McKinsey reported that the maximum GenAI adoption has been in the sales and marketing functions of organizations. By 2025, 35% of chief revenue officers will add a “GenAI Operations” team to their go-to-market organization.

Regardless of your opinion of artificial intelligence in sales, your role, or in general, the fact is that it is becoming more sophisticated and irreplaceable with time. With the C-suite looking at strategic AI implementation, AI for sales is going to become more central to your role. 

If you’re wondering about the use cases of AI for sales, or are on the fence about investing in AI in sales tools: this blog is for you; we’ll present use cases, benefits, and artificial intelligence tools.   

Let AI handle the groundwork, freeing reps to excel at their best—building meaningful relationships, earning trust, and forging deeper connections. This is the true path to sales success. ~ Yamini Rangan, CEO at HubSpot

What is AI in Sales?

Artificial intelligence is an umbrella term used to refer to machine learning, natural language processing, and many such. These tools are capable of analyzing large sets of data quickly and efficiently to perform specific tasks.

1. Machine learning (ML): LinkedIn’s ‘People You May Know’ analyzes your interaction patterns and recommends people that interact with the same things that you do. ML tools spot patterns by learning from vast amounts of data.
2. Natural Language Processing (NLP): Right from Gmail’s Smart Compose to Auto Correct in your phone, these AI tools understand, interpret, and generate human language. 
3. Generative AI: This is all the rage now with ChatGPT! GenAI is your creative partner, MetaAI, Apple Intelligence, Perplexity, and many more can create videos, written content, and images based on your prompt.

A research by Salesforce found that high-performing teams are 4.9 times more likely to be using AI than underperforming teams. 

Artificial intelligence in sales can do everything from drafting personalized email campaigns, flagging when prospects show buying intent through website behavior, and predicting which leads will likely convert based on historical patterns and everything in between. 

The Role of Artificial Intelligence in Sales

By 2026, 65% of B2B sales teams will transition from intuition-based to data-driven decision making, using technology that unites workflow, says research analysts at Gartner. 

Right now, sales teams only spend about 30% of their time interacting with customers. 70% of their time is spent on data entry, internal meetings, prospecting, and other tasks that have little to do with making your pipeline stronger.

Artificial intelligence in sales solves for this by:

1. Automating repetitive tasks: NLP processes and understands ongoing communication across channels—emails, calls, forms, or chats—and schedules meetings and suggests follow-up times. ML can learn historical and incoming customer data, extract  key pointers from sales conversations and update your CRM with the relevant data.
2. Analyzing data to produce actionable insights: Machine learning can analyze your customer data and produce actionable insights on which leads to prioritize, when to follow up, what messaging to use, and how to personalize interactions. 
3. Acting as your sales coach: Artificial intelligence in sales call analysis might indicate that the rep spent more time pitching than understanding the prospect's challenges. Based on this, it can suggest questions to engage the prospects and gather key details.

Key Benefits of Using AI in Sales

81% of sales teams are already convinced that AI in sales will improve their efficiency and make their life easier. 

We’ll tell you why!

1. Get more time for actual selling

Reps spend 70% of their time on administrative tasks (e.g., quote generation, prospecting, CRM updates, lead prioritization). 

Julie Ginn, Vice President of Global Revenue Marketing, Aprimo saved 40% of their time spent on administration tasks. Here’s what she says, 

“AI improves our content operations. Using AI-powered Digital Asset Management (DAM), we automate asset categorization and tagging, freeing up resources for strategic activities and improving our go-to-market speed.” 

AI helps you reclaim this valuable selling time by handling routine work in the background, such as:

• log calls, emails, and meetings in the CRM
• draft email follow-ups based on the conversation analysis
• draft initial draft of proposals and quotes
• co-ordinate calendars and send meeting invites
• store and manage sales assets

According to McKinsey, sales reps that have adopted AI have increased leads and appointments by 50%.

2. Deliver hyper-personalized experiences

AI can augment sales teams' capabilities—from decoding customer psychology and predicting buying patterns to enabling real-time coaching and crafting personalized experiences at scale. Such capabilities explain why 75% of salespeople exceeded their quotas after using AI.

AI in sales can help you decode customer psychology and predict buying patterns to enable real-time personalized experiences at scale. 

This is why 75% of sales reps that used AI for sales exceeded their quotas and why 59% of businesses report that sales reps struggle to personalize the sales interactions. 

