B2B buying behavior is constantly changing. Today's brands need a solid sales enablement strategy to keep up the pace and navigate this constant shift surrounding sales. 

Sales enablement involves providing your sales team with the right technology, content, and training to engage with prospects and close more deals. 

Unfortunately, it’s not as easy as it sounds. Implementing a sales enablement strategy can be challenging, irrespective of your industry. 

However, one technology that’s been a game-changer for sales is artificial intelligence, specifically Generative AI. 

In this post, we dive into what the future of sales enablement looks like with Generative AI. 

How is Generative AI changing B2B sales enablement?

Let’s discuss ways Generative AI is set to reshape the B2B sales enablement landscape: 

1. Enhancing the overall performance of sales teams 

Teams incorporating AI into their everyday workflows can significantly reduce time-consuming tasks and streamline everyday activities.
  • Automation of administrative tasks: AI in sales enablement can put an end to repetitive administrative tasks sales teams perform, thus leaving room for more strategic activities. For example, sales reps can train to use AI sales enablement tools that auto-generate playbooks, sales proposals, RFPs, and other sales collateral. 
  • Streamline sales processes: AI-powered analytics and reporting can guide sales teams to uncover potential bottlenecks that may hamper their conversions. AI also offers optimization best practices so teams can prioritize only impactful activities. 

2. Forecasting and lead scoring 

AI-based lead scoring and sales forecasting are undertaken by Machine Learning algorithms that auto-generate a score for each lead between 1 and 100. These algorithms learn from customer data and interactions, such as specific phrases they use and how they respond and sound during calls. 

Here are some benefits of AI-led forecasting and lead scoring as part of sales enablement:
  • AI tools for forecasting make it convenient for your teams to target the right sales-ready leads 
  • AI lead scoring models stay up-to-date as and when new data comes in
  • Algorithms provide reliable sales predictions, so sales leaders can make better decisions for resource allocation, training, and territory planning
  • Increased productivity by devoting more time to pursuing qualified leads 

3. 24/7 virtual sales assistance

Sales and GTM teams often handle complex prospect queries. Sometimes, questions are beyond their expertise, forcing them to put prospects on hold while they search for answers. 

However, that’s not the case with AI-powered virtual sales assistance.

For example, a Generative AI digital assistant tool like Docket delivers accurate answers by learning from your internal knowledge sources. Docket’s answers are trained to be conversational, so you can use the same response to answer prospect queries on the spot and move them to the consecutive sales stages. 


4. A personalized, customer-focused selling 

Prospects have varying needs and expectations. However, a recent HBR survey says that more than two-thirds of buyers felt certain sales communications to be robotic and impersonal. 

Understanding and tailoring your messaging to suit individual customer and prospect needs is your best bet to staying competitive. 

Using Generative AI (GenAI), sales teams can design a more personalized approach to selling and building strong customer relationships. 
For example:
  • Customize sales pitches and content: GenAI can analyze data from past interactions, purchases, and trends to generate and suggest personalized sales messages and pitches. Sales reps can use these recommendations to engage prospects and increase the likelihood of conversion.
  • AI-driven customer profiling: AI customer profiling analyzes data from sources such as CRM, chatbot conversations, website interactions, etc. The resultant insights can give your teams an in-depth view of prospects’ buying behaviors, pain points, and needs. 

5. Automated sales processes 

Tedious tasks deserve automation. And task and process automation is one of GenAI’s biggest advantage that improves sales efficiency. 

Some major examples of GenAI-automated sales processes are:
  • Automated data entry that ensures your CRM remains up-to-date 
  • Automated customer service using AI chatbots that cater to users 24/7 and can route more complex queries to a live sales agent 
  • Automated note-taking during critical calls so your team can focus on driving the conversation forward
  • Automated personalized outreach and follow-ups through channels like emails, LinkedIn, SMS, etc.

6. Personalized learning to bridge skill gaps

AI-powered adaptive learning tools are rapidly setting new standards for continuous personalized sales learning. 

Such tools are heavily trained to detect potential skill gaps, assess knowledge, and pinpoint strengths and weaknesses within a sales team. 

For example, AI can analyze specific sales rep’s skills, such as objection handling or time management, and track each rep’s performance metrics to recommend targeted training programs and recommendations to bridge potential gaps.

7. Better sales team collaboration and communication

AI features to automate tasks like meeting transcription, translation, and summarization of team calls, can streamline team collaboration and communication, thus boosting productivity. 

For example, sales team members can collaborate on the AI platform to access summarizations of Zoom calls with potential leads and work together to prioritize follow-ups. 

Being able to access real-time call summaries, transcripts, and more leaves no room for misunderstandings and instead encourages team alignment. 

8. Improved customer experiences 

Customer relationships and experiences are at the heart of high-converting sales. Personalization is key to creating a winning customer experience. And what better way to personalize than using AI-driven insights?

Here’s how AI-driven insights can guide sales enablement for superior customer experiences:
  • Anticipate customer and prospect needs, challenges, intent signals, and behaviors
  • Identify communication patterns, such as frequency of interaction, preferred channels, and best timings
  • Analyze customer feedback for recurring trends and areas of improvement 
  • Identify opportunities for SDR training to handle customer queries

9. Sentiment analysis and social listening 

It’s not humanly possible for sales and marketing teams to manually dig through social media and various online portals to understand how consumers perceive their brand and products. And the same goes for uncovering what competitors are up to. 

Meanwhile, with AI, Machine Learning algorithms are used to categorize text sentiment collected across sources as positive, negative, or neutral. 

For example, if a customer expresses dissatisfaction with a product on Twitter, their concern can be prioritized through AI-based sentiment analysis and social listening. 

Wrapping up

As AI evolves, so will the sales enablement strategies and the future of B2B sales. AI will become more central to the success of a sales enablement strategy—using AI to interact with customers, create marketing resources, or for sales leaders to analyze trends.

Further, staying informed about your target market's constantly shifting journeys is key to maintaining momentum and not trailing behind. 

But where should you begin? 

Start by adding digital AI assistance tools like Docket into your sales workflows. Docket eases sales enablement by helping your internal team find the most accurate answers to prospect queries just in time.