Maximizing Returns with AI-Enabled Selling – A Strategic Blueprint

The Compelling Economics of AI-Enabled Selling Come with a Caution

Quantitative studies and industry reports are beginning to articulate a compelling case for adopting AI in sales operations. According to the "Salesforce State of Sales Report," businesses embracing AI have seen a 50% reduction in time spent on data entry tasks by sales reps, a 35% boost in customer satisfaction scores, and a 30% increase in close rates for sales teams. The result: “83% of sales teams with AI saw revenue growth in the past, versus 66% of teams without AI.”

These are compelling results, especially given how recently these technologies were deployed. But they only tell part of the story. Security, training, and trust are formidable challenges according to sales professionals and they need to be taken into account in order for companies to receive the full value of their investment.

Similar concerns are forefront in the minds of the buyers of a product or service and must be considered when adopting AI technology. In fact, “Only 55% of business buyers trust AI to be as accurate as a human,” according to the Salesforce report. There are several likely reasons causing their concern.

• First, AI accuracy heavily depends on the quality of the data it is trained on. If the data is flawed, biased, or unrepresentative, the AI’s performance will suffer and so will the recommendations and advice given to buyers.
• Secondly, business buyers may be wary of over-relying on technology without human oversight, fearing that AI lacks the intuition, contextual understanding, and ethical judgment that humans bring to decision-making.
• Finally, AI systems often operate as "black boxes." This lack of transparency makes it difficult for users to understand how decisions are made, leading to skepticism about the reliability of the results.

The Path Forward

I’m reminded of the Hippocratic Oath: First, do no harm. Sales professionals have invested significant time and energy building relationships with their buyers. They cannot afford a costly misstep through improper or inadvertent usage of a new technology, no matter how compelling. At Chief Outsiders, we advise clients to adopt an approach like the one below.

1. Clearly Define Objectives and Use Cases: Before integrating AI, clearly define the specific objectives and use cases where AI can add the most value. This might include lead scoring, sales forecasting, customer segmentation, or personalizing outreach. A well-defined purpose ensures that the AI solution aligns with business goals and provides measurable outcomes, enhancing the likelihood of success and adoption.
2. Ensure Data Quality and Integration: AI models rely on high-quality data to perform accurately. Poor data can lead to unreliable AI outputs, which can undermine trust and effectiveness within the sales team and customers. Invest in cleaning, organizing, and integrating your data across systems to ensure it is accurate, relevant, and accessible to your AI tools. Consider implementing data governance practices to maintain quality.
3. Focus on User Training and Change Management: Successful adoption of AI depends on user buy-in. Training and support help sales teams understand the benefits, reducing resistance and improving the integration of AI into daily operations. Provide comprehensive training for your sales team on how to use the AI tools effectively and how these tools can enhance their workflows.
4. Prioritize Transparency and Explainability: Choose AI solutions that offer transparency and explainability in their outputs. Sales professionals are more likely to trust and use AI recommendations if they understand how those recommendations are made. This transparency helps build confidence in AI's capabilities for both sellers and buyers.
5. Start Small and Scale Gradually: Starting small allows you to identify potential issues, adjust strategies, and demonstrate value without disrupting the entire sales operation. A phased approach helps to build momentum and refine the AI integration process. Begin with a pilot program or a limited rollout to test the AI technology in specific areas of the sales process. Measure results, gather feedback, and iterate before scaling up.

Conclusion: AI-Enabled Selling as a Strategic Imperative

AI-enabled selling isn't an option—it's a strategic imperative. The operational efficiencies, enhanced customer insights, and improved decision-making afforded by AI translate into real competitive advantages.

If you have not started down the path to AI-enabled selling, you should. And if you have started, chances are you overlooked some of the key tenets for success.

According to the Salesforce report, 41% of the sales teams surveyed believe that they have “fully implemented AI”. Yet most of them have not trained their employees or set ethical standards for usage.

Implementing a new technology is relatively easy. In and of itself, it has no inherent benefit to a company. The benefits come with enablement and usage. And the journey begins with a commitment—an investment not just in technology, but in data, people, business processes, and a commitment to transparency for all consumers of AI content.

Read the full series on AI-Enabled selling

• What is AI-Enabled Selling and Why is it Important?
• Navigating the AI-Enabled Selling Software Landscape

Originally published on the CEO blog by Dan Lackner