Opening of the data:unplugged Festival 2026

Felix Schlenther built 25 AI employees – and fired every single one of them. In his keynote, the founder of AI FIRST reveals what paradigm shift is needed for AI to create scaled impact in business. An honest journey through three years of trial and error – with a clear blueprint for what comes next.

Self-employed people are CEO, CFO, CMO, and CTO all rolled into one. Every day, they make decisions in eight roles simultaneously. Tax, marketing, logistics, finance. Without a team, without a network. This is the biggest unsolved problem in entrepreneurship.
At the same time, Agent Hospital, AI Scientist, and Jane Street show that AI systems are already independently taking on complex tasks in medicine, science, and finance. Not as assistants. As decision-makers.
Christian Steiger, Managing Director of Lexware, shows how Lexware is making these technologies available to 4 million self-employed people in Germany. Using real products such as AI-supported Instagram content creation and the vision of AI that proactively prepares business decisions. His approach: away from prompting, toward mandating. Don't ask AI, lead it.

Philipp will present the 2026 edition of his "Beyond the AI Hype" series of talks. You'll learn about the pivotal moments in AI, this years challengens and what the future holds for the industry.

How Organization, Governance, and Data Quality Determine the Success of AI Multi-Agents
The Trojan horse metaphor captures how many companies approach generative AI: quick to deploy and easy to integrate—but risky without a solid data foundation. This presentation explains why a GenAI strategy goes beyond tools and leads to the piloting of AI multi-agents. Data quality is crucial to ensure that quick wins with AI do not become a “Trojan horse.”

I show why, in the age of AI, it's not the best model that wins, but the most adaptable people and organizations. From my nearly 25-year journey from the tutoring room to millions of math learners on YouTube to AI-powered learning systems and courses, I deduce how learning works as a system - not as a coincidence. Access to knowledge is not the problem - AI has solved that. The real problem is that most people have never learned how to truly learn. In this session, I will show why “learning how to learn” is the crucial skill of the next decade - and what you need to do to make it happen!

Who isn't familiar with that pure fascination about everything that has suddenly become possible through Artificial Intelligence? Yet, almost simultaneously, a certain unease often creeps in: Where is our economic and working world actually heading right now?

The media is full of the signs of this shift: Classic entry-level jobs are disappearing, coding is increasingly taken over by machines, and on the stock market, minor feature updates from major AI flagships are enough to cause the share prices of hundreds of companies and established industry leaders to plummet within an extremely short time.

But who will be hit next – and above all: why?

As an AI startup investor, dealing with radical market disruption on a daily basis is our core business. We specifically look for the structural vulnerabilities of traditional industries and opportunities for new entrants like startups. In this session, we take an exclusive look behind the scenes and share insights that are highly relevant for every decision-maker.

Behind the media noise lies an astonishingly clear logic. We will demonstrate the hidden criteria used to calculate which business models are structurally defenseless – and which (often unexpected) sectors possess a massive protective shield.

Get ready for 15 minutes of unfiltered reality – and find out which side your market is on.

Quantum computing is often described as a technology of the future. Yet the race has long since begun. Whilst many companies are currently focusing on AI, a new computing paradigm is emerging in the background – one that could fundamentally transform the way we solve highly complex problems. From drug development and supply chains to energy systems, quantum computing has the potential to unlock entirely new avenues of value creation. The key question is no longer whether this technology will become relevant –
but who is prepared for it.

Artificial intelligence is having a disruptive effect on companies, and not just in the form of chatbots and agents. Industrial companies in particular have enormous potential to leverage sensor, laboratory, and other process data. This data can be used to measurably optimize industrial and production processes. In our joint slot, we will show how Ingredion has not only achieved initial success in recent years along the entire value chain, from a data platform to industrial AI use cases, but has also fundamentally optimized shop floor processes. We show the journey over several years and how use cases have made it from proof of concept to an operationalized and productive system.

In her presentation, Dr. Meike Schäffler, a member of the Executive Board at Westfalen AG, demonstrates how artificial intelligence is evolving at Westfalen from a passing trend into a source of genuine value for the company. With practical insights into the AI journey, innovative approaches such as “Fail Forward,” and the development of a self-learning organization, it becomes clear why AI doesn’t allow for a 5-year plan—but courage and curiosity lead the way.

Be inspired by how AI becomes a competitive advantage and how WestfalenGPT is transforming knowledge and processes in a sustainable way.

Doing is like wanting—only cooler!

Agentic AI is the next stage in AI implementation. However, the challenges that arise during operation are often underestimated. The presentation will provide insight into the fundamental concepts and concrete use cases. Stefan Brock is the Head of the AI Excellence Center and was responsible for IT operations for over 20 years.

The shortage of skilled care professionals is no longer a future challenge: It is today’s reality.

Intelligent service robotics and AI are already delivering measurable impact. 10X Robotics GmbH from Bochum presents real-world implementations with the German Red Cross, Diakonie, and AWO, demonstrating how technology creates tangible relief in elderly care environments.

