Artificial intelligence is showing up in every corner of business operations with the promise of “streamlining operations” and “fueling growth.” Among B2B sales professionals, AI is causing as much excitement as it is anxiety. It’s true that AI is shifting the way we view traditional sales roles, but the reality about this technology is nuanced—and promising.
The most successful B2B companies aren’t using AI to replace their sales teams. Instead, they’re combining human expertise with AI-driven insights, embracing a hybrid approach and seeing up to 50% more revenue from their sales efforts.
For sales professionals wondering about their future in an AI-powered world, the evidence points to transformation rather than displacement.
Why AI and Ecommerce Enhance Sales
AI is great at many things, but having strong (human) relationships isn’t one of them. Connecting with people, building trust, and understanding the nuance of what customers need are all things that underpin great B2B sales skills. According to McKinsey, only about one-third of sales-related tasks are highly automatable in B2B environments. It’s the administrative work that’s easiest to offload to our robot coworkers, particularly the gathering and analyzing of digital information.
AI is remarkably good at augmenting human capabilities because it’s tireless, accurate, and excels at managing data. AI-powered search and recommendation systems like Coveo analyze customer behavior patterns and predict which products a buyer might need next.
This is information that sales representatives can use to inform what they focus on when speaking to a prospect. The AI provides data-backed insights that the rep uses to create a more meaningful conversation. This can happen at any point of a very complicated B2B buying journey, so it’s important for a sales rep to be prepared when a prospect is ready to engage.
Per McKinsey, 70% the of B2B buyers in decision-making roles now prefer remote and digital interactions, though in-person interactions haven’t disappeared entirely. In a recent article, McKinsey wrote, “Forty percent of customers using a new supplier prefer to buy only if they’ve met the sales rep in person. An opportunity for in-person engagement when customers prefer it is an interaction option that most sales organizations need to provide.” So, while it’s true that AI is everywhere, it’s also true that human connection remains an important part of the sales process, even as digital tools become more sophisticated.
The Hybrid Sales Model in Action
Ahybrid sales model combines human expertise with AI and automation. The latter handles processes like data analysis and lead prioritization, while the former focuses on strategic relationship-building and hands-on sales activities like face-to-face meetings.
In this hybrid scenario, AI supports human-focused work by increasing productivity, reducing errors, and helping staff become more efficient at finding the right information quickly. This leads to more sales because, among other things, it enables a sales development representative (SDR) to find and focus on the highest-quality prospects.
Here’s a breakdown of how a hybrid B2B sales model combines human and AI elements in a way that makes both more impactful:
- Data analysis for lead prioritization: AI is exceptionally good at processing huge amounts of data. AI tools help sales reps by logging and processing customer data and prioritizing leads. AI can transcribe meeting notes, then make those notes available for searching and analyzing. Humans use the insights generated by AI to better understand what prospects offer the most value. They step in when a lead is already identified and scored – so time can be spent on building relationships with the most promising prospects.
- Automation for time-intensive tasks: AI never gets bored. The technology handles lead qualification, appointment scheduling, note-taking, follow-up reminders, and basic customer queries. According to McKinsey, sellers only spend about 36% of their time actively selling, so offloading tasks like these adds up to many hours per week saved.
- Predictive analytics for understanding buying patterns: Predictive analytics tools use AI and machine learning to analyze data and predict next-best actions for SDRs to take. AI tools gather information more efficiently and accurately than humans can by tracking customer interactions across all channels. Generative AI then provides insights and guidance that sales teams can use to spot buying patterns and flag opportunities they might otherwise miss.
- Find information quickly: AI search helps users on both the buying and selling side of the B2B buying journey find information much more quickly than traditional search. Machine learning makes AI search tools even more effective since it learns users’ search patterns and customizes the results based on past behavior. GenAI summarizes results from the documents in your knowledge base and helps users locate the right document quickly. All of this equals less time spent hunting for the information and more time selling.
On that last point, Coveo’s platform supports SDRs with AI-powered service features that turn site search into a secret weapon – at least when it comes to saving time. As-you-type suggestions, also called “query suggestions,” for example, guide users to vetted information in a natural way. Other features like personalized search results, dynamic filters that use machine learning to display relevant categories based on user context, and generative experiences all make it much easier for sales teams to find important information quickly.
The AI Advantage in the Buyer Experience
B2B buyers have high expectations, yet according to recent data from Forrester, 81% of them expressed dissatisfaction in at least one area during their most recent purchase process. They may use ten or more channels during the B2B purchasing process, and this can go awry without a way to stitch these channels together. Buyers want their experience to be a good one – and by “good” we mean seamless and personalized.
B2B’s multichannel buying reality makes it difficult to delegate sales entirely to AI – but who would want to do this? B2B buying demands a sophisticated approach to managing customer expectations, one that relies on human expertise, particularly once buyers get to the end of their self-service journey.
So while it’s true that two-thirds of B2B buyers prefer remote and digital self-service interactions, it’s also true that this doesn’t eliminate the need for human interaction. When customers do engage with sales representatives, their expectations are high. Research from PwC shows that 72% of B2B buyers expect personalized engagements with sales reps, underscoring the need for a data-backed hybrid approach.
AI helps sellers provide a better CX by adjusting content automatically so that messaging and recommendations shift based on the customer’s industry, role, and stage in the buying journey. Automated A/B testing continuously optimizes the customer experience based on what’s working. AI also supports SDRs by unifying data across all these touchpoints. Cross-channel data unification is what lets B2B sales teams create wholistic customer profiles – it lets the channels talk to each other.
Perhaps most importantly, AI makes it possible for sales professionals to meet customers where they are in their buying journey by providing real-time insights into customer needs. Usage analytics help your sales reps understand exactly how customers interact with content across different stages of the journey.
Here are two examples of how AI helps improve CX in the B2B buying journey:
- Using search analytics to understand customer behavior: Enterprise search analytics show what documentation buyers access, how long they spend on specific pages, and which product features they’re most interested in. By analyzing zero-result searches and queries that yield no clicks, sales teams can identify gaps in their content strategy. They can then proactively address customer needs.
- Using conversational commerce to manage complex requests: In B2B manufacturing and distribution specifically, conversational commerce tools use AI to handle complex technical queries like “What are the disposal considerations for this lubricant?” or “What types of conformal coatings can we source for our new circuit boards?” These tools can then provide accurate, grounded responses that help move the sale forward.
Embrace AI to Stay Competitive in B2B Sales
In a perfect hybrid B2B sales environment, AI does the heavy lifting for humans in ways that support and augment human-focused tasks. The future belongs to organizations who figure out how to combine human expertise and AI capabilities effectively. Rather than focusing on replacing humans with AI, forward-thinking B2B companies are investing in tools and training that enhance their sales teams’ capabilities.
With 86% of B2B buyers reporting stalled purchase processes due to price and internal complexities, the most successful organizations will be those that use AI to augment their teams’ natural strengths – letting machines handle data processing and pattern recognition while humans focus on building trust, understanding nuanced needs, and delivering the personalized experiences that complex B2B selling requires. Embracing this balanced approach creates value for customers and helps sales teams build stronger and more sustainable relationships.