Observed Signal · Sep 25, 2026 · Research Report · Source: https://martech.org/feed/ · Impact: 3/5 · Sentiment: Neutral
GTM Teams Losing Track of AI Agents
A new report from LeanData reveals that while 93% of go-to-market (GTM) teams have deployed at least one AI agent, many lack visibility into their actions. Nearly one-third of the 157 B2B practitioners surveyed couldn't state how many agents were operating on their records, and 30% found unauthorized actions without an audit trail. Data quality and AI readiness are top challenges, with 70% reporting degraded GTM execution due to poor data hygiene. This has led to issues like multiple tools contacting the same prospect and marketing sequences firing during sales interactions. The chaos stems from a proliferation of agents across embedded tools, custom LLM-based apps, and agent platforms like Agentforce, Copilot, and Gemini Enterprise. Many organizations lack clear governance, with 19% having no owner for AI strategy. The top desired solution is a complete audit trail for all record actions. This highlights the urgent need for better agent management and data governance in marketing operations.
This report highlights a significant pain point in marketing and revenue operations: the lack of visibility and governance over AI agents. It underscores the growing complexity of AI deployment in GTM processes, which is critical for MarTech professionals to understand as they scale AI initiatives.
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Key Takeaways & Evidence Grounding
- 93% of GTM teams have deployed at least one AI agent, per LeanData's '2026 State of AI Go-to-Market Readiness Report'.
- Nearly one-third of respondents couldn't specify how many agents were acting on their records; 30% found actions without an audit trail.
- Data quality and AI readiness are top AI transformation challenges, cited by 55%; 70% say data hygiene degraded GTM execution.
- 69% of respondents use AI features embedded in GTM tools like Gong, Outreach, or HubSpot.
- Only 8% of organizations described their AI operations as fully optimized.
Connected Companies & Entities
6 Entities mapped“Sixty-nine percent of respondents use AI features embedded in GTM tools such as Gong, Outreach, or HubSpot....”
“Sixty-nine percent of respondents use AI features embedded in GTM tools such as Gong, Outreach, or HubSpot....”
“Sixty-nine percent of respondents use AI features embedded in GTM tools such as Gong, Outreach, or HubSpot....”
“Agentforce is mentioned as an example of an agent platform in use....”
“Copilot is mentioned as an example of an agent platform in use....”
“Gemini Enterprise is mentioned as an example of an agent platform in use....”
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
LeanData Survey Reveals Bad Data Hinders GTM AI Success
LeanData, an AI-ready go-to-market (GTM) infrastructure provider, has released results from its AI GTM Customer Survey conducted in May 2026. Polling 157 revenue operations, marketing operations, and sales practitioners, the survey highlights a growing gap between AI deployment and performance. While 79% of respondents are currently scaling or deploying AI agents, 70% state that poor data quality is undermining their execution. Key hurdles to successful AI integration include inconsistent or incomplete CRM data (45%), undocumented business processes (37%), and siloed teams (32%). GTM professionals also expressed apprehension, with 60% fearing that AI agents would operate on inaccurate data or wrong records, indicating a need for greater control and auditability in GTM systems.
Bad Data Breaks B2B Go-To-Market Engine
The article explains how poor data quality in B2B marketing creates misleading ‘high-intent’ signals that distort pipelines, damage sales execution, and erode cross-functional trust. Outdated records, failed lead-to-account mapping, inflated intent spikes from bots/crawlers, and buyers moving to hard-to-track channels (LLMs, Slack, private groups, events, dark social) contribute to missed opportunities and inaccurate forecasts. The piece argues incremental fixes to legacy intent systems are insufficient and advocates redesigning the go-to-market (GTM) architecture around "agentic" intelligence: autonomous AI layers that synthesize buyer-level, cross-platform signals to deliver validated, actionable outreach for marketing and sales. The article frames agentic marketing as a path to restore trust and alignment across GTM functions and signals a follow-up installment on implementation details.
Marketers Say AI Uses Poor CRM Data
A Validity survey of 500 B2B and B2C marketing professionals (July 2026) finds that marketers increasingly delegate decisions to autonomous AI agents despite poor CRM data readiness. Nearly 91% say data readiness is critical for AI adoption, but only 21% consider their CRM data very well prepared. Forty-five percent already use agentic AI and two-thirds increased delegation to autonomous agents in the past year. Poor CRM data is already hitting revenue (62% said it probably or definitely cost revenue), and many marketers have acted on AI recommendations later suspected to be wrong (19% frequently, 43% occasionally). Organizational gaps — limited data governance, uneven collaboration between marketing and IT/RevOps, and unclear ownership — are cited as barriers. Respondents prioritized continuous automated monitoring, unified platforms, and third-party validation to improve CRM readiness.
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