This talk focuses on authentic use cases from daily operations:

Autonomous delivery robots transporting medication, laundry, and meals while reducing unproductive walking distances. AI-powered cleaning robotics ensuring the highest hygiene standards. And social and humanoid assistive systems powered by Large Language Models, enabling natural conversations, cognitive activation, orientation support, music-based engagement, and guided movement exercises for fall prevention.

The goal is not replacement but empowerment. More time for human connection. Greater independence and quality of life for seniors. And a new level of human-machine collaboration.

We will show how robotics becomes a true team member through seamless software integration and process consulting – compliant, practical, and economically viable.

A keynote for everyone who wants to understand how Care 4.0 is already transforming elderly care today.

Code is cheap, trust isn’t. In a world where trust is collapsing, visibility is evaporating, and products can be copied overnight, there’s only one real moat left against the competition: the story people believe about you.

OTTO's transformation from a mail-order giant to the largest German online retailer is a testament to its constant innovation. Now, around 30 years after pioneering online retail, OTTO is embracing another paradigm shift: AI. Just as the internet reshaped shopping, AI is poised to transform user journeys and access to OTTO's vast assortment.

In his keynote, the former CEO of OTTO Marc Opelt, will provide an inside look at this ongoing transformation, revealing how the company prepared for the age of AI assistants and intelligent shopping agents to define the future of retail once again.

What we wish we'd known before migrating from Redshift to Snowflake: insights after the first six months in production.
In this session, we'll cut through the vendor pitch and share real-world lessons: when off-the-shelf migration tools fail (and what to do instead), why embedding analysts as co-owners accelerates cutover, and how parallel ingestion strategies de-risk high-stakes transitions.
Expect a balanced assessment of where Snowflake exceeded our expectations and which capabilities required more investment to unlock. You'll walk away with actionable best practices for migration planning, team enablement, and realistic timeline setting.
This session is for data platform leaders, engineers, and analytics managers evaluating or planning cloud data warehouse migrations who want honest insights over vendor promises.

Talent development in competitive youth sports is often heavily based on early competition results, even though it is well known that selection and promotion based solely on this criterion carries an increased risk of misjudgment. Against this backdrop, the German Alpine Club has developed a standardized nationwide test battery for young athletes in sport climbing.

In addition to competition data, this also records technical, tactical, athletic, psychosocial, and environmental parameters. It soon became apparent that the added value of this approach depends crucially on a central data platform that guarantees data sovereignty, transparency, and adaptability—key aspects of digital sovereignty.

In collaboration with Woodmark, a platform was created that bundles and evaluates extensive data sets and visualizes relevant parameter combinations without removing decision-making authority from the sports context. This supports coaches in making data-based, transparent decisions.

The presentation introduces the data-driven model, the underlying platform, and initial findings on optimizing the promotion of young talent in climbing.

A practical report from Toll Collect and Telekom MMS on secure, hybrid AI architectures in the EU Cloud.

How can artificial intelligence be safely deployed in highly sensitive, heavily regulated data environments?
Tino Mager (Telekom MMS) and Frederik Spang (Toll Collect) provide insights into how Toll Collect, as a privacy-focused company, has made the majority of its document inventory intelligently usable with Business GPT—compliant, performant, and in the German Cloud.
The hybrid architecture with MS Foundry and EU models forms the basis for diverse applications: from deep research and translations to LLM chats with company-specific data.
The result: secure, practical AI that delivers real value even under the strictest requirements.

The next generation of data platforms must serve not just traditional analytics but emerging AI workloads like RAG, vector search, and agentic pipelines - all while remaining open, cost-efficient, and performant. The Open Lakehouse architecture has emerged as the foundation enabling this openness. This session dives under the hood of an Open Lakehouse - showing how Apache Iceberg, Apache Hudi, and Delta Lake bring database-grade capabilities to cloud object storage. We’ll explore technical internals like ACID transactions, concurrency control, indexing, and table optimization services such as clustering, compaction, and cleaning, and understand what true “openness” means in practice. Attendees will learn how these components enable low-latency queries, predictable costs, and real-time consistency, with real-world examples, powering analytical, streaming, and AI-driven workloads.

In this talk we explore the transformative impact of big data and artificial intelligence on the insurance industry. From using chatbots for customer service to AI-driven fraud detection, this talk delves into how these technologies optimize critical business processes. Focusing on telematics data in motor insurance, it highlights personalized pricing and streamlined claims reporting. As the market leader in motor insurance in Germany, HUK-COBURG leverages vast data and cutting-edge technologies to optimize models, integrate AI, and drive innovation through interdisciplinary, agile analytics teams.

SKF stands for more than 100 years of industrial innovation. However, the transformation into an AI-driven organization is not only a technological challenge, but above all a cultural and organizational one. Therefore, the presentation focuses on change management as the key to the success of SKF’s AI strategy.
The introduction of AI fundamentally changes processes, roles, and responsibilities. Employees often approach these changes with curiosity, but also with uncertainty and resistance. Successful change management takes these emotions seriously, provides orientation, and fosters a learning organization.
Change management is the engine of AI transformation at SKF. Only when people, structures, and culture evolve together can a traditional company like SKF make the leap to a “Frontier Company” in the age of AI.

