The modern B2B buying process has dramatically evolved. According to McKinsey, the variety of touchpoints used by B2B buyers in their customer journey has more than doubled, making it more complex than ever.
Yet, despite this complexity, customers expect a seamless buying experience. In fact, over half of B2B buyers are willing to switch providers if they feel the connection or the overall experience doesn’t meet their expectations.
In response, business leaders are now under increasing pressure to orchestrate data-driven workflows across multiple teams. It’s no surprise that roles like Chief Revenue Officers (CROs), Chief Growth Officers (CGOs), and Heads of Go-To-Market Sales are among the fastest-growing positions in the U.S., with organizations seeking individuals who can unite teams and drive growth. In this new landscape, revenue leaders must focus on improving productivity, predictability, and overall revenue performance to meet these heightened expectations.
How do you get there? Spoiler alert: It might just be AI.
The Challenges: Productivity, Visibility, and Morale
One of the primary challenges facing sales teams today is seller productivity. According to Forrester, productivity is at an all-time low, with 77% of a salesperson’s time being spent on non-sales activities like CRM updates, meeting preparation, and internal reports. As a result, sellers only truly begin selling after spending a large chunk of their day on these mundane tasks.
Moreover, this inefficiency results in visibility gaps that hinder the predictability of sales outcomes. For example, Forrester’s data shows that 79% of organizations miss their revenue forecasts, and only a third of sales reps hit their targets.
This lack of predictability not only affects the bottom line but also undermines morale, contributing to higher turnover rates—an issue that can derail any sales team. With the average tenure of a CRO now at just 18 months, leaders are under immense pressure to prove their worth quickly by solving these issues.
The Opportunity for Change: AI as a Game-Changer
In light of these challenges, AI presents a golden opportunity to enhance productivity, streamline workflows, and increase sales predictability. With over 2,000 sales and revenue technology vendors using AI today, and the AI market expected to reach $1.7 trillion by 2030, the potential for growth is enormous. However, as many leaders grapple with AI FOMO—fear of missing out or fear of “messing up”—the challenge isn’t just adopting AI, but implementing it in a way that drives measurable results.
To maximize the impact of AI, leaders must focus on three core principles: quantity, quality, and context of their data. Without sufficient, objective, and bias-free data, AI tools can’t deliver actionable insights.
For instance, CRM systems often rely on manual, subjective data entry, which only represents a small fraction of the customer conversation (as little as 1% of the actual words spoken between a salesperson and a customer). AI, however, can process vast amounts of data to surface key insights that help sales teams refine their strategies and improve their performance.
AI in Action: Driving Productivity and Revenue Growth
AI-driven tools like Gong are already making a significant impact across global sales teams. With more than 4,500 customers in EMEA and worldwide, Gong uses AI to improve productivity by focusing on three key areas: process, deal visibility, and new narratives.
1. Optimizing Sales Processes
AI-powered tools can analyze every stage of the sales cycle and identify conversion rates, deal velocity, and potential bottlenecks. For instance, Gong enables sales leaders to track key metrics such as discovery win rates, conversion rates, and AE performance, allowing them to pinpoint where improvements are needed.
If, for example, a team is struggling with converting leads after the discovery stage, leaders can analyze the types of questions being asked, review individual AE performance, and adjust the sales process accordingly.
2. Understanding the Changing Buying Team
The modern buyer’s journey now involves more people than ever before. While it used to be that a single decision-maker would sign off on a deal, today’s B2B sales are increasingly involving multiple stakeholders—on average, 5.7 people.
Gong tracks interactions across all stages of the sales process to identify which touchpoints and buyer personas are most effective at closing deals.
For example, Gong found that deals involving 10 or more calls had significantly higher win rates, demonstrating that consistent communication is key to moving deals forward.
3. Using AI to Improve Deal Outcomes
AI can also help sales teams understand the power dynamics within a deal. For example, Gong’s AI platform found that deals involving C-level executives or senior leaders tend to have higher win rates. By identifying which stakeholders have the most influence over a deal, sales teams can prioritize engaging with key decision-makers earlier in the process.
A notable example of AI’s power is how Gong leveraged insights about the RevOps persona. Historically, Gong had focused on engaging Heads of Sales and Enablement, but as RevOps professionals began playing a larger role in purchase decisions, Gong adapted. After identifying RevOps as a key buyer persona, Gong made it a point to engage with RevOps in every deal over $50K, which led to a 17% increase in win rates.
New Narratives: Shifting Sales Conversations with AI Insights
As the buying landscape becomes more competitive, sales teams must constantly refine their messaging and narratives. AI tools can track the effectiveness of new sales messages in real-time. Gong, for instance, uses smart trackers to monitor key concepts like “discount,” “next steps,” and “competitor mentions” in sales calls.
This enables sales teams to understand which messages resonate with buyers and which need to be refined.
One example of this at Gong was the shift in messaging to focus on “why change” rather than just promoting the product. After training the sales team to adopt this new narrative, Gong used AI to track the adoption of the messaging. By the end of the training period, adoption had increased to 82% across teams. This data-driven approach allows Gong to continuously fine-tune messaging and retrain sales teams in a targeted, efficient way.
Conclusion: The Road Ahead for AI in Sales
The future of sales is data-driven, and AI plays a central role in transforming how sales teams operate. With AI, businesses can optimize productivity, improve visibility, and create a more predictable path to revenue growth. By leveraging AI to understand buyer behavior, refine sales processes, and adapt messaging in real-time, sales leaders can make better decisions, drive higher win rates, and ultimately build stronger, more efficient teams.
As the AI market continues to grow, it’s crucial for sales leaders to embrace AI not just as a tool, but as a core part of their strategy to unlock new levels of revenue growth. The challenge isn’t about knowing if to adopt AI; it’s about knowing how to implement it effectively. By ensuring data quality, leveraging AI-powered insights, and continuously refining processes, sales teams can navigate today’s complex buying landscape and achieve long-term success.
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