“The most advanced organizations also fail; they see failures sooner”: many companies are already having to cancel their AI customer service tools

Sinch challenges the idea that most companies are stuck in pilot mode when it comes to AI
AI rollbacks are actually a sign of strong governance, not weak performance.
Investments in AI will continue to increase in 2026

According to new data from Sinch, AI customer service deployments are already widespread, but many organizations are struggling post-launch, with three in four (74%) having canceled or stopped at least one of the AI communications agents they have deployed for governance reasons.

This is because around three in five companies (62%) already have AI customer communications agents in production.

With this data, Sinch counters the common narrative that most businesses are still stuck in pilot mode.

Companies continue to experience problems with AI well after pilot phases

Instead, the report says the biggest challenge is operational reliability once AI agents are actually deployed at scale. Sinch says the higher recovery rate among mature organizations might actually be a sign of stronger governance: in other words, they detect and stop failures earlier.

“Higher restoration rates reflect better monitoring and control, not lower performance,” explained CPO Daniel Morris.

“Engineering teams spend most of their time building and maintaining security systems, which their communications infrastructure should largely provide, instead of focusing on improving the customer experience,” Morris added, highlighting the emergence of a “guardrail tax.”

In the future, investments in AI go far beyond just paying for the latest models. Data now shows that companies are investing more in trust, security and compliance (76%) than in AI development itself (63%).

Nearly all respondents (98%) plan to increase investments in AI in 2026, but a much bigger change is at stake: 86% are evaluating or considering new communications providers and 55% need to create custom infrastructure for a multi-channel context.

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