AI works behind the scenes and analyzes the prospect’s data from multiple sources—emails, signup forms, chatbots, calls, social media, etc and creates a unified buying journey.

For example, when someone downloads the whitepaper, it will automatically register their data in your CRM and analyze their digital profile as per information provided by the prospect. As and when their intent matches, they would be added to your sales pipeline and prompted with relevant emails or calls. 

It also picks intent signals and identifies patterns such as engagement, content preferences and pain points. 

For example, it might suggest:

• A three month email campaign if the ticket size is high
• Webinars and other group conversations before prompting for a demo
• Or anything else that you’ve seen work for your deals

3. Built a high-quality sales pipeline

As AI integrates with your CRM and other sales tools, it analyzes multiple signals to evaluate each lead’s potential. It examines behavioral patterns (like website visits and email engagement), firmographic data (company size, industry, and location), and pre-defined scoring criteria to generate a “fit score.”

At the same time, it assesses incoming leads' likelihood to buy based on tracking buying intent signals like time spent on case studies page, frequency of sales interaction, or specific feature inquiries.

This automated scoring system helps you weed out poor-fit prospects and focus on those genuinely interested in buying. 

For example, if a target prospect keeps visiting the pricing page and is engaged with sales emails, AI can score them higher so that you can prioritize them in your sales pipeline.

This intelligent filtering leads to higher close rates, larger deal sizes, and more predictable revenue streams.

4. Predict sales success with confidence

Rather than relying on gut feelings, artificial intelligence in sales helps managers make strategic decisions backed by real data.

It does so by analyzing multiple data points at once, including:

• historical win/loss patterns
• deal velocity and stage progression
• customer engagement metrics (email opens, demo attendance, whitewater downloads, etc.)
• market conditions and seasonal trends
• competitor activities

For example, AI tool notices that enterprise deals closing within 45 days show engagement from multiple stakeholder engagement in the first two weeks and involve initiation of pricing discussions by the prospect.

As Nathan Thompson, Demand Gen Manager at Copy.ai says, 

“AI sales forecasting models don’t just generate predictions and then go dormant until the next quarterly planning session. They operate in an always-on fashion, continuously ingesting the latest data signals and refining projections in real-time.”

When new opportunities display such patterns, AI can flag them as high-probability wins, making your sales forecast more accurate.

Identify invaluable customer insights in real-time

AI tracks customer interactions across channels, evaluates recurring behavior and preferences, and monitors changes in engagement levels. Based on such proactive and on-time analysis, you can understand customer insights typically overlooked by human eyes.

For example, Superlayer's sentiment analysis tool can detect when a prospect’s tone shifts from enthusiastic to hesitant during pricing discussions. The tool flags emotional turning points and provides recommendations, such as when to bring in executive stakeholders.

7 Ways to Optimize Your Sales Process With Artificial Intelligence

From automating tedious tasks to diving into customer insights, AI can be used across the sales department. 

1. Sales prospecting

One low-key way to include AI in your workflows is prospecting. 

From researching potential leads to drafting personalized messaging, AI can optimize this key phase of the sales process.

Prospect research

You can use AI sales prospecting tools to find and engage potential customers.

You can also analyze long datasheets of leads, sales calls, and mail communications to understand prospects’ pain points. Based on this, you can generate discovery questions, pinpoint potential objections, and frame your responses accordingly.

Apollo.io’s Chrome extension helps you find potential customers. It gathers contact information (company, job profile industry, team size, etc.) from platforms like LinkedIn and sets up automated outbound messaging using triggers and actions within the tool.

Automated data enrichment and personalized outreach

By integrating AI tools with your CRM, you can automate the data flow from multiple sources to your CRM. AI tools can update data in real-time, fill in missing details, and suggest next actions based on your sales interactions.

With enriched CRM data, you can also craft highly targeted communication strategies. 

Superlayer generates key takeaways from each call and highlights the prospect’s engagement level, sentiments, and pain points. With such information at your fingertips, you can draft tailored follow-up communication to engage prospects.

2. Lead management

75% of B2B buyers prefer a sales-rep-free experience. So, they already have hours of research long before they decide to interact with a rep.

It means there are ample intent signals (engaging with competitor’s content or checking review sites, etc.) that you might not notice, but AI does.

6sense’s Revenue AI tool collects these invisible intent signals across sites like G2 or Capterra, competitor post engagements, or comparison page visits. Let’s say your potential buyers search for "conversation intelligence software" on G2 and read your product reviews. 6sense will pick up such signals and flag them as early buying intent.

