AI looks affordable until the invoice arrives — and by then, most teams are already over budget. In this episode, we break down exactly why AI costs spiral after launch and what smart leaders do to stay ahead of the bill.
What You'll Learn
- Why unit costs for AI are falling but total infrastructure bills are still skyrocketing toward $1.7 trillion
- The hidden cost drivers behind most AI overruns — data prep, integration, and ongoing maintenance
- Why 60% of AI projects are predicted to be abandoned by 2026 and how to avoid being in that group
- How pricing models from Microsoft Copilot, Intercom, and AWS Bedrock differ — and why the model you choose shapes your long-term spend
- Real-world ROI examples, including a healthcare automation case that saved 6,700 hours monthly and delivered 30% ROI in year one
Podcast Agenda
- 00:00 - The AI Invoice Shock No One Sees Coming
- 00:25 - The $3.3 Trillion Paradox: Cheaper Tokens, Bigger Bills
- 01:04 - What Actually Drives Costs After Launch
- 01:44 - Pricing Models That Change Everything
- 02:08 - Real ROI: What Winning Use Cases Look Like
- 02:40 - Adoption Is the Cost Driver You Can Control
- 03:15 - Budget for the System, Not Just the Tool
