By 2026, B2B sales organizations using embedded GenAI sales technologies will reduce the amount of time spent on prospecting and customer-meeting prep by over 50%, according to Gartner.
As Chief Sales Officers (CSOs) update technology plans to account for this new technology, we spoke with Dan Gottlieb, Senior Director Analyst in the Gartner Sales Practice, to discuss how sales leaders should prioritize generative AI projects.
Journalists who would like to speak with Dan regarding this topic can contact Matt.LoDolce@Gartner.com. Members of the media can reference this material in articles with proper attribution to Gartner.
Q: How should CSOs pivot existing technology plans to now include generative AI?
A: CSOs must realize that incorporating generative AI into sales isn’t the ultimate goal. Rather, it is a means to an end, where the end is sales outcomes. A comprehensive plan with this in mind will proactively answer questions from CEO/CFO/COO partners about increased productivity expectations, cost reductions and expected revenue growth.
When communicating these plans, CSOs must discuss how generative AI can drive strategic value and fit into the company’s future, so it is key to focus on its transformational potential. CSOs have three short-term to mid-term opportunities for generative AI to highlight this potential in technology plans:
- Turn data into atomic insights: Synthesizing different sources of unstructured data, creating full narrative insights. Atomic insights are core inputs for more dynamic generative AI use cases, e.g. synthesize earnings and meeting transcripts, summarize customer service logs.
- Facilitate collaboration between sellers and AI: Natural language interfaces enable sales organizations to interact with sales tech apps in new ways to execute deal-related activities, e.g. assemble an account brief, draft an RFP response, craft a business case.
- Compound productivity gains from automation: Sales tech apps compound productivity by autonomously completing creative and analytical selling tasks in succession on behalf of users, e.g. update CRM records, recommend next-best-action activities, conduct account and prospect research.
Q: What are some use cases CSOs can utilize to take advantage of these opportunities?
A: Understanding generative AI capabilities starts by learning the types of tasks that it is capable of completing, such as text summarization, sentiment analysis, answering questions, and simple analytics. It starts to get overwhelming when CSOs apply those tasks to the wide range of B2B sales use cases.
One of the first use cases that comes to mind is generative value messaging. Being able to help a seller customize value messaging narratives for each buying team using customer intelligence is key for CSOs as deal planning continues to evolve.
Beyond that, generative AI can be used to interpret data including forecast management, or decision-making support for sales strategy and planning by simulating outcomes based on actions taken or events.
Finally, CSOs can set up AI-seller assistants using generative AI that can augment sellers with automated routine sales engagement tasks and recommend next-best-actions, or conversational reporting, data synthesis and interpretation.
As vendors across the market integrate generative AI technology into sales workflows, CSOs can expect the applications for B2B sales use cases to expand exponentially.
When evaluating a generative AI use case, synthesizing all of the complexity surrounding the data, talent and process requirements for sales, then ranking or prioritizing them, requires a new set of criteria for evaluation that may provide unforeseen hurdles for CSOs.
Q: Which use case should CSOs focus on first?
A: For generative AI to deliver productivity gains, frontline employees first need to be willing to use and be influenced by the technology. Without frontline adoption, it will be difficult for a sales organization to discern generative AI’s impact on headcount, territory planning or compensation.
Because of this, generative value messaging should be an early focus of sales leaders when implementing generative AI due to its high value impact and relatively low time to value investment.
This is why Gartner predicts that B2B sales organizations using embedded generative AI sales technologies will reduce the amount of time spent on prospecting and customer-meeting prep by over 50% by 2026.
Furthermore, Gartner also predicts that sales teams using generative AI to generate proposal and bid responses will spend an average of approximately 16 hours per RFP, down 40% from 27 hours per RFP without sacrificing win rate by 2026.
Both of these generative value messaging examples are already core components of a well-oiled sales function, and generative AI can help be the real differentiator for a CSO looking to separate themselves from their competitors.
Clients can read more in “Generative AI Strategic Planning Essentials for B2B Chief Sales Officers.”
