Annual Report
Thought Leadership

State of
Enterprise AI
2025

The shift from experimentation to production. What's working, what's failing, and where enterprises are investing next.

72% Have AI in production (up from 41% in 2024)
3.2x Average ROI for governed AI vs. ungoverned
$2.1M Average enterprise AI spend (2025)
67% Cite governance as top concern

Methodology

Survey of 500 enterprise AI leaders across financial services, healthcare, insurance, telecommunications, and government. Q4 2024 - Q1 2025.

02 / 04

The production pivot is happening

2024 was the year of POCs. 2025 is the year of production. Enterprises are moving past experimentation - but facing new challenges.

72% AI in production
87% Increased AI spend
54% Using agents

Top AI Investment Priorities (2025)

Governance
67%
Observability
58%
Cost optimization
52%
Agent infrastructure
48%
Model capability
34%

The Governance Shift

For the first time, governance outranks model capability as a top investment priority. Enterprises have learned that better models don't help if you can't deploy them safely. Infrastructure is now the bottleneck.

03 / 04

What's changing and why it matters

1

Agents Going Mainstream

54% now have agents in production (up from 12% in 2024). But 78% report agent governance as "inadequate." The tooling hasn't kept pace with adoption.

2

Regulatory Pressure Intensifying

EU AI Act enforcement begins August 2026. 89% of enterprises are "not fully prepared." Gap between current state and compliance requirements is 12-18 months of work.

3

Cost Optimization Becomes Critical

Average enterprise AI spend: $2.1M/year. 63% report "unsustainable" cost trajectories. Trust Cascade architectures reducing costs 40-60% for early adopters.

4

Hallucination Detection Non-Negotiable

Top production concern: AI reliability. 71% have experienced customer-facing AI failures. Real-time hallucination detection becoming standard requirement.

5

Build vs. Buy Shifting to Partner

60% moving to hybrid models. Pure build too slow. Pure buy too rigid. Partnership with knowledge transfer emerging as preferred approach.

Winners vs. Laggards

Top performers invest 25%+ of AI budget in governance and observability. Laggards spend 90%+ on model capability. ROI difference: 3.2x.

Industry Leaders

Financial services most mature (78% in production). Healthcare catching up fast (68%). Government lagging (42%) but accelerating.

04 / 04

What to do now

Based on what's working for top performers:

1. Front-Load Governance

Allocate 20-25% of AI budget to governance from day one. Organizations that wait until production to add governance see 4-8x higher costs.

2. Start EU AI Act Prep Now

August 2026 is 18 months away but compliance requires 12-18 months. Start gap analysis immediately. Build documentation infrastructure.

3. Implement Trust Cascade

Route decisions to cheapest sufficient intelligence. Early adopters see 40-60% cost reduction. Most organizations still route everything to expensive models.

4. Add Hallucination Detection

Real-time reliability monitoring is table stakes. 71% have had customer-facing failures. Detection catches issues before customers do.

5. Build Agent Governance

Agent adoption outpacing governance infrastructure. Establish identity, lifecycle, and accountability frameworks before scaling further.

6. Consider Partnership

Hybrid approach (60% adoption) delivers fastest time-to-value with best optionality. Pure build is slow. Pure buy is rigid. Partner for expertise.

The Bottom Line

Enterprise AI is maturing rapidly. The winners aren't those with the best models - they're those with the best infrastructure. Governance, observability, and cost optimization are now competitive advantages.

The gap between leaders and laggards is widening. Organizations that invest in AI infrastructure now will be positioned to capture value. Those that wait will struggle to catch up.

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Detailed findings and industry-specific analysis.