Mercedes-Benz AG has decided, as part of its cloud strategy, to gradually migrate its Finance Controlling BI applications from SAP BW to MS Fabric.
This presentation describes the framework, prerequisites, general conditions, success factors, experiences, and challenges during the migration. In doing so, we address both organizational and technical aspects. The migration was carried out in two main steps. First, a "Gold2Gold" migration, in which ready-made transactional and master data were made available in the new MS Fabric target architecture in a short time. In the second step, a "Bottom-Up" approach was executed, in which the entire BI transformation logic was migrated on the MS-Fabric side. Here, master data harmonization was also carried out along central characteristics (Central Integrated Dimensions) to enable further data integration, especially with the Mercedes-Benz Vans division. During a subsequent parallel operation phase (Cutover), data will be reconciled between the on-premise and the new cloud implementation.
Specifically, we are looking at a productive application for contribution margin controlling for Mercedes-Benz Cars, which is used worldwide for all Mercedes-Benz markets.

Artificial intelligence can only be as good as the data it is based on. But how do companies manage to sustainably anchor data quality and responsibilities for data? In this session, Rolls-Royce Power Systems demonstrates how to successfully establish a federated data governance organization in practice - with clearly defined roles, where Data Owners and Data Stewards take responsibility for data and central tasks in data management.
Learn which communication and training strategies foster acceptance, how stakeholders are involved, and how to promote cultural change. This presentation provides practical insights into the challenges and success factors in building a data governance organization that strengthens data quality and enables the long-term use of AI.

In this deep‑dive session, we demonstrate how Snowflake and Microsoft Fabric work together in practice—using Iceberg tables as an open storage format and Fabric mirroring as the integration bridge. Using a representative integration setup inspired by real project experience, we walk step by step through the available options, from mirroring and semantic modeling to metadata virtualization, governance, cost, and performance considerations.
You’ll learn when to use Iceberg versus Delta, where the current technical boundaries lie, and how to minimize data duplication, latency, and platform lock‑in.
Takeaways include proven integration patterns, architecture blueprints for interoperability, concrete metrics to assess business value (e.g. time‑to‑insight, compute cost, BI stability), and clear dos and don’ts for running Snowflake and Fabric side by side in production.

Retail competition is fierce: countless competitors, rising dropshipping startups, and major marketplaces offering products directly from manufacturers at unbeatable prices – all in a challenging consumer climate. How can a German retailer compete, survive, and thrive?
In this talk, we present Tchibo's PUMA, an AI project designed to improve pricing and distribution for Tchibo's unique offering program "A New World Every Week." This creates a "non-stop cold-start" for AI developers: new products with only a handful of pilot sales. Our solution combines limited pilot signals with a growing foundation of historical sales data – from banana slicers to inflatable boats – to determine optimal prices and efficiently distribute our products across warehouses, stores, and online channels. We'll dive into our lightweight, Google Cloud-based setup and share what worked – and what didn't.

Fabric IQ turns AI gimmicks into real workforce: Agents that know our business, take on tasks, and deliver immediate business value.

In this keynote presentation, we'll not only showcase a real-world example, but also provide a roadmap for how companies can leverage AI not as a buzzword, but as a concrete, productive workforce. You'll witness firsthand how Fabric IQ Agents at Fegime Germany autonomously perform repetitive tasks, accelerate internal processes, and generate measurable results.

How is artificial intelligence changing everyday work in media sales? This presentation provides practical examples of how AI solutions at RTL and Ad Alliance support the entire process chain, from preparation and execution to follow-up of customer appointments. Information from meetings and emails is automatically structured and transferred to the CRM system, relevant market and customer information is available at the touch of a button for appointment preparation, and follow-up is efficient and integrated – with noticeably better data quality in the CRM system. The combination of AI, CRM, and Outlook makes it possible to exploit sales opportunities in a more targeted manner and reduce administrative tasks. Nordic AI Solutions is currently implementing this project at Ad Alliance/RTL and, together with the customer, is providing honest insights into challenges, learnings, and concrete added value for sales from the ongoing project.

How can a B2B fulfillment process that relies heavily on locality be digitized without losing personal proximity to the customer? Instead of manually taking orders by phone, WhatsApp, fax, and email, an AI agent now guides the liba team through the process. The customized Beverage AI Assistant (BAIA) independently processes orders, responds to regional specifics, helps optimize product selection and quantities, and thus relieves the team in their daily work. Together with liba, we provide exclusive insights behind the scenes and into the future of wholesale. The pilot phase shows that the combination of shop system, dialogue-based AI, and smart assistance is not a sure-fire success. We show what works, where the problems lie, and what lessons can be learned when humans and machines learn fulfillment together.

AI is everywhere and promises a technological revolution, yet many companies still struggle to create real value with it. It’s a case of not seeing the forest for the trees: too much focus on technological capabilities, and not enough on aspects such as strategic relevance, employee competence, collaboration processes, and governance mechanisms. In this talk, Tiankai introduces the FOREST framework – an intuitive and practical way to set the right priorities and make AI scalable for true business value.

