Last week, Stelia joined Lenovo and other enterprise customers in Munich for Lenovo’s annual EMEA Customer Advisory Forum – a three-day gathering centred around how increasingly intelligent AI capabilities are delivering tangible business impact. The forum addressed a critical inflection point for enterprises: as AI moves beyond experimental use cases, organisations are confronting what it actually takes to deploy these capabilities at production scale with confidence.
Matt Dobrodziej, SVP & EMEA President at Lenovo, opened the forum with a keynote exploring findings from Lenovo’s latest CIO research. His presentation assessed the strategic imperatives emerging across enterprise AI adoption, as organisations transition from hype-driven AI experimentation to calculated, ROI-driven investments focused on business outcomes rather than technology deployment for its own sake. The research revealed that the greatest challenge enterprises are facing comes down to data quality and management. With most AI workloads expected to run on hybrid infrastructure and governance frameworks still maturing, the findings underscored that it will be operational readiness and architectural foundations that determine whether AI initiatives deliver value or accumulate technical debt.
This theme – what it takes to truly productionise AI at scale – ran throughout the forum.
During the event, Kevin Smith, Stelia’s COO, joined Per Overgaard, General Manager of ISG EMEA at Lenovo, on stage to discuss exactly how AI can effectively be used to drive innovation and genuine competitive value at scale.
Kevin’s presentation focused on a persistent challenge facing enterprises today: the gap between AI pilots that demonstrate promise and AI systems that deliver sustained business value at scale. Organisations are repeatedly discovering that proof-of-concept success doesn’t translate directly to production environments, as models performing well in controlled settings encounter integration complexities and operational constraints in real-world environments. The result is a growing portfolio of AI initiatives with unclear paths to deployment, or systems launched into production that require constant intervention to maintain acceptable performance.
“Productionising AI at scale demands a system-aware approach across the entire AI stack. Organisations are discovering that moving from experimentation to operational deployment requires embedding resilience and security from the ground up, not as afterthoughts, but as foundational principles that enable AI to generate lasting business outcomes, not just for tomorrow but for years to come.”
The discussion explored the systematic approach enterprises need to take when transitioning AI capabilities from controlled environments into production systems that must operate reliably, securely, and at scale. Rather than treating AI deployment as primarily a technical challenge, Kevin emphasised the architectural decisions required to ensure systems remain adaptable as models evolve, and critically continue to meet evolving compliance requirements across jurisdictions.
This system-level thinking reflects Stelia’s approach in helping organisations architect AI infrastructure that balances performance with operational maturity, ensuring that the foundations supporting AI capabilities can accommodate growth, change, and increasing complexity without introducing fragility into core business operations.
As enterprises move from AI experimentation to operational deployment at scale, forums like this underscore a growing recognition: success increasingly depends on whether organisations have built the architectural foundations to deploy their AI capabilities reliably, securely, and in ways that deliver sustained competitive advantage.
