Most organisations reach the same point with AI. A pilot works well in one part of the business, but scaling it further raises three practical problems at once.
Security and compliance. Using AI with your own data means addressing privacy, governance, and regulatory requirements as a condition for trusting the results. Ensuring EU sovereignty becomes key for many industries.
- Cost control. A pilot is cheap to run. AI in production, across multiple use cases, is a different cost equation, particularly with per-token pricing and vendor copilots at scale.
- Flexibility and vendor lock-in. Technology changes quickly. A platform that forces you to rebuild every time a new model or provider appears is not a sustainable foundation.
What could a secure, scalable AI platform look like inside your own organisation, and what are the trade-offs in getting there?
Who this event is for
This after work session is aimed at people responsible for AI and data platform direction, including:
- Head of AI
- Head of Data Platform
- Head of AI Governance
- Enterprise Architects working with data and AI
- Digital Transformation Leads
- CDO / CIO / CTO
- Particularly relevant for manufacturing, energy, financial services, and the public sector, where security, compliance, and flexibility are not optional
Why attend
A concrete look at the trade-offs for an AI platform. A short talk on what actually holds back AI at scale: security, cost, and flexibility, based on patterns seen across industries.
- Live demo: What does a scalable AI platform look like in practice? We’ll demo how organisations can move from individual AI use cases to a broader platform approach while maintaining control over security, governance, costs, and vendor flexibility. Using Solita FunctionAI® as an example, we’ll show how AI agents, workflows, and applications can be deployed without rebuilding the underlying architecture for every new initiative.
- Open discussion about what architecture and approach make sense in your own context, together with the other attendees.
- Peer network. A chance to meet others in similar industries who are working through the same decisions around data ownership, cost, and scaling AI beyond a pilot.