It then weighs these signals against your ideal ICP’s intent and assesses a score, considering any pre-defined criteria and prioritizing high-intent leads.

Once potential buyers are identified, AI helps maintain the momentum through personalized communication. For example, AI tools can

• triggers instant demo scheduling when prospects fill out a demo request form
• sends personalized email sequences based on entry point (demo request content download, etc.)
• schedules follow-ups on incomplete form fill or abandoned demo bookings

Artificial intelligence in sales ensures smooth movement and management of leads through your sales pipeline.

• It automates lead routing by understanding each lead’s characteristics and matching them to the right sales rep based on expertise, experience, and past success rates.
• It auto-populates CRMs by extracting data from emails or sales calls, updating lead status, tracking funnel stages, and ensuring data accuracy.

4. Sentiment analysis

41% of salespeople already use AI to recognize and respond to buyer emotions or sentiments, with 83% saying it’s effective. AI is effective as it not only captures the words said but also dissects the sentiment behind them, allowing you to uncover otherwise missed opportunities.

AI analyzes multiple hidden communication signals like:

• voice tone variations and micro-changes in pitch
• linguistic patterns and word choice
• speech pace and rhythm patterns
• moments of silence, duration, and timing
• contextual detection from previous interactions

Superlayer can detect when a prospect’s tone shifts slightly lower while discussing the budget, even if their words remain positive, signaling potential pricing concerns.

AI also contributes to contextual sentiment analysis, including industry-specific languages and norms, cultural and regional differences, and seniority levels.

5. Conversational intelligence

Conversation intelligence (CI) is one of the newest use cases of artificial intelligence in sales.

It uses NLP to extract meaningful insights from each sales call through automated recording and transcription. So, you can focus more on understanding the customer's pain points, and ask probing questions to get deeper insights.

CI tools are a godsend for conversation analysis.

• record and transcribe sales calls in bulk
• generate detailed transcripts with speaker labels—even for multiple speakers
• summarize the conversation and generate key takeaways
• identify keywords, phrases, and recurring themes during the call
• share call metrics like talking time, moments of silence, monologue duration, etc.

Superlayer helps you analyze over 50 sales calls at once. It highlights recurring patterns like pain points mentioned, features discussed, and questions asked. With such pattern analysis, you can assess what themes lead to a winning deal.

And, most conversation intelligence tools, including Superlayer, automatically update the CRM with call notes, saving you tons of time.

6. Sales Coaching

Unlike traditional coaching, which involves countless hours spent shadowing sales calls, manual call reviews, and generic advice, AI automates the entire process.

Imagine you have to sit through 15 sales calls per week and spend your weekend reviewing them to prepare coaching material. All of this, while focusing on meeting your quarterly numbers.

Not only are you already swapped for time, but rather than actively listening you end up scribbling down notes. And, by the time you finish reviewing, your reps had already conducted dozens more calls.

AI flips this script.

It automates the call recording and analysis process and hands over key insights. For example, it can flag that a rep's demo ran 10 minutes late, specifically during pricing discussions.

With this, sales leaders can have a 1:1 with the rep and share pointers on how to tackle such instances in the future.

Read More: AI-Powered Sales Coaching: Revolutionizing Sales Team Training

Here are some other ways AI tools can help:

Analyze sales reps’ performance

AI can analyze each sales rep's performance across cold calls, email messaging, and other customer interactions.

Superlayer generates a summary of each conversation and creates custom scorecards based on how the rep handled the call, highlighting metrics like talking ratio, prospect’s engagement level, monologue duration, etc.

AI continually monitors performance and generates insights into their progress allowing you to identify top performers. You can assign them larger or more complex deals.

Build interactive coaching materials

Once you’ve identified areas where sales reps are lagging, you can use AI to develop personalized, relevant, and interactive coaching materials.

For example, you can engage sales reps in role-playing scenarios, create quizzes to assess reps’ knowledge and provide instant feedback. You can also use such diverse coaching materials to get new sales reps up and running without much hassle.

7. Sales analytics

AI sales tools dig through your historical sales data (win/loss patterns, deal velocity, deal size), current pipeline data (engagement levels, stakeholder involvement, proposal status), and customer interaction data (email responses, meeting frequency, sentiment).

By connecting these datasets, AI tools identified critical patterns, such as deal velocity indicators, risk signals, and buying commitments.