In the heart of Berlin, GASAG has been shaping the capital’s energy supply for more than 175 years—from gas-lit streets to climate-neutral energy for tomorrow. This talk explores how, building on this foundation and after numerous periods of transformation, an entirely new data organization is emerging. What does it mean to break open established structures in a company rich in tradition and rethink them digitally? What lessons were learned and what obstacles encountered on the journey from a traditional utility to a data-driven service provider? The journey spans historical complexity and diverse business units, through cloud transformation, to embedding AI and data literacy into the DNA of a large enterprise. It offers candid insights into how the company brings innovation and sustainability together in an industry undergoing profound change—and why data has become the fuel for the next era.

Industrial production environments generate more data than ever before.
IoT stacks, data platforms, and analytics tools are largely in place — yet the practical impact in daily operations often remains limited.

The real bottleneck is no longer data collection, but access.
Powerful interfaces exist, but they typically require deep domain expertise. This is where RUBY AI comes in.

This session presents a real-world industrial use case demonstrating how natural language can serve as an interface to machine data — and why generic AI models quickly reach their limits without domain context. The key lies in combining structured machine data with process knowledge and long-established domain expertise.

The talk outlines how “ask-to-data” evolves into a context-aware production assistant — and what comes next on the path toward proactive, operational AI in manufacturing.

Data Culture is an important trend topic in the current Analytics discourse. While the term itself is very much of the moment and shapes the debate, it brings together the well-established themes surrounding the implementation of data-driven working in organizations and companies — and the question of what it takes to make that transformation succeed. It is essential to foster a willingness to work in a data-driven way, to build the competencies that make it possible, and to create the right conditions for it to thrive. But change has never been a simple matter. In individual companies, Data Influencers can make all the difference. In a discussion between two experts, the necessary competencies, key success factors for change, the role of the Data Influencer, and real-world perspectives on transformation drawn from project experience will all be explored.
Highlights:
Experience a lively expert panel discussion!
Hear answers to the question of what it takes to drive successful change.
Be part of the conversation yourself.

• Why Data Democratization is important
• What are the key components and success factors
• How does it work in a real life environment
• What are the concrete steps to start your data democratization journey

How PAYBACK has been rethinking data-driven decision-making with ThoughtSpot for several years:
In this interview, both companies offer insights into their shared journey – from initial challenges and concrete internal and external use cases to measurable business impact.
This interview will illustrate how BI and analytics have evolved at the loyalty market leader, which employs 1,000 people and serves over 700 partner companies in several European countries.

Germany has no shortage of innovation reports, rankings, and funding programs. But one of the most honest indicators of innovation is hiding in plain sight: job postings.

We analyzed over 300,000 currently open positions to see which AI and data skills companies are actually hiring for today. The result is a real-time picture of how fast different industries are truly transforming – and where the gaps between ambition and reality are widening.

For leaders who want to know: Where does my industry stand? What are my competitors hiring for? And which skills will define competitiveness tomorrow?

As enterprises evolve from isolated AI assistants to domain-specific multi-agent systems, scaling innovation without overloading central teams or violating data and AI governance becomes critical. BASF Coatings addresses this with MAUI (Multi-Agent Universal Interface), a Databricks-native platform that enables business to build, operate, and scale multi-agent solutions within a unified enterprise framework. We illustrate this end‑to‑end workflow through a descriptive real‑life example of a marketing and sales assistant AI, demonstrating how domain‑specific agents create tangible value in everyday business.

Sales teams in B2B manufacturing often face a dilemma: they spend too much time on routine inquiries, searching for data sheets, and initial lead qualification—time that is desperately needed for complex customer consulting and actually closing deals. At the same time, international buyers increasingly expect immediate, precise answers around the clock.

How do you break this bottleneck? In this session, using the TRUMPF AI Assistant as a prime example, we will show that modern "Agentic AI" is much more than just a reactive support tool. Following its successful launch in Germany and subsequent rollout to the US market, the system now operates as a digital top performer within the sales team.

Learn from practical experience:

The Workload Reliever: How the AI agent autonomously handles initial technical queries, completely freeing up the human sales team to focus on high-value tasks.

The Revenue Driver: How the system acts as a 24/7 sales assistant, proactively guiding users to the right machine and generating qualified leads across all time zones.

The Tech Shift: Why the leap from basic Generative AI to autonomous Agentic AI was crucial for achieving this dual ROI (efficiency + growth).

A pragmatic blueprint for mid-sized and manufacturing companies looking to reduce their sales team's workload while simultaneously maximizing their global sales opportunities.

A ChatGPT here, a Copilot there, a few prompts in marketing – and still the feeling that none of it truly moves the needle? You're not alone. Most mid-market companies are experimenting with AI tools but aren't transforming their business. The reason: AI is treated as a utility instead of a strategic lever within the value chain. In this session, Christoph Knöll shows how Operational AI works – the approach that embeds AI directly into core business processes to drive real transformation. No slide-deck strategy, but real-world cases: from an AI-powered due diligence agent to intelligent portfolio filtering systems to lead intelligence that transforms sales operations.

