- 23–24 March 2027
- Amsterdam, Netherlands
Agenda
Business Intelligence and Analytics Summit 2027
Day 1: Tuesday 23 March 2027
–50 minutes
Registrations and Breakfast
–10 minutes
Opening Remarks
–30 minutes
Navigating AI Economics and Boardroom Expectations
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- The scoring method used to rank a live portfolio, including the two criteria that ended up overruling all the others.
- What moved, what was cut, and what survived on political grounds rather than performance, with the reasoning attached to each.
- The run-rate costs that had quietly become permanent, and how they were brought back under review.
- What the board asks for now that it has stopped asking about pilots, and the level of detail that satisfies it.
–30 minutes
Building the Data Foundation for AI: Quality, Engineering, Access and Interoperability
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- The data engineering practices required to make enterprise data reliable for analytics, AI and agentic workloads.
- Data contracts, ownership, lineage and quality thresholds that hold up in production.
- How organisations balance central standards with domain-level ownership and delivery speed.
- The architecture decisions that improve interoperability across warehouses, lakehouses, platforms and AI systems.
–30 minutes
The Semantic Layer: One Definition of the Business Across Every System
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- How semantic layers connect metrics, business definitions, ontologies and operational data.
- Where semantic definitions sit in modern data and AI architectures, and how analytics and AI systems use them.
- How organisations measure improvements in consistency, answer quality and decision-making.
- What happens when business units cannot agree on definitions, ownership or governance.
–30 minutes
Coffee & Networking Break
–30 minutes
Panel discussionThe AI Stack Strategy: Concentration Risk, Procurement and European Alternatives
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- Where dependency actually sits across cloud, models, platforms, data, identity and tooling.
- What European and open alternatives can realistically support today.
- The engineering, migration and operational costs involved in reducing dependency.
- How organisations assess portability, interoperability and vendor exit before signing long-term commitments.
–30 minutes
Retrieval and Knowledge Graphs for Unstructured Enterprise Data
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- When retrieval is sufficient and when enterprise knowledge graphs add measurable value.
- How organisations handle entity resolution, document structure, permissions and changing source data.
- Comparing approaches using accuracy, latency, maintenance effort and cost.
- Keeping enterprise knowledge current, governed and traceable once it becomes part of AI workflows.
–30 minutes
Data Products in Production: Ownership, Reuse, Quality and Lifecycle
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- What makes a data product genuinely reusable across teams and business domains.
- Ownership models, service levels, quality expectations and discoverability.
- How adoption and reuse are measured after launch.
- When products should be improved, consolidated or retired.
–1 hour
Networking Lunch
–30 minutes
Token Economics and AI FinOps in Action
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- How organisations measure the real cost of AI workloads beyond headline model pricing.
- Cost drivers across inference, retrieval, orchestration, retries, context and multi-step workflows.
- Forecasting demand and setting useful unit-economics measures for business owners.
- How FinOps changes architecture and model-routing decisions once workloads scale.
–30 minutes
Panel discussionThe EU AI Act in Practice: From Compliance Requirements to Operational Controls
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- What the EU AI Act means in practice for organisations deploying AI systems across different risk categories.
- How providers and deployers are interpreting responsibilities around documentation, transparency, oversight and risk management.
- What evidence, controls and processes organisations are putting in place ahead of enforcement.
- How AI governance teams are integrating the AI Act with existing privacy, security and risk frameworks.
–30 minutes
Fireside chatThe 2027 Data & AI Operating Model: What Should the Function Own?
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- How data, analytics and AI responsibilities are being divided between central teams and business functions.
- What belongs with the CDO, AI leadership, technology teams and individual business domains.
- How operating models are changing as data products, AI products and agentic systems move into production.
- Which capabilities should be built internally and where organisations are relying on external partners.
