Report Finds Data Quality Hinders Agentic AI in GTM
A new report on the state of agentic AI in B2B go-to-market strategies for 2026 reveals that while 58% of leaders see potential for efficient execution, data quality remains a major bottleneck. The RevSure report stresses the need for companies to strengthen their underlying data layers to effectively use AI for tasks like analyzing intent signals and automating operations.
- The RevSure report highlights that while 76% of organizations are deploying or implementing agentic AI, many lack the foundational data infrastructure to support it. This disconnect is a primary reason why 47% of GTM leaders cite lead and data quality as significant barriers to efficient execution. - Signal-based GTM strategies are moving companies away from static lists toward prioritizing accounts based on real-time buying behaviors, such as hiring patterns or new funding events. This approach, which complements Account-Based Marketing (ABM), helps teams focus on accounts showing active intent, reportedly leading to a 3x higher meeting booking rate. - For B2B companies selling API-first products, a developer-focused strategy that includes deep technical content, open-source tools, and excellent documentation is crucial for building initial credibility and driving adoption. The sales motion often evolves from this product-led growth to a more traditional enterprise sales model as the customer's usage and needs expand. - In India's HR tech market, which reached over $1.2 billion in 2025, AI-powered recruitment and workforce analytics are key trends. 69% of Indian recruiters now use data analytics, and 63% rely on AI tools to improve hiring efficiency and quality. - Recent funding in the Indian HR tech startup scene includes a ₹7 crore seed round for All Things People (ATP), a platform focused on employee analytics and continuous listening. This investment reflects a broader trend, with Indian HRTech companies raising $379M in 2025, a 102% increase from the previous year. - As leaders scale their GTM teams, a common failure point is not evolving from solving individual problems to building systems and processes. A key transition involves hiring experienced sales leaders and establishing a repeatable sales model with a clear management operating rhythm to ensure consistency and scalability. - Poor data quality directly impacts AI model performance, with 89% of leaders whose companies use AI reporting inaccurate or misleading outputs as a result. This highlights the necessity of investing in data cleansing, unification, and governance before expecting reliable results from AI-driven GTM initiatives. - The role of HR is shifting from a purely administrative function to a strategic partner, driven by workforce analytics. Predictive analytics are now being used to forecast turnover, identify skills gaps, and inform headcount planning, enabling HR to contribute directly to executive-level business decisions.