What you'll take away:

• Understand why isolated AI tools don't deliver transformation – and what actually works
• Learn the triad of Strategy, Change, and AI Architecture that creates real impact in the Mittelstand
• See concrete cases where AI operates directly within the value chain – measurable and immediately actionable
• Walk away knowing how to take the first step from tool adoption to genuine business transformation

AI systems like ChatGPT, Gemini, and Perplexity are fundamentally changing search behavior.

While LinkedIn is declaring the end of SEO and promoting “GEO” (Generative Engine Optimization) as a completely new playing field, practical experience paints a far more nuanced picture: we are not witnessing a replacement, but a structural transformation of digital visibility.

In this keynote, Michael Möller - active in Organic Search for over 15 years and advisor to well-known mid-sized and enterprise companies -explains what AI Search truly means from a strategic perspective.

The real shift goes deeper:
We are moving from an internet primarily used by humans to an ecosystem in which AI systems and agents filter information, evaluate it, and prepare decisions.

For decision-makers, the question is therefore not whether SEO is dead — but how visibility works in a world where answers matter more than rankings.

The presentation demonstrates:

• how search behavior is measurably changing through systems like ChatGPT, Gemini, or Perplexity
• why many companies misinterpret their current AI visibility
• what limitations existing tracking methods have
• and which three strategic fields of action are now critical to systematically building AI visibility

The talk is aimed at marketing and digital leaders in mid-sized and technology-driven companies who are seeking orientation - beyond hype, tool promises, and reactive actionism.

A strategic overview for anyone who wants to understand how to win in AI Search before market share is lost invisibly.

Transforming AI hype into measurable productivity: Join Bo Arian Bruun (CEO) and Malik Kirchner (CTO) of xelonic, together with Antje Lubitz (CEO/Founder) and Julia Krause (COO) of 3PM Services, as they reveal the inner workings of their strategic partnership.

Discover the shift from basic RAG-based chat systems to high-performance Agentic Workflows—where AI agents in asset management go beyond providing answers to proactively managing complex tasks across existing software landscapes.

Moving past the buzzwords, the speakers demonstrate why high-tier Data Quality and robust ETL pipelines are the true engines of success. They also pull back the curtain on their collaborative journey: showing how a specialized SME team prepares for AI and how a synergetic partnership can truly redefine the future of work.

This is the story of a chatbot destined to be more than just another algorithm. It wasn't just built to reply; it was built to understand. But along the way, we learned a crucial lesson: True empathy isn't only needed in the code, but primarily in front of the screen. It is the invisible bond between client and service provider—and the only way to spark genuine innovation. The fact that NFON, as our technology partner, trusts us at CEWE Group with this speaking slot is the ultimate proof of this approach in action.

Our shared journey with NFON serves as a prime example of how to successfully handle AI in general: It’s not just about the raw technology, but about how we humans deploy it collaboratively, empathetically, and with purpose. I will share how we built a new team from scratch and why mutual understanding remained our most important compass throughout the entire development phase.

Who is this talk for? Innovators, project managers, CX enthusiasts, and anyone looking to do more than just automate processes with AI, but to create real, human value.

I warmly invite you to join the session: Come by, get inspired, and discover why, sometimes, the absolute best thing you can do is send your chatbot to the psychologist. I look forward to seeing you there!

How are professional football clubs already using AI in their day-to-day operations — and what's standing in the way of scaling it up? Representatives from SC Preußen Münster, FC Schalke 04 and VfL Wolfsburg share concrete use cases from IT, Business Innovation and Marketing. Together with ecm:one, they explore the role of structured data and document management as the foundation for AI projects — and what other organisations can learn from their experience.

The vision of Artificial Intelligence in the enterprise is huge - but the reality inside ERP systems is often still rigid and unwieldy. How do we bridge the gap between theoretical AI hype and true, native value creation right at the users' desks?

We are taking it one crucial step further. We will make the buzzword "Agentic AI" tangible through practical examples and look ahead to the true paradigm shift of the future. What happens when AI stops merely analyzing data and starts taking independent action? We will outline the vision of an ERP world where autonomous AI agents control entire business processes, create workflows from scratch, and proactively handle routine tasks.

In this session, we will show you the path from the first strategic idea to the functioning live environment, and all that in just 3 months. Using the AI agent developed by us for the ERP system Haufe X360, we’ll show you what native generative AI looks like in action today. Discover how deep UI integration and intelligent data abstraction ensure that the AI intrinsically understands the user's exact context and makes complex ERP data immediately usable.

A session for CEOs, strategists, and data architects who want to grasp the big picture - from the functioning status quo to the autonomous enterprise future.

Despite substantial investments in data & AI, many organizations struggle to demonstrate visible returns. Bayer has decided to tackle this challenge with Mindfuel’s Data & AI Impact Management approach.

In this session Nadiem von Heydebrand (Co-Founder & CEO @Mindfuel) and Timo Peters (Head of Process Insights & Value @Bayer) will introduce Data & AI Impact Management: a shift from one-off projects (which often fail) to demonstrating actual business impact from AI investments. A playbook-style intro paired with practical examples from Bayer.

