How to use AI for sales

Tristan Ovington
By Tristan Ovington
Updated May 29, 2024

With the explosion in popularity of artificial intelligence (AI) with tools like ChatGPT, it can be hard to separate its different use cases.

How to use AI in enterprise sales is like everything in life: Easy when you know how. However, many enterprises don’t, as AI digital adoption is slower than many people may think.

Despite 52% of sales professionals saying AI is essential to their daily activities, 29% of organizations lost USD 50-100 million due to misuse. Learning how to use AI for sales correctly can save you money for growth. 

Despite 52% of sales professionals saying AI is essential to their daily activities, 29% of organizations lost USD 50-100 million due to misuse (1)

AI for sales analyzes data to predict leads, personalize outreach, and close deals faster. This technology allows staff to focus on higher-level tasks AI cannot do: spending time with customers to inform them about new products to close sales more effectively and retain customers longer. 

Arm yourself with the knowledge to use AI for sales, which offers higher revenue and a better employee experience. Below, we have listed the best ways to use AI for sales. Follow them and join the organizations benefitting from this powerful new technology today.

How do you use AI for sales?

How do you use AI for sales_ (1)

Innovative applications of artificial intelligence (AI) are revolutionizing sales strategies, offering unprecedented opportunities for businesses to optimize processes and drive revenue growth. 

Sales leaders can leverage AI in many ways, from lead generation to predictive analytics, transforming the sales landscape with data-driven insights and automation.


Artificial intelligence (AI) systems leverage historical data. Doing so allows them to anticipate future outcomes