What You’ll Learn
Featured Sessions
Who Should Attend?
This track is designed for:
Explore the DIS2027X2 Stages and Summits
The keynote presentations are the pillars of the entire conference and the most memorable presentations of the event. As opening plenary talks, they set the tone of the entire conference, tie all themes together and provide excitement on the presentations that are about to come. This year’s keynote list includes visionaries and leading expert names in Data, Analytics and AI.
Technical stage bringing machine learning engineers, data scientists and AI practitioners together to engineer reliable AI systems and move them from experimentation into production. This year’s focus is on generative and agentic AI, context engineering, evaluation, memory, agent orchestration, retrieval, multimodal AI, post-training, inference optimization, observability and production-scale machine learning.
Technical stage bringing data engineers, DataOps practitioners and platform builders together to engineer reliable data systems for analytics and AI. This year’s focus is on AI-ready pipelines, streaming and real-time data, agentic data engineering, unstructured data, data contracts, orchestration, automation, open formats, pipeline observability, quality and cost-efficient data operations.
Technical and strategic stage bringing enterprise architects, data architects and platform leaders together to design scalable data and AI foundations. This year’s focus is on AIready architecture, semantic and context layers, hybrid and sovereign platforms, interoperability, open standards, realtime systems, metadata, knowledge graphs, composability and modernizing legacy estates for the next generation of enterprise AI.
Strategy stage bringing CDOs, data leaders and governance practitioners together to make enterprise data trusted, AI-ready and valuable. This year’s focus is on AI-ready data strategy, governance at AI speed, ownership and accountability, data products, stewardship, metadata, quality, unstructured data, regulatory readiness, operating models, literacy and measuring the business value of data.
Technical and business stage bringing analytics leaders, BI practitioners, data scientists and decision experts together to turn enterprise data into better business decisions. This year’s focus is on decision intelligence, BI and self-service analytics, forecasting, predictive and causal analytics, optimisation, real-time intelligence, semantic models, conversational and agentic analytics, decision automation and measurable business impact.
Strategy and governance stage bringing CAIOs, AI leaders, risk practitioners and responsible AI leaders together to manage AI as an enterprise capability. This year’s focus is on AI operating models, portfolio and investment strategy, AI economics and token consumption, agent governance, autonomy and oversight, AI risk, regulatory readiness, responsible AI, accountability and measurable business value.
Technical and strategic stage bringing AI platform, infrastructure, cloud, HPC and security leaders together to build and operate enterprise AI in production. This year’s focus is on accelerated computing, GPU capacity and utilisation, workload orchestration, inference infrastructure and economics, hybrid and private AI, Edge AI, storage and networking, observability, resilience, sovereignty, energy efficiency and securing AI and agentic workloads.
Strategy and operational stage bringing AI transformation, intelligent automation and process leaders together to redesign how work gets done with AI. This year’s focus is on AI-powered automation, workflow and process redesign, agentic automation, human-agent orchestration, process intelligence, autonomous workflows, AI-enabled operating models, productivity, new products and services, and scaling automation into measurable enterprise transformation.
Technical stage bringing database engineers, architects, data quality, MDM and data platform practitioners together to build trusted data foundations for analytics and AI. This year’s focus is on modern and agent-ready databases, data quality and reliability, vector, graph and hybrid retrieval, AI context and memory, master data, data modelling, lineage and integrity, database observability, unstructured data and performance for AI workloads.
Technical and operational stage bringing industrial AI, manufacturing, automation, engineering and robotics practitioners together to apply and scale AI in physical operations. This year’s focus is on industrial AI, production optimisation, predictive and prescriptive maintenance, computer vision, industrial data, edge AI, digital twins, OT/ IT integration and industrial agents, while exploring the emerging role of Physical AI, robotics and autonomous systems in the next generation of industrial operations.
Several rooms for short workshops and crash-courses. The sessions are 100 minutes long and will provide training on various organisational, business, and technical topics. The rooms are the lower part of the venue and limited to 24 people per crash-course session. Due to capacity limitation participation requires pre-registration. Workshops are released weeks before the event.
