How AI Is Rewiring Sales: Quota, Retention & What's Actually Working

The panel discusses how AI is transforming B2B sales, focusing on revenue growth rather than simply cutting costs. While AI adoption can be challenging, with initial rollouts being "bumpy," the ultimate goal is to enhance sales processes and customer engagement. One key insight is that AI adoption in sales is often more complex than in service or operational areas. This is because sales heavily relies on human interaction and data quality in sales is often less structured. However, AI can significantly improve lead qualification, follow-up, and personalization, especially for lower-quality inbound leads that might otherwise be ignored. For example, Salesforce utilized AI to curate, enrich, and follow up on a large volume of low-quality web leads, leading to direct revenue that would have been missed. Similarly, Mangamit, a vertical SaaS company, leveraged AI during a hackathon to automate the process of fixing customer-uploaded logos and applying brand colors, turning a multi-hour manual task into a minute-long automated one. This instant value for customers, even if initially surprising, is a significant benefit. The discussion also highlights the importance of a strategic approach to AI implementation. Simply providing AI tools is not enough; companies need to invest in training and education to ensure their sales force understands how to effectively use these tools in their daily workflows. Salesforce, for instance, emphasizes that sellers want to sell, and if given the right tools and strategy, they will adapt. Momentum, an AI-native company, uses AI to empower its non-English speaking SDRs and AEs in Argentina, enabling them to write sequences and personalize outreach, thus democratizing language and supercharging their efforts. However, even in AI-native companies, workflows often remain "human-assisted," emphasizing the current stage of AI development where human oversight is still crucial for personalization and breaking through noise. A significant challenge in AI rollout is internal resistance, particularly from legal teams, CIOs, and even sales teams who fear job displacement or are reluctant to change established workflows. CIOs, for instance, are cautious about data security and intellectual property concerns, as a data breach due to AI misuse could have severe consequences. To overcome this, companies need strong internal champions who are committed to the cause and can explicitly communicate how AI will change workflows and demonstrate the tangible benefits. For Momentum, quantifying the time saved per deal and showing how AI integrates into existing tools like Slack helped overcome resistance. The panel also stresses the importance of analytics to prove AI's effectiveness and identify areas for improvement in agent processes. The discussion also delves into the impact of AI on sales quotas and team structure. While some might assume AI will lead to a doubling of quotas due to increased efficiency, the panelists caution against this simplistic view. Instead, they suggest that AI should be used to elevate average performers to top-performer levels by providing better tools and support. Mangamit, for example, is not raising quotas in the coming year, opting instead to focus on making AI truly native to their team's workflows, allowing them to reap the benefits of increased efficiency without immediate pressure to hit higher targets. The consensus is that AI necessitates a more holistic approach, requiring a stronger operational backbone with more RevOps and Ops personnel to manage the agents and data. This allows sales teams to be more efficient, but only if the underlying systems are well-orchestrated. The goal is not just to increase sales but to understand the broader impact on the entire business, including operations and customer service. Finally, the panel touches on AI's role in customer retention. While AI can enhance outreach, the key is to personalize interactions and provide value relevant to the customer. It's not about traditional marketing drips but about building digital relationships through surveys, questions, or thought leadership, allowing humans to focus on closing deals. Salesforce, for example, uses AI to maintain fresh relationships with existing customers, ensuring consistent follow-up and feedback collection, especially for seasonal businesses. Momentum, by listening for moments of customer dissatisfaction, helps CSMs proactively address issues before they escalate, offering a significant advantage in retention. AI can also streamline post-sales processes, such as translating support calls and integrating data into CRMs, which can have a huge impact on customer success and retention.