REPORT

The AI Production Paradox

Across 10 countries and 6 industries, 2,527 enterprise decision-makers told us the same thing: AI in customer communications has left the pilot stage. Organizations have made it to production, and they’re failing in ways most can’t see. This report exposes the gap between confidence and operational reality, and what the teams building AI customer communications programs in 2026 need to know.

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What you’ll learn

  • Why three in four enterprises have been forced to roll back a deployed AI agent, and why the organizations with the most mature governance programs have the highest rollback rates of all.
    What’s actually triggering rollbacks: PII exposure, hallucinations, and lack of audit trails – and why each requires a different fix.

  • How 84% of AI communications engineering teams spend at least half their time on guardrails and safety controls, and what that means to theinstead of building new customer experiences, and why that cost compounds with every new deployment.

  • Why 90% of enterprise leaders describe themselves as confident in their AI readiness, but are still rolling back at the same rate as everyone else.

  • Why infrastructure satisfaction is the single strongest predictor of AI deployment success, outranking governance investment, team maturity, and budget. 

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“The industry has assumed that better governance leads to better outcomes. But that’s not enough: If governance was the fix, the most mature teams would roll back less, not more. Our data points to a deeper issue. Engineering teams are spending most of their time building and maintaining safety systems, a lot of which their communications infrastructure should be providing, instead of focusing on improving the customer experience. That’s the guardrail tax that slows organizations down.”
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Daniel Morris CPO, Sinch

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Most AI in customer communications has already failed once.

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