AI Revolutionising B2B Research: A Shift from Legacy Models

Gartner’s stock price plunge and G2’s diminishing traffic are indicative of a major transformation in the B2B research industry. The traditional systems—built on gated reports, pay-to-play models, and vendor-biased reviews—are rapidly being upended. This shift is primarily driven by AI technologies, with large language models at the forefront, reshaping how businesses engage with research. Buyers and sellers alike are recalibrating their strategies in response to a new landscape where access to data is instantaneous, personalised, and driven by real-time insights.

For decades, legacy firms like Gartner and Forrester dominated the research space, offering in-depth, but often slow-moving insights in exchange for high costs. Their traditional grid-based analyses, though respected, were perceived as rigid and sometimes outdated, providing a one-size-fits-all perspective. Meanwhile, review sites like G2 and TrustRadius aimed to offer faster insights but often faced criticism for shallow or vendor-incentivised content. While these platforms catered to buyers looking for swift answers, the reviews were often generic and lacked personalisation. Both models, while serving their purpose, have come to feel increasingly inadequate as the industry evolves.

Buyers today demand more from their research tools. The rise of AI-driven platforms reflects a shift in expectations: information must be fast, tailored, and integrated with peer reviews, all without the heavy influence of vendors. Traditional sales calls and vendor presentations are no longer desirable during the early stages of the buying process. A major change is evident: buyers prefer to gather 80% of their information before engaging with a seller. This has resulted in a steep rise in the demand for decision engines that empower buyers to do their own research in real-time, unencumbered by the noise of outdated models.

AI-powered platforms are addressing these pain points. By delivering instant, personalised answers and creating tailored recommendations, these technologies are challenging the dominance of traditional research firms. Large language models are particularly transformative, enabling AI systems to scan vast amounts of data quickly, providing up-to-the-minute insights and playbooks without the bottleneck of human oversight. The result is faster, more relevant research, cutting through the noise of traditional, vendor-centric approaches.

For sellers, this transformation represents both a challenge and an opportunity. Customer acquisition costs continue to rise, and potential buyers are increasingly resistant to early sales calls. With buyers now equipped with AI-powered research tools, sellers must adapt by providing value at earlier stages in the buying process. Simply put, the only path forward for sales teams is to help buyers conduct better research and make more informed decisions. Sellers need to move beyond generic content like SEO-optimised eBooks and instead offer real buyer enablement resources such as detailed playbooks, personalised vendor comparisons, and tools that foster collaboration with potential buyers.

Platforms like Zeer AI are already integrating these shifts into their go-to-market strategies. Through their Buyer-Led Agentic platform, Zeer is revolutionising B2B research by creating daily pulses that allow buyers to share their most pressing concerns directly with AI agents. These agents then provide instant, tailored insights, including vendor leaderboards and one-click access to personalised RFPs. The AI agents continually scan fresh content, ensuring that the insights buyers receive are always up-to-date and relevant. This constant stream of personalised data positions Zeer’s platform as a valuable tool in the decision-making process, offering buyers the resources they need to make better-informed decisions.

Zeer’s platform incorporates human-curated research through its network of experts, agencies, and consultants. This network aids in the identification of ‘soft intent’—when a buyer is interested in a solution but not yet ready to engage. Once a buyer interacts with a solution that resonates with them, the system seamlessly transitions from soft to hard intent, prompting a meeting with the vendor. This soft intent to hard intent progression streamlines the sales funnel, making the buying process more efficient and collaborative.