–10 minutes
Closing Remarks - Day 1
–1 hour 20 minutes
Cocktail Reception
Day 2: Wednesday 24 March 2027
–50 minutes
Registrations and Breakfast
–10 minutes
Opening Remarks
–30 minutes
AI & Agent Observability: Monitoring, Security, Access Control and Audit Trails
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- What organisations actually need to monitor across models, agents, tools, workflows and downstream actions.
- Tracing failures to individual steps, tools, data sources or model decisions.
- Identity, permissions and controls for non-human systems acting without a human session.
- Building audit trails that support investigation, governance and regulatory requirements without creating unnecessary monitoring overhead.
–30 minutes
What "Trustworthy AI" Means to Customers, Regulators and Employees
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- How enterprises evaluate AI systems for accuracy, reliability, groundedness, consistency and task performance.
- Testing and monitoring AI systems as models, data and workflows change.
- Security risks, including prompt injection, data leakage, excessive permissions and unsafe tool use.
- Connecting technical evaluation to business outcomes and deciding when a system is ready for production.
–30 minutes
Panel discussionGoverning Agents That Act on Their Own
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- Risk-tiering criteria and what qualifies an action for human review.
- Agent identity, access, the override switch, and who is accountable when an autonomous system acts.
- Policy as code and guardrails that run in the background, and where human validation adds control rather than delay.
- How governance changes as agents move from recommendations to taking actions independently.
–30 minutes
Coffee & Networking Break
–30 minutes
Fireside chatWithdrawing an Agent From Production and the Controls That Followed
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- The warning signals that trigger a decision to pause or withdraw an AI system from production.
- The operational and business impact of unwinding workflows that other teams have already built around it.
- The controls, remediation and review processes introduced afterwards.
- What the organisation changed before allowing similar systems back into production.
–30 minutes
From BI to Decision Intelligence: Modern Analytics in the Age of Conversational AI
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- How BI is evolving from dashboards and scheduled reporting toward conversational, embedded and AI-assisted analytics.
- Where natural-language analytics works today and where it still produces unreliable answers.
- How semantic models, governed metrics and context improve analytical accuracy.
- Moving from answering questions to supporting decisions, recommendations and measurable business outcomes.
–30 minutes
AI in Customer-Facing Operations: What Improved Performance and What Did Not
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- Deployments across service, sales and marketing with the measured effect on revenue, cost to serve and satisfaction.
- Which use cases produced measurable improvements in revenue, cost, productivity or customer outcomes.
- The handover design between automated and human contact, and how that threshold was set.
- How organisations determine when AI should automate, assist or hand work back to people.
–1 hour
Networking Lunch
–30 minutes
From Self-Service to Governed Analytics: Scaling BI Without Losing Control
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- How organisations are expanding self-service analytics while maintaining consistent metrics, definitions and access controls.
- What belongs with central data teams versus business users.
- How semantic layers, governance and AI-assisted analytics are changing the self-service model.
- Measuring adoption, trust and business value without recreating dashboard and reporting sprawl.
–30 minutes
Agent-to-Agent Transactions, Interoperability and Liability
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- What agent-to-agent interaction is already possible, and where interoperability remains immature.
- Identity, authentication, permissions and accountability when autonomous systems interact.
- How organisations manage liability when actions are initiated across multiple systems or organisations.
- The standards, controls and architecture decisions required before agent-to-agent workflows can scale.
–30 minutes
Building an AI-Literate Organisation From the Top Down
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- The operating model, ownership and process changes required for sustained adoption.
- How leadership, workforce capability and business-process redesign affect AI adoption.
- Measuring whether AI is actually changing how work gets done rather than simply increasing tool usage.
- What AI literacy looks like in practice, beyond a training module and a completion rate.
–10 minutes
Closing Remarks
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Join us in Amsterdam
Business Intelligence and Analytics Summit 2027
- Leadership, Value & AI Economics
- Modern Data Foundations
- Generative & Agentic AI
- Modern BI & Decision Intelligence
- Governance, Risk & Regulation
- AI Infrastructure & Sovereignty