In this session you’ll learn how to:

• Increase your chances of finding high value use cases and transforming unstructured business demands into opportunities with clear value hypotheses upfront.
• Use case discovery done right, leading to initiatives prioritized based on business outcomes, not just technical feasibility.
• Application of a product mindset to data & AI allowing to scale impact beyond single initiatives by linking business use cases to reusable data products.
• Make value the center of the conversation for data & AI using its full potential in different fields and organizational setups.

This session is for data & AI leaders and innovators who want to stop managing projects and start managing impact.

Marketing and product decisions are expensive bets. New campaign. New feature. New market positioning. Most companies only find out if something lands after the launch — after the budget is spent, after the time is gone, after the momentum is lost. The guesswork and flying blind aren't a failure of individual teams. They're structurally built in, as long as there's no reliable way to pre-test human responses.
Digital Twins solve exactly this problem — not with random synthetic profiles, but with validated, neuropsychologically grounded personas built on over 1 million real survey responses and up to 250 data points per person.

Dr. Jonathan T. Mall — neuropsychologist, AI researcher and co-founder — shows how the findings of cognitive science can, for the first time, be turned into scalable decision infrastructure.

What to expect:

- 𝗪𝗿𝗼𝗻𝗴 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝗮𝘀 𝗮 𝘀𝘆𝘀𝘁𝗲𝗺 𝗳𝗮𝗶𝗹𝘂𝗿𝗲: Why traditional market research and gut instinct both break down before the data exists
- 𝗡𝗲𝘂𝗿𝗼𝗽𝘀𝘆𝗰𝗵𝗼𝗹𝗼𝗴𝘆 𝗺𝗲𝗲𝘁𝘀 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝗰𝗲: What decision research captures that pure statistics cannot
- 𝗣𝗿𝗲-𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝗰𝗼𝗻𝘁𝗲𝗻𝘁, 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗮𝗻𝗱 𝗯𝗿𝗮𝗻𝗱: How teams validate messages and positioning before a single euro is invested
- 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗲𝗱 𝗮𝗴𝗮𝗶𝗻𝘀𝘁 𝗿𝗲𝗮𝗹 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝘀: 85–98% alignment with actual survey respondents from our clients, like Essity, Oetinger Verlag, Rewe etc.
- 𝗦𝘆𝗻𝘁𝗵𝗲𝘁𝗶𝗰 𝗱𝗮𝘁𝗮, 𝗴𝗲𝗻𝘂𝗶𝗻𝗲 𝗲𝘁𝗵𝗶𝗰𝘀: No personal data, no consent issues — and still precise at the human level

Ideal for anyone who has decided to stop flying blind — and wants to make wrong decisions genuinely optional.

AI is cheap, powerful, and easy to access. But is that enough when it runs in demanding environments, e.g. on real machines and in real processes? What happens when an agent overshoots - and no one stops it?

With our sensorized popcorn machine, we show how agentic AI combines sensor data, documentation, and domain knowledge into actionable recommendations. And why the critical moment isn't when the AI finds a solution, but when it recognizes that its solution violates an operating limit - and says No.

We apply the same principle to examples from robotics, building management, and e-commerce. Because reliable AI isn't an industrial niche but a fundamental question for anyone deploying agents in production.

Data must flow in order to create value. But often it ends up as unused capital in isolated silos.

In this presentation, we break down the walls: Learn how a regional energy supplier, together with doubleSlash and badenIT, made the leap to a scalable data lakehouse ecosystem.

We show how established workflows and a new data culture turn departments into true partners—backed up by concrete cases such as sustainability management, customer journey analyses, and customer insights.
A practical report from the field for the field.

Why AI needs context

Many companies quickly reach their limits with AI projects, despite high expectations.
The presentation highlights why these limits are often not technological, but rather how customer journeys are conceived and structured.
It shows where customer journeys actually begin, why consistency and context play a central role in this, and what this means for the successful use of AI.

Most mid-sized businesses are dabbling in AI – but few are actually transforming. The reason is simple: they treat AI as a tool, not as a fundamental shift in how work gets done. Marek Janetzke breaks down what a truly AI-First organisation looks like, why the most common failure mode is unclear ownership of the end-to-end adoption process – and how to get there deliberately, without chaos, with results you can measure.

Remmert, based in Löhne, specializes in fully automated storage technology, intralogistics, and automation solutions, particularly for sheet metal and long goods.

In our slot, Sven Wunram from Remmert will provide insight into the data journey of the past year, and Aleksander Fegel from Ailio will report on project experience with data, analytics, and AI in medium-sized industrial companies.

Together, we will provide insights into what the data transformation and journey at Remmert has looked like so far and what companies can achieve with a clear data strategy.

Many companies are investing heavily in AI, yet in most cases only a small number of knowledge workers actually use these tools. The majority of the organization remains excluded. In this session, Tom will explain why a successful AI transformation only truly begins when frontline and non-desk employees also gain access to AI. Real-world examples will demonstrate how organizations are scaling AI and achieving real productivity gains.

