Outcome-Based AI for B2B Sales Performance

AI is transforming B2B sales—but is investing in it enough?

B2B sales teams are making big moves in AI, with spending growing by 70% year-over-year. According to Salesforce (2024), 80% of businesses are already testing or rolling out AI. In just three years, AI-powered applications are expected to capture 28% of the market. The opportunity is clear: AI has the potential to deliver 1.8x margin growth (BCG, 2024).

But here's the thing...Simply investing in AI isn't enough.

To get the most out of AI, B2B sales organizations should invest in Outcome-Based AI. As BCG (2024) puts it, “Sales AI transformation is 90% change management and 10% AI.” In this article, I’ll share my thoughts on how Outcome-Based AI can help sales leaders not just adopt AI, but see clear positive ROI.

“Every AI conversation needs to be an ROI conversation.” – Ketan Karkhanis, EVP & GM, Sales Cloud

Sales Performance Drivers: Connecting Outputs to Outcomes

Outcomes are the tangible, measurable results of your sales efforts. While sales teams may not have direct control over those outcomes, they can influence them by focusing on the right performance drivers. And those drivers? They’re powered by the daily sales activities performed.

• Sales Outputs: Day-to-day activities such as emails, calls, and meetings
• Sales Performance Drivers: Indicators like win rates and average deal size
• Sales Outcomes: The business results that matter, including revenue growth and quota attainment

In essence, daily outputs fuel performance, and strong performance ultimately drives outcomes.

What is Outcome-Based AI?

Outcome-Based AI is a framework for applying artificial intelligence to achieve specific business goals, like increasing sales or meeting targets. Instead of just making tasks faster, this approach ensures that AI efforts directly contribute to measurable results. Teams measuring business outcomes, like sales operations, play a key role in aligning AI with their strategic goals. Sales leaders should adopt this framework because it drives real sales success, not just operational improvements.

"The sales team of the future is humans + AI to drive sales success.” – Ketan Karkhanis, EVP & GM, Sales Cloud

Outcome-Based AI Framework

1. Start with Clear, Measurable Outcomes: Every successful AI initiative begins with a specific goal. For instance, aiming for $1M in sales for Product A over three months. Whether it's AI-generated email drafts speeding up outreach or AI-powered coaching improving win rates, it’s all about making sure your AI efforts are focused on the right targets.
2. Align Outputs with Outcomes: AI delivers real value when its outputs—like personalized email drafts or suggestions for cross-sell products—are directly tied to performance drivers like deal size or number of deals. Picture an AI Sales Coach helping reps refine their pitches and boost win rates, all to hit that $1M sales target.
3. High-Quality Inputs Matter: AI is only as good as the data it’s fed. Accurate CRM data and clear instructions are the fuel that makes AI-generated outputs—like call summaries or next-best actions—reliable and actionable. The better the inputs, the more aligned the results will be with your business goals.
4. Outcome-Based Rewards: It’s the team effort between humans and AI that drives sales success. It’s the sales reps who turn AI activities into real results. Sales leaders should set clear targets (like quotas) and empower their teams to use AI to hit those goals. And let’s be honest—rewards should follow the outcomes.
5. Measure, Measure, Measure: Tracking key metrics like win rates and deal cycle times is essential to ensure your AI is performing as expected. Ongoing reporting helps keep your AI efforts aligned with your evolving sales strategy and keeps you on track to the outcomes you’re after.

Examples of Outcome-Based AI use cases in B2B Sales

• Sales Assistant for Optimizing Visit Plans: AI intelligently plans customer visits for field sellers, focusing on high-value clients while minimizing travel time. This results in more frequent, high-quality customer interactions, ultimately leading to an increase in the number of deals generated.

Outcome: Such “Sales Buddy” AI use cases drive a 5% revenue uplift (BCG, 2024).

• Sales Assistant for Predictive Insights: By analyzing CRM data, AI uncovers hidden opportunities and recommends additional products to offer, growing the average deal size.

Outcome: Such “Sales Info Assistant” AI can add 40 cross-sell leads per rep (BCG, 2024).

• Sales Coach for Actionable Feedback: AI offers real-time, personalized coaching to refine sales pitches, equipping reps with feedback that directly impacts win rates.

Outcome: Such “Sales Coaching” AI can improve seller performance by 15% (BCG, 2024).

Total Sales = Number of Deals x Average Deal Size x Win Rate

Together, these 3 AI use cases boost total sales and help reps hit quotas faster, delivering the desired sales outcome. And these are just 3 AI use cases. In their latest research on the "future of sales AI", BCG identified 14 AI use cases across the B2B sales process, each linked to specific sales outputs and corresponding outcomes:

Maximizing AI ROI

Outcome-Based AI gives sales teams the freedom to focus on what matters—driving business results. When AI is aligned with key sales goals, companies can truly maximize their return on investment. With AI taking care of tasks like personalized outreach, sales reps can concentrate on what they do best—closing deals and hitting targets. Every AI-driven action leads to meaningful outcomes, making Outcome-Based AI the future of sales performance.

The Sales Leader’s Role in AI Transformation

Sales leaders play a critical role in making AI work. By fostering collaboration and breaking down silos, they can help teams embrace AI faster. Leaders should be the champions of Outcome-Based AI—offering clear incentives, addressing any resistance, and communicating the benefits. When leaders drive AI adoption, the entire B2B sales team hits quota faster and performs better. (BCG, 2024)

How to Get Started with Outcome-Based AI

Start by setting a clear, short-term goal—like launching a new product and reaching a specific revenue target. Look for quick-win AI use cases, such as AI-powered Sales Coaches for real-time feedback. The key is to align these AI tools with your critical sales objectives—whether it’s improving pitch preparation or negotiation skills. And don’t forget—change management is crucial. Get your sales leaders excited about AI, and offer short-term incentives to encourage rapid adoption. (BCG, 2024)

I’m a Lead Solution Engineer at Salesforce, dedicated to helping B2B companies supercharge their sales processes with the latest technology. Having transformed sales for over 100 companies across 15 countries and 10 industries, I’m passionate about leveraging AI to drive performance and revenue growth. Let’s connect! I’m always up for a chat—AI, sales performance, or anything in between. Coffee's on me! ?