To foster more immersive and in-depth knowledge sharing and interaction, we have allocated time and room for interactive roundtable discussions on both Foundation days. This provides an excellent opportunity for you to voice your opinions, share ideas and challenges, or benchmark your strategies with peers. Each roundtable session will last 40 minutes. Due to capacity limitation, participation requires pre-registration.
Returning for its sixth annual edition, the Data and AI Readiness (DAIR) Awards celebrate organisations driving Data and AI transformation and innovation across the Nordic region. Following the successful integration of the awards into the summit, DAIR 2027 will once again recognise outstanding organisational achievements, real-world impact, and the teams turning Data, Analytics, and AI into enterprise capability.
What is a great event without a great party? After the official end of the second summit day, this year again we are organising a Data After Dark networking party at the venue for the delegates attending the event. This is a great opportunity for the delegates to network in an informal environment and makes meaningful connections and memories. The Data After Dark programme will take place in the plenum area. It will start after the end of the Expo Crawl. Refreshments and finger food can be found in several locations in the expo area.
MAY 21TH, 10:00 AM
LOCATION: Kungsträdgården, next to the big scene stage in the center of the square
Attire
Please dress appropriately for running in colder weather, with temperatures expected to be around 10 degrees Celsius that Friday.
Track
Our route is an urban one, with occasional stops due to traffic. It’s mostly flat, with a slight challenge around the 9km mark, featuring an elevation of 14 meters over 200m. For a glimpse of the part of the track, check out the screen dump of our test run | https://www.plotaroute.com/route/3288670?units=km
Baggage
Unfortunately, there are no storage or changing facilities available, so kindly refrain from bringing bags.
Spirit of the DIS2027X2 Run
This isn’t a competition with time requirements or leaderboards. It’s all about enjoying the experience, networking, and having fun! Feel free to walk or run at your own pace and decide the length you’d like to cover.
Hydration
Don’t forget to bring a water bottle to stay refreshed during the run. There are also shops along the way if you need to replenish your supplies.
Looking forward to running together and making some memorable moments.
The keynote presentations are the pillars of the entire conference and the most memorable presentations of the event. As opening plenary talks, they set the tone of the entire conference, tie all themes together and provide excitement on the presentations that are about to come. This year’s keynote list includes visionaries and leading expert names in Data, Analytics and AI.
This stage brings together business, Data and AI leaders from highly digital and data-intensive industries to explore how applied intelligence is reshaping services, decisions and customer experiences. This year’s focus is on AI-enabled financial and digital services, fraud and risk, hyper-personalisation, intelligent customer operations, autonomous workflows, network intelligence, trust and governance, and creating new digital products and business models.
This stage brings together industrial, Data and AI leaders to explore how intelligence is moving deeper into physical operations. This year’s focus is on industrial AI, intelligent and autonomous operations, predictive and prescriptive maintenance, production and asset optimisation, digital twins, Edge and Physical AI, energy optimisation, resilience, and transforming industrial data into measurable operational value.
This stage brings together retail, commerce, supply chain, logistics, Data and AI leaders to explore how applied intelligence is transforming the movement of customers, products and goods. This year’s focus is on personalisation, demand forecasting, pricing, inventory and fulfillment optimisation, intelligent supply chains, customer and shopping agents, automation, and using real-time intelligence to improve customer experience and operational performance.
This stage brings together creative, product, Data and AI leaders to explore how AI is reshaping how content and experiences are created, distributed, discovered and monetised. This year’s focus is on generative and agentic AI, AI-assisted creation, personalisation and recommendation, intelligent production workflows, immersive experiences, audience intelligence, new business models, intellectual property, trust and the changing relationship between human creativity and machine intelligence.
This stage brings together public leaders, healthcare and education professionals, and Data and AI practitioners to explore how applied intelligence can improve services and societal outcomes. This year’s focus is on AI-enabled public services, healthcare and learning, decision support, intelligent workflows, personalisation, responsible automation, trusted and sovereign data, human oversight, accessibility, and scaling AI while maintaining public trust.
DIS2027X2 Partners
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