
What happened
Twilio's marketing team reduced account research and personalized content creation for a single campaign from over two weeks to under a day, and now runs as many as 15 account-based campaigns a quarter, up from three.
Why it matters
The gain came not from the model alone but from unglamorous groundwork — human taste, data hygiene, governance and integration — which the CMO says most companies skip, so their AI pilots stall between demo and production.
Summaries like this, every morning.
Twilio's marketing results arrive against a wide gap between what vendors promise and what enterprises run. The CMO points to surveys showing 86% of companies believe customers are satisfied with their AI-powered service, while only 51% of customers agree. Deloitte found just 25% of organizations have moved 40% or more of their AI pilots into production, and one survey of data leaders found only 8.4% say their data is ready for production AI.
The CMO describes enterprise AI adoption in three phases: personal productivity, team workflows, and autonomous end-to-end processes. Twilio places itself in phase two, and argues that the industry has condensed all three into one story sold as though phase three already exists. The company's French localization attempt, where AI tools added berets onto every person, is offered as an example of why human taste must come first.
The piece also cites the 2024 CrowdStrike outage, triggered by a faulty software update that disrupted millions of Windows devices worldwide, as a reminder of why quality controls underneath enterprise technology matter. Twilio sells infrastructure for customer engagement in the AI era, and the CMO's advice is to resist overpromising and show customers running the technology in production.
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