From Experimentation to Production: Why Inference Is the Defining Layer of AI

The real AI challenge isn’t building models—it’s running them at scale

As AI adoption accelerates, the hard part is no longer building models—it’s running them reliably in production. In this on-demand session, The Futurum Group’s Nick Patience, alongside industry practitioners, unpacks the “production AI gap,” where promising prototypes stall under real-world demand, latency, and cost pressures—and why inference, not training, is now the defining layer of AI.

In this webinar, we’ll cover: 

• Why inference—not training—now drives real business value in AI
• The “production gap” that breaks systems under scale, latency, and variability
• New challenges from agentic, multi-step workloads: bursty demand, observability blind spots, and unpredictable costs
• How infrastructure choices shape reliability, latency, and cost across the full AI stack

Built for technical and business leaders moving from experimentation to deployment, this session offers a grounded look at what breaks in production, why, and how to align infrastructure decisions with business outcomes. Watch on demand.