partners with major technology providers such as Google Cloud, AWS, Microsoft Azure, Salesforce and NVIDIA. With over 30 years of experience, SoftServe is among the established players in enterprise digital transformation.
