Context Over Compute: The Overlooked Lever for AI ROI

​Most enterprises chasing AI ROI look first at bigger models and more compute—but the biggest gains often come from a more economical, less glamorous lever: better context. Pilots stall and production systems underperform not because the models aren't capable, but because they aren't given the right information at the right time, forcing costly rework, manual review, and lost trust.

​This webinar reframes context engineering as a business decision rather than a purely technical one. We'll unpack where context investment delivers outsized returns compared to model upgrades, how to identify where context gaps are silently draining value from existing AI initiatives, and how leading teams are prioritizing context work to accelerate time-to-value.

​Key Takeaways:

​1️⃣ The Real ROI Driver: Why context—not raw model power—is often the fastest path to measurable AI returns.

​2️⃣ Diagnosing Hidden Costs: How to spot context gaps that quietly inflate rework, review, and support costs.

​3️⃣ Prioritization Frameworks: How to decide where to invest in context versus other AI improvements.

​4️⃣ Scaling Value: Strategies for sustaining ROI gains as AI initiatives expand across the business.

📍 Register here