There is tremendous buzz about artificial intelligence (AI) and its power to transform business, and the Sales function is no exception. Lately articles have reported sky-high ROI from AI designed to boost field and inside Sales force performance. From all the success stories, one might conclude that most sales forces are well on their way to realizing value from AI, and that the going is easy. The truth is that only a small number of sales forces are using AI successfully. Some sales forces are stuck in multi-year efforts to build systems that have yet to see the light of day. And most are yet to take even the first step. Firms trying to implement AI systems to drive sales will need patience, and should keep these four factors in mind.
There is tremendous buzz about artificial intelligence (AI) and its power to transform business. Sales is no exception. AI is associated mostly with online selling at companies such as Amazon and Netflix. Lately articles have reported sky-high ROI from AI designed to boost field and inside sales force performance. From all the success stories, one might conclude that most sales forces are well on their way to realizing value from AI, and that the going is easy.
The truth is that only a small number of sales forces are using AI successfully. Some sales forces are stuck in multi-year efforts to build systems that have yet to see the light of day. And most are yet to take even the first step.
Consider one key application of AI in sales: increasing salespeople’s productivity in finding, acquiring, and monetizing customers. (There are many other applications, but we will focus on this one.) AI promises to help salespeople generate and focus on higher-quality leads, gain insight into customer needs and preferences, coordinate selling with other channels (such as online and partner organizations), find opportunities to cross-sell and upsell, prevent customer defections, and more. The reported results are impressive: higher sales, lower costs, big productivity gains, and a better sales environment.
The potential of AI to transform selling is huge. And the benefits are real. But the success stories you read about rarely offer enough insight about the challenges companies must overcome to realize the benefits. Consider four major challenges and some surprisingly simple but often missed solutions.
Bringing AI models to life requires new roles with specific skill sets. Team members from sales are critical for giving voice to the sales force, product, and customer needs. The team needs big data experts, data scientists, machine learning engineers, and more.  To stitch all this together, the team also needs a boundary spanner–a person who understands both and sales and technology.
Such cross-functional AI teams are generally most effective when they come out of grassroots efforts, not from top-down directives. For example, when a technology company developed an AI system for one of its sales teams, the project champion came from within sales. The individual worked to cultivate a common belief and purpose for AI-enabled selling, bringing together more than 50 people across five business units.
AI systems work with vast amounts of data.