For example, let’s say AI detected the following deal progression signals:

• when champions share internal Slack messages/emails showing team discussions
• when prospects request customer references within the first 3 meetings

Now, based on these, AI can show that deals showing 2 of these signals in the first 30 days have 85% higher chance of closing. Such pattern analysis helps you identify opportunities that mirror successful deal characteristics.

But there’s more.

AI doesn't just tell you what has happened but also why it happened and suggests actions to resolve any roadblocks.

For example, AI detects that a deal mirrors patterns from previously lost opportunities (like delayed responses or lack of pricing discussions). Based on this, it can suggest actions such as:

• elevating the conversation to new stakeholders
• scheduling an executive touch-point
• introducing additional value propositions

3 Best AI Sales Platforms for Smart Selling

To make AI part of your sales activities, AI sales tools are a no-brainer. But, with so many platforms out there, how do you find the one that fits your needs?

We’ve done the heavy lifting and picked the top three AI sales tools for automating your current workflows.

1. Superlayer

Superlayer is an AI-powered conversational intelligence software that analyzes sales conversation and uncover invaluable insights. It helps you connect better with your prospects and ensures you never miss key details like pain points discussed, competitors mentioned or pricing suggested.

How does Superlayer automate the sales process?

• It analyzes and generates in-depth conversation insights by diving into the prospect’s sentiments, tone, and emotions, helping you create personalized messaging.
• It automatically generates a rep performance scorecard, enabling sales leaders to build personalized coaching programs.
• It automates data syncing in CRM with accurate and timely data, helping you get a holistic view of your pipeline.
• It helps with pattern recognition through batch call analysis, highlights trends over time, and helps you understand a prospect’s likelihood of conversion.

Superlayer Pricing

We offer custom pricing plans based on your team’s use cases, size, and budget. Book a demo and get a custom quote.

2. Gong

Gong is a revenue intelligence platform focused on revenue operations. It helps sales and revenue teams ensure pipeline growth and makes accurate revenue forecasts.

How does Gong automate the sales process?

• It records and transcribes all sales interactions and extracts key insights and action items without manual input from the sales team.
• It tracks customer interactions and engagement to forecast success and identify at-risk deals early.
• It tracks rep performance and identifies coaching opportunities based on actual conversation data.

Gong pricing

Gong has a custom pricing plan based on a few factors: license required, platform fee-based, features, and integrations.

3. Chorus

Chorus by Zoominfo is another conversation intelligence tool that helps with call analysis, market intelligence, and relationship management.

How does Chorus.ai automate the sales process?

• It analyzes sales calls and meetings and identifies successful sales tactics and customer concerns.
• It automatically creates tasks in CRM tools based on conversation data, ensuring you don’t miss any follow-ups and action items.
• It improves team collaboration by allowing users to tag colleagues in meeting notes.

Chorus.ai’s pricing

Like other tools, Chorus.ai offers custom plans that cater to different feature requirements, use cases, and team sizes.

Time to Level Up Your Sales Process with AI

Artificial intelligence in sales is changing how sales teams work by automating workflows, predicting sales outcomes, personalizing coaching material, and understanding customer’s sentiments.

And, it comes with a ton of benefits – increased sales productivity, hitting quotas, improving sales performance, and most importantly, more human interactions.

If you’re ready to see artificial intelligence in action, check out Superlayer, an AI-power conversation intelligence tool. The tool centralizes your sales conversations, identifies winning deals, and updates your CRM.

Book a demo today

FAQs

Can AI replace salesmen?

No, AI cannot fully replace salespeople. While AI can automate routine tasks, create new content, analyze data, and make predictions, human involvement is important. It cannot replicate the human elements essential to selling - building trust, understanding emotional nuances, negotiating complex deals, and maintaining long-term relationships. AI serves best as a tool to improve salespeople's capabilities rather than replace them.

What is the future of artificial intelligence in sales?

AI in sales will become more ingrained in sales activities with more advanced predictive analytics, voice-assisted interactions, and real-time conversation analysis. This will enable hyper-personalized customer interactions at scale while providing more accurate sales forecasting and pipeline management.

How to use artificial intelligence in sales forecasting?

AI studies past sales trends, customer behaviors, and market conditions to identify patterns that influence sales performance. By monitoring external variables like market trends, economic conditions, and competitors, it adjusts the sales number and makes more accurate, dynamic, and realistic forecasts.

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