How Does the 10-20-70 Rule Determine Success in AI Sales Transformation?

Why Are 90% of Enterprises Failing to Scale Generative AI in Sales?

Discover Boston Consulting Group’s 5-step framework for scaling Generative AI in sales. Learn why data unification between Salesforce and AWS is critical, how to implement human-centered design, and why successful AI adoption depends 70% on people transformation and only 10% on algorithms.

Read the full guide below to implement the specific 5-step framework that transforms isolated AI pilots into a scalable revenue engine for your sales team.

Recommendation

While the vast majority of businesses expect to deploy GenAI in the near future, only a minority of them have started scaling GenAI throughout their organization. Gain insight into the best ways to drive sales outcomes and manage teams by leveraging the power of GenAI. Boston Consulting Group guides sales leaders in adopting GenAI with a holistic five-step framework. Learn how to harness the potential of your data, boost business outcomes, and build consumer trust.

Take-Aways

• Speed up the adoption of GenAI, giving your AI tool access to data from multiple sources to optimize outcomes.
• Leverage tools that build trust, while embracing a human-centered design approach.
• Unlock GenAI’s potential with a holistic five-step framework.

Summary

Speed up the adoption of GenAI, giving your AI tool access to data from multiple sources to optimize outcomes.

Generative AI (GenAI) tools have the potential to benefit sales teams in dramatic ways, ranging from improving personalization to boosting account engagement. Augmented sales agents can create natural language prompts, rapidly generating plans and strategies with a GenAI “assistant” that can do everything, from suggesting next best actions to identifying new sales opportunities. In fact, GenAI is a powerful growth engine, capable of driving a 1.8x margin impact. More than 80% of businesses expect to deploy GenAI by 2026, yet only 10% of enterprises have started scaling just one GenAI application across their organization, while about half of organizations are still pilot-testing GenAI, and 40% have yet to take action.

“With the AI tracking down data and generating content, the sales agent not only prepares faster but spends less time on leg work, freeing up time for other activities.”

To accelerate adoption of GenAI to drive value, companies should prioritize people and processes, and consider adopting Boston Consulting Group’s framework for scaling AI and optimizing it with the AWS-Salesforce integration, which requires unifying business data. When you integrate Salesforce Data Cloud and Amazon Web Services, your AI can access your data, even when it resides in multiple locations (for example, in a cloud data warehouse and within Salesforce). There are numerous benefits of this integration. For instance, if a member of your sales team wanted to prep for a meeting, they could access data such as your client’s financial accounts and histories of previous interactions from multiple sources to trigger an informed response to questions such as: “What should I know about John Smith before we meet?” Embrace the “10-20-70 rule” to ensure you succeed in your AI transformation, dedicating 10% of your effort to algorithms, 20% to data and technology, and 70% to your business and people transformation.

Leverage tools that build trust, while embracing a human-centered design approach.

AI is dramatically transforming sales by enhancing and speeding up human capabilities, but successful adoption requires a human-centered approach that prioritizes both utility and ease of use. However, companies aren’t always prioritizing these aspects, and frontline workers report experiencing the following three challenges when using GenAI: ineffective training; a lack of sufficient time dedicated to learning how to use the new tool; and uncertainty regarding when it is and isn’t appropriate to rely on GenAI.

“AI revolutionizes sales by augmenting and accelerating human capabilities. But human-centered design is as much about adoption as features.”

Promote adoption and build trust by deploying tools such as Amazon Q, which gives users the ability to engage with your AI using natural language in real time. Similarly, Salesforce’s Einstein Copilot assists sales agents with carrying out research, asking the AI questions, or prompting the AI to generate content. When you integrate AWS and Salesforce, users benefit from large language models (LLMs), which Amazon Bedrock hosts, as well as predictive AI models, which they can use to serve their individual needs. These tools can help companies alleviate customer concerns about data privacy and use, as many have built-in features to build trust. For example, Salesforce’s Einstein Trust Layer protects users with features such as zero data retention and data masking.

Unlock GenAI’s potential with a holistic five-step framework.

Embrace BCG’s framework to effectively scale GenAI at your organization, by prioritizing the following:

1. Potential — When you begin deploying GenAI tools, get clear on your objectives, identify potential pain points GenAI could help you alleviate and look for ways to use GenAI tools to boost efficiency while creating more value for your customers.
2. Platform — Given that LLMs tend to train on unstructured data, it can be difficult to manage data and govern its use. Ensure you have “modular IT infrastructure, data pipelines, and robust data management practices” in place when beginning your GenAI transformation.
3. People — Ensure generative AI empowers people to unleash their full potential, augmenting human capabilities to exchange — not replace — your workforce.
4. Policy — Ensure accountability, creating policies for responsible AI (RAI). Treat RAI as an ongoing process that will adapt to reflect changing societal norms and the emergence of new technologies.
5. Operating model — Optimize your operating model, embedding GenAI into your organization by rethinking your processes — redesigning them to generate better actionable insights and drive more optimal outcomes — and organizational structure, allowing roles to become more fluid and creating space for them to evolve.

About the Authors

Adolfo Magan, Wolfgang Walther, Bryan Gauch, Stephen Robnett, Fabian Namgalies, Rupa Boddu, Raj Aggarwal, Jean-Marie Pierron, and Sandee Couch are professionals with Boston Consulting Group.