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Vilnius’ AI Summit Europe 2026 to Focus on Moving AI from Pilots to Production This November

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  • AI Summit Europe 2026 will examine practical pathways from experimental projects to scalable enterprise applications on November 24–27th in Vilnius
  • The Summit’s sessions will explore autonomous agents, governance, security, data infrastructure and responsible AI adoption
  • Hands-on workshops will address AI strategy, lakehouses, multi-agent systems, streaming and data security
  • International experts will share case studies spanning enterprise deployment, organizational transformation, AI economics, and governance

Vilnius will host the third edition of AI Summit Europe, examining AI adoption, agents, governance, automation and measurable business impact. The Summit will take place in Vilnius and online from November 24–27th, focusing on the practical challenges of turning AI from an experimental technology into a scalable business capability. The third edition will feature more than 40 sessions across three tracks, with 400+ attendees expected from more than 35 countries.

The event will start with a full day of hands-on workshops at Simbiocity Nova on November 24th, followed by three conference days at Forum Cinemas Vingis on November 25–27th. Participants can attend onsite or online, while a single ticket additionally provides access to the co-located Big Data Conference Europe 2026.

From AI Pilots to Production

A central question running through this year’s programme is how organizations can move beyond impressive demonstrations and deploy AI reliably at scale. Sessions will examine enterprise adoption, AI strategy, operational implementation and, the organizational changes required to turn AI investments into measurable results.

The agenda will cover AI agents and autonomous workflows, production-grade architectures, LLM evaluation, observability, AI governance, security, and cost optimization. Speakers will also address the practical realities of deploying AI across regulated industries and complex enterprise environments, including data access, model risk, privacy, cybersecurity and human oversight.

One example is Klemensas Mecejus‘ (of AI71)session on Europe’s AI deployment gap, which will examine how sovereign and industrial AI can move from pilots toward governed, secure, and measurable production operations. His presentation will focus on workflow ownership, data access, cybersecurity, privacy, model riskб and the operating models needed to industrialize AI.

Various Perspectives on the AI Transformation

  • The programme is organized around six tracks:
  • Proof of Value,
  • Minds & Machines,
  • Data Meets AI,
  • Data in Motion,
  • Data Value & Trust,
  • and Agent Foundry.

Together, they cover the business, organizational, technical and governance dimensions of AI adoption.

The Agent Foundry track, for instance, will explore the rapidly developing world of autonomous systems, with sessions on multi-agent architectures, agent orchestration, evaluation, observability and enterprise search. Topics include building agent teams with skills and MCP, deterministic architectures, agent trust, AI-driven document processing and the security of autonomous systems.

Meanwhile, Data Meets AI and Data in Motion will examine the infrastructure behind production AI, from AI-ready data and real-time pipelines to scalable data platforms and agentic applications. Sessions will address subjects such as production-grade AI agents on Databricks, Apache Flink, semantic caching, GenAI evaluation, and the migration of large-scale data environments.

Governance, Trust, and the Human Side of AI

As AI systems become increasingly autonomous, governance and accountability will receive significant attention. The programme will explore AI safety, regulatory requirements, privacy, security, verification, and practical governance frameworks for organizations operating in regulated environments.

Sessions like Building AI Governance: A Practical Architecture for Regulated Organisations will look at concrete approaches to assigning ownership, categorizing risk, establishing human oversight and maintaining evidence for audits. The emphasis is placed on making governance repeatable and operational rather than treating it as a purely theoretical or compliance-driven exercise.

Altogether, the Minds & Machines track will address another dimension of adoption: the relationship between people, organizations and increasingly capable AI systems. Topics range from preserving human decision-making and managing AI anxiety to organizational culture, AI transformation and the practical challenges of embedding AI into everyday work.

Workshops Focused on Practical Implementation

The workshop day of November 24th will offer full-day sessions covering technical implementation, AI strategy, data infrastructure, and responsible adoption. Participants are welcome to choose from topics including building GenAI-ready lakehouses on AWS, creating sandboxed multi-agent systems, optimizing Spark pipelines, and developing real-time data pipelines.

More workshops will focus on data testing, AI strategy, AI-assisted product discovery, privacy and sensitive-data anonymization, low-code streaming analytics with Apache Flink, and persistent data architectures. The format is designed around hands-on learning, with participants working on focused implementation challenges alongside experienced practitioners.

International Speakers Look at AI’s Next Phase

The keynote programme features such speakers as:

Their sessions will address AI leadership, organizational transformation, emerging software models and the implications of increasingly automated systems.

The wider speaker roster spans technology, data, cybersecurity, consulting, and enterprise AI, with contributors from such companies and organizations as Databricks, AWS, ICEYE, and AI71, and more. Among the programme’s practical case studies is Karin Immenroth‘s session on how Mediaplus developed an AI operating model across more than 25 markets, examining the transition from isolated experiments toward organization-wide adoption.

The programme also reflects the growing importance of AI economics, with sessions examining token costs, semantic caching, local AI, and efficient model deployment. Rather than focusing exclusively on what AI systems can do, the agenda looks at what organizations need to operate them sustainably, securely and at scale.

AI Summit Europe and Big Data Conference Europe Are Co-Located

AI Summit Europe 2026 will take place alongside Big Data Conference Europe, creating two parallel programmes focused on complementary aspects of the AI transformation. While AI Summit Europe concentrates on strategy, adoption, agents, automation, and enterprise implementation, Big Data Conference Europe focuses on data engineering, analytics, cloud platforms, and production data systems.

A 3-Day Onsite, 3-Day Online or 4-Day Full ticket provides access to both conference programmes from November 25–27th, while the four-day option adds one full-day workshop on November 24. The main Summit is hybrid, with all sessions available to remote participants and recordings included with summit passes.

Beyond the sessions, the event will feature a special movie screening on November 25th and an AI Summit Party on November 26th at Forum Cinemas Vingis. The venue itself offers cinema-scale screens and sound, giving the technical programme a setting designed for large-format presentations and demonstrations.

In a Nutshell

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