88% of companies use AI in at least one function. But only 7% have truly scaled it (1). The rest are stuck in pilot.
One mid-sized industrial company made that leap with dbeyond ai+: from zero to 1,300 active AI users in less than four months.
Our founding partner Kevin will walk through the real success factors live, joined by two representatives from the company, and show what you can take away for your own AI transformation.

(1)Singla, A., Sukharevsky, A., Yee, L., & Chui, M. (2025). The state of AI in 2025: Agents, innovation, and transformation. QuantumBlack, AI by McKinsey.

Agentic AI is changing both the capabilities of AI and our understanding of work. But who orchestrates the agents? And who ensures that they do the right thing? Yasemin Efiloğlu (PD) and Oskar Trautmann (Plan.Net Studios) bring together what belongs together: radical practice and responsible governance. From real use cases to architectural thinking to governance frameworks. A talk for everyone who wants to use agentic AI correctly and sustainably.

How AI Turns Handoffs into Real Collaboration Between Teams

Let’s be honest: You're using 99 different tools, but none of them are really talking to each other. The reality in many companies looks like this: Sales uses CRM A, Procurement works in ERP B, Excel sheets are flying back and forth via email in between, and across departments, people are secretly using ChatGPT, Gemini, or Claude in their browsers.

The result? Data silos, manual copy-paste processes, missing interfaces, and uncontrolled shadow AI.

In short: 99 tools, 99+ problems.

The solution to this chaos isn't app number 100, nor is it the next external consulting team. What companies need now is a strategic breakthrough from a single source—a completely new concept that combines IT expertise, profound service, and a revolutionary tool approach, drastically streamlining your service provider landscape: Allow us to introduce: Your new BAIP!

BAIP stands for Business Automation & Integration Platform and seamlessly expands into a Business Artificial Intelligence Platform. But what does that mean exactly for your day-to-day operations?

A BAIP is not just a simple tool; it is the architectural master plan for true business orchestration. It acts as the conductor of your IT:

Integration & Automation: Instead of manually migrating data, this concept connects all your existing systems (like M365 and specialized applications). Documents are intelligently recognized (OCR), data is transformed, and everything is controlled within fully automated end-to-end processes via dynamic multi-step forms.

Artificial Intelligence: Instead of letting AI grow unregulated, a BAIP centrally orchestrates all AI models. This goes far beyond mere chatting: By configuring tools via the Model Context Protocol (MCP), you establish granular rights. You control exactly which CRUD operations (Create, Read, Update, Delete) are allowed to be executed in your systems. This gives your processes an acting "brain" that performs routine tasks independently, but strictly according to your rules.

Why do we secretly call it our "Babe"? Because it brings back exactly what companies miss most in the AI era: control and security. A BAIP not only harmonizes systems, data, and AI, but it also makes your data protection officers happy. It puts an end to the GDPR gray areas of shadow IT and ensures that you are playing at the technological forefront—100% compliant.

On the Tomorrow Stage, we will reveal the secret. We won't just show you why the BAIP concept is the future of enterprise IT—we will demonstrate the technology that makes this vision a reality today. Stop by and get your aha moment.

Successful AI models are based on clean data, while productive AI applications rely on well-thought-out integration. Processes and results must remain traceable and reproducible at all times. This is precisely where FME comes into its own. As an all-data, any-AI platform, FME enables the seamless orchestration of AI applications. In this presentation, we will show how FME can be used to implement the entire AI workflow in a structured and controlled manner – from data preparation and the integration of a wide variety of AI models to the automated further processing of results. From data preparation and the integration of a wide variety of AI models to analysis and evaluation: everything in one workspace. All data formats can be integrated, transformed, and output again—structured or unstructured, locally or in the cloud. This creates the complete Data-Science-Lifecycle in a user-friendly, no-code platform. AI orchestration made easy.

Everyone wants AI: CLV predictions, churn models, marketing mix modeling, agents, automation.
Reality: data scattered across ten tools, messy tracking, three different definitions of “conversion” and every team defending its own numbers.
And then people wonder why AI does not deliver. Shit in, shit out. Just faster. And more expensive.
Before talking about models, we need real use cases. And a setup that avoids silos instead of reinforcing them.
This is about what is almost always missing:
Clean data flows. Clear KPI definitions. No tool or department silos. And finally a real way to connect marketing costs with revenue and margin.
AI is not the starting point. AI is the amplifier. Good structure gets better. Bad structure gets multiplied.

If you want to use AI without it blowing up in your face tomorrow, this talk is for you.

Introducing AI is the easy part. Bringing it to life in an organization—that's the real challenge. Warsteiner has developed over 200 AI agents in less than a year—not through a centralized IT project, but through a principle that the brewery has known for centuries: pass on knowledge, try things out, hand over responsibility. What it takes: people who go along with it – not because they must, but because they want to. Because AI rarely fails because of the technology – but because of the people who don't embrace it. How to turn reluctance into enthusiasm and get an entire organization on board.

Artificial intelligence is getting better and better. So what's next?

How do we prepare for a future in which algorithms organize our thoughts and make decisions without us? What will happen to our self-confidence? Will we think like machines? Who will lead whom?

