Bain: How Generative AI Is Forging Productivity in Sales and Marketing

The article discusses the significant impact of generative AI on sales and marketing, particularly within business-to-business (B2B) markets, where it’s poised to transform these functions dramatically. According to a Bain & Company survey of over 550 enterprises, about 40% are already using or evaluating generative AI, focusing primarily on sales, marketing, and customer support.

The rapid adoption of generative AI in these areas can be attributed to its strength in handling unstructured text and general reasoning, which are prevalent in sales and marketing. For instance, generative AI can autonomously qualify leads, support sales representatives by providing detailed product knowledge, automate the creation of requests for proposals (RFPs), and generate personalized content swiftly. These applications are crucial as they enhance productivity by enabling faster growth without corresponding increases in costs. Generative AI not only improves the capabilities of B-level sales reps but also enhances top performers, significantly reducing the time spent on administrative tasks.

Generative AI introduces numerous potential use cases, estimated to be about ten times more than previous AI generations, due to its pre-training on vast Internet-scale data. This abundance makes it challenging yet essential to select high-priority use cases strategically. The recommended approach is to prioritize based on the role, ensuring connection to measurable outcomes like improved sales rep productivity. Companies should group use cases into several “solution packages,” each focusing on a specific role within the organization. Each package should consist of 5 to 10 use cases tailored to automate or augment tasks, such as a “sales rep copilot” that might offer real-time guidance, generate sales collateral, or provide coaching.

Choosing use cases within these packages should be based on criteria like the most important business objective (efficiency or effectiveness), the time to realize value, the organization’s ability to deploy them, and the associated risks. This strategy not only limits the scope of change to fewer individuals but also creates valuable data assets that can be leveraged for other applications, enabling a quicker follow-up and enhancing the overall value of the initiative.

Early adopters of generative AI in B2B sales and marketing are gaining significant competitive advantages. These include customization, speed, and efficiency, with the development time for a proof of concept being half that of traditional AI projects. Fast deployment and reinvestment of savings make it challenging for slower-moving competitors to catch up.

However, despite these advantages, many organizations remain hesitant to fully embrace generative AI. Some wait for more proof of the technology’s effectiveness or for the maturation of expertise, while others underestimate its readiness for enterprise applications. The resistance is partly due to fears about job security among employees, highlighting the need for effective change management. Successful adoption of generative AI not only requires mastering its technical capabilities but also managing the behavioral changes necessary for integrating new technologies into existing workflows. Companies that excel in both aspects will likely achieve the greatest success with generative AI in transforming their sales and marketing functions.

How Generative AI Is Forging Productivity in Sales and Marketing

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