Observed Signal · Jul 15, 2026 · Research Release · Source: https://martechseries.com/feed/ · Impact: 3/5 · Sentiment: Neutral
Kana: 70% of Enterprises Run AI Agents in Marketing
Kana published The Agentic Divide, a survey of 225 senior marketing, data, and AI leaders at U.S. enterprises with $250M+ in annual revenue, finding widespread deployment of custom AI agents for marketing tasks but persistent uncertainty about ownership and governance. The study reports that 70% of respondents run AI agents in production while only 3% report no marketing AI use. Respondents express high self-reported readiness for governance and data infrastructure, yet identify data governance and data quality as major obstacles. Many expect AI agents to take on a substantial share of routine marketing decisions in the next two years. Kana’s CEO Tom Chavez highlights the gap between rapid adoption and untested governance.
Study shows high production adoption of AI agents in enterprise marketing and highlights governance and ownership gaps that could affect scaling, vendor selection, and organizational risk—relevant to MarTech strategy but not a platform-level policy change.
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Key Takeaways & Evidence Grounding
- Kana released The Agentic Divide, a study of 225 senior marketing, data, and AI leaders at U.S. enterprises with $250M+ annual revenue.
- 70% of respondents said they already run custom AI agents handling real marketing tasks in production.
- Only 3% of respondents reported no marketing AI use at all.
- Across the sample, 40% said the Chief AI Officer should own agentic marketing strategy and execution; AI leaders favored the CAIO at 52%.
- 82% expect AI agents to handle at least one-third of routine marketing decisions within two years; 46% expect a majority.
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Ontology Mapping & Concepts
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Enterprise AI Agent Ownership Unclear Despite Widespread Deployment
A new survey of 225 senior enterprise leaders by Kana reveals that 70% already run custom AI agents for marketing, yet ownership and maintenance responsibilities remain ambiguous. While 85% of IT professionals (per Ivanti) claim a named owner exists for every AI agent, only 42% say ownership is clear. The article argues for splitting ownership: central IT/AI teams should manage access, data, and models, while marketing owns instructions and output quality. It draws parallels to software maintenance history and recommends assigning specific accountability across existing roles.
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