Personal intelligence stands for the ability to consciously process information, recognize context, learn throughout life, and produce human clarity and decisions.

Andrea Weichand shows how we can use creative problem solving in the context of AI and PI and reveals how we as humans can benefit from it.

Most automation projects don’t fail because of technology. They fail because no one asked the right questions beforehand.
In this keynote, you’ll learn why the foundation determines success or failure and what that really means in practice. With real-life examples straight from everyday work.

Data doesn’t drive decisions; understanding does. In this live demo, Kevin shows how teams can transform raw datasets into clear, interactive stories using AI-powered tools. From analysis to visualization to scalable distribution, discover how to turn insight into impact in minutes, not days.

The future of childhood is being written right now. The question is not if technology will shape that future. It's who will shape it. And for whom. It will define whether AI accelerates inequality or unlocks opportunity for every child. Innovation can become impact on global scale. Let us shape the future!

Many companies have built agents. Few have agents that truly function as productive coworkers. Is it all just hype?
Not necessarily, but the difference between pilot and productive use rarely lies in the model. It lies in the lack of context and infrastructure to enable agents to act in the real world.
Esri shows how ArcGIS closes this gap: through spatial domain knowledge that enables agents to make operational decisions about the physical world. Context-based, scalable, and with measurable ROI.

Information overflow. How do we reach people today with trustworthy content? What matters, and what is right? Join us on an expedition into the world of digital visibility. How visible are you? And how do you build trust?

AI is reshaping the skills businesses need – faster than most of us can realistically keep up with.
How do you hire for roles that barely existed two years ago? And at what point does your accountant, your project manager, your head of marketing need to have AI skills too?
In this fireside chat, we'll get into the real, practical challenges AI transformation creates for businesses. What does current labor market data actually show us? Which industries and functions are already feeling it – and where are we still asleep at the wheel?
And the big question: what should SMEs actually do about it, right now?

Artificial intelligence does not automatically make organizations more productive. In many cases, it first exposes how unclear collaboration, responsibility, and leadership already are. AI is not only changing processes, but also roles, decision logics, and team dynamics. In hybrid work settings especially, this quickly becomes more than a technology question. The real challenge is whether organizations can combine efficiency gains with clarity, trust, and sound judgment. That is where transformation actually begins.

Artificial intelligence can hold conversations that sound surprisingly human. But how does intelligent behavior actually emerge? In humans. In machines. Where do we find structural parallels, and where are the truly fundamental differences?

In this talk, Michael Romer deliberately takes a step back from tools, prompts, and product demos and asks a deceptively simple question: how do humans and machines really tick?

Drawing on perspectives from computer science, cognitive science, and philosophy of mind, he explores why modern AI systems can appear so astonishingly capable and why our impression of “thinking machines” often reveals more about us than about the machines themselves.

Once machines start talking to us, something strange happens. We begin to attribute understanding, intentions, or even consciousness to them. The talk shows why humans are fundamentally experiential beings, while modern AI systems resemble data-driven entities. This distinction is key to understanding what AI can already do remarkably well, what is likely to scale in the coming years, and where genuine scientific breakthroughs are still required.

Rather than offering another roundup of tools, this talk provides something different: a mental map for navigating the AI jungle. Less hype and buzzwords, more understanding. And a reminder that when it comes to artificial intelligence, the most important intelligence we have is still our own.

AI is beginning to take over part of the traditional work performed by lawyers in the VC and M&A context. The question is no longer what AI can do. The real question is: what are we still needed for? The answer no longer lies in documents or standard legal knowledge. Legal advice is shifting away from execution and toward structure, context, and decision-making. Anyone working in VC and M&A today who wants to create real value must do more than deliver technically sound legal work. They must connect the dots, build deals, and help shape and make decisions. The value of legal is not disappearing, but it is shifting radically. It is no longer about drafting contracts. It is about designing deals that actually work.

Everyone wants AI. Everyone wants to be successful.
But hardly anyone consistently answers the decisive question: Don’t we need to fundamentally change our organization to achieve that?
Because the uncomfortable truth is this: most AI initiatives don’t fail because of the technology — they fail because organizations keep their ways of working, responsibilities, and decision‑making processes unchanged.
In their talk, Alina and Kai‑Luka show why AI is, above all, a question of enablement — and why future readiness doesn’t depend on whether a company uses AI, but on how consistently it embeds AI into the organization.
They will share insights into the GuideCom approach to making AI effective across both the breadth and depth of the organization — turning isolated experiments into real productivity and new innovative strength.
Alina and Kai‑Luka look forward to sharing impulses and insights on how companies can shape this path in practice.

Security agencies and the police have been using robots for some time now in particularly high-risk and dangerous situations.

Increasing autonomy and performance make their use conceivable in an ever-wider range of applications. At the same time, concepts for the use of robotics in public spaces are increasingly being developed on the market. The civilian use of robots offers new opportunities but also presents challenges for police work. Robotics and autonomous systems are therefore a key focus of the Innovation Lab of the North Rhine-Westphalia Police.