Episode
How Valiance Fixes the Enterprise AI ROI Problem
- Podcast
- Tech Talks Daily
- Published
- Jul 25, 2026
- Duration seconds
- 1813
- Processing state
not_requested- Canonical source
- https://techtalksnetwork.com/
- Audio
- https://traffic.libsyn.com/secure/techblogwriter/Tech_Talks_Network_-_Valliance.mp3?dest-id=289572
Actions
POST https://stenobird.com/v1/public/podcasts/tech-talks-daily-3579/episodes/how-valiance-fixes-the-enterprise-ai-roi-problem/transcription-requests
Idempotently request low-priority transcript generation for this episode.GET https://stenobird.com/podcast/tech-talks-daily-3579/how-valiance-fixes-the-enterprise-ai-roi-problem.md
Read the agent-friendly Markdown representation of this episode resource.
Summary
Why do so many enterprise AI initiatives begin with impressive demonstrations but struggle to produce measurable business value? In this episode of Tech Talks Daily, I speak with Dom Selvon, CTO and value partner at Valiance, about enterprise AI ROI, outcome-based consulting, build versus buy decisions, proprietary data, ontologies, and governance. Valiance is an AI-native consultancy that charges against client outcomes rather than hours worked. Dom explains why his "value partner" title is deliberate. The company begins by identifying the financial or operational result a client wants and connects its own compensation with achieving that result. Dom argues that many AI initiatives begin without a clear definition of success. The pressure to adopt AI is real, but companies frequently select technology before agreeing on the business problem, desired outcome, or measurement. He identifies three recurring mistakes. The first is framing the project around AI rather than the business need. The second is failing to establish a metric and baseline before work begins. The third is using a consulting model that rewards billable time without connecting payment to the client's result. We also discuss how generative AI is changing traditional build versus buy decisions. Companies historically bought software because custom development was slow, expensive, and difficult to maintain. Coding agents can now reduce the time and cost required to create software for specific internal needs. Dom does not believe SaaS will simply disappear. However, vendors selling convenience, workflow wrappers, or integration glue face new competition from customers who can create similar capabilities themselves. He argues that stronger SaaS positions will depend on assets a model cannot easily regener…