What the data shows
AI agents are scaling faster than your ability to control them.
- Agent deployment doubled in 2025: As enterprises moved from pilots to production across core workflows.
- Costs jumping 10× across stacks: Real-world usage exposes behaviors and feedback loops not seen in testing.
- Tens of thousands lost in days (without detection): Caused by misconfigured or looping agents continuously at scale.
Get the research: Discover why 40% of agentic AI projects may be cancelled by 2027…
Enter our brand new eBook: ‘The Financial Blind Spots in Autonomous AI.’
Our latest eBook reveals how autonomous AI systems create hidden and compounding costs at machine speed, long before finance teams ever spot them.
Most enterprises can’t see it happening until it’s already too late.
Now’s your chance to get ahead…
What’s inside:
- Why 40% of agentic AI projects may be cancelled by 2027: Escalating costs, unclear ROI, and weak governance are converging, turning promising pilots into financially unsustainable deployments.
- A six-layer framework for governing agent economics: Designed for machine-speed decisions, this model embeds financial controls directly into agent execution.
- The legal precedent that makes this your responsibility: Courts are increasingly treating autonomous agent decisions as organizational actions, meaning liability for spend.
- Why agent costs jump 10× from prototype to production: Testing environments fail to replicate real-world feedback loops, usage patterns, and edge cases, so cost escalation only becomes visible once systems are already spending.
As AI agents become embedded across core business processes, financial governance needs to evolve just as quickly.
Organizations that fail to adapt risk unmanaged spend, unclear accountability, and erosion of business value.
This report provides a structured approach to understanding (and controlling) those risks.
👉 Enter your details in the form above and start to establish control over your autonomous AI spend.
