"87% of AI initiatives stall because users don't adopt them. This webinar shows product leaders at high-growth tech companies exactly how UX Research closes the gap between technical accuracy and real-world adoption."
Validate your AI products with real users - before launch, not after a costly failure.
#1:
40% of IT leaders say employee skepticism is their #1 AI adoption blocker
#2:
A technically 'accurate' AI can still reach 0% adoption
#3:
A 1-week research sprint costs a fraction of a 3-month failed dev cycle
SPEAKERS
Meet Your Speakers
Ryan McGarry
UXR Manager, Akraya
Ryan leads Akraya's UX Research practice with a focus on AI product validation for enterprise technology organizations. He has conducted frontline UXR engagements with Fortune 500 Hitech and Software companies and developed Akraya's proprietary Decision-Confidence Framework.
Sid Chakravarty
Chief Revenue Officer, Akraya
Sid works directly with CPOs, CTOs, and CIOs at $200M+ technology organizations to align product investment strategy with measurable ROI. He brings the executive lens to the question of how UX Research justifies itself at the board level.
Sajeesh KV
PMO Head, Akraya (Moderator)
Sajeesh brings structure and clarity to complex product conversations. As PMO Head, he translates practitioner-level insights into strategic frameworks that resonate with both technical and business leadership.
In 50 Minutes, You'll Walk Away With:
Why technically perfect AI models still fail in the market and the exact user behavior that predicts it
The Three Pillars of AI Adoption Risk: Functional Reliability, Workflow Fit, and User Trust
Three detailed case studies: Ghost Tools, the Early Adopter Trust Gap, and Fruitless Success
Akraya's UXR Decision-Confidence Framework - the step-by-step methodology your team can implement
How to present AI launch risk to your board using human-validated evidence, not guesswork
at $200M+ revenue tech, software, and internet companies navigating AI feature launches.
Heads of UX Research and UXR Managers
who need executive-level frameworks to justify and scale their research programs.
CTOs and CIOs
responsible for AI adoption, governance, and ROI accountability across technical and non-technical stakeholders.
If you're shipping AI products and want to make go/no-go decisions with evidence instead of instinct this is for you.
KEY INSIGHT FROM THE WEBINAR:
40% of IT leaders say employee skepticism is their #1 AI adoption blocker. Not technical failure. Not security risk. Not ROI debates. That means the humans using your AI tools don't trust them enough to change their workflows. That's a UX Research problem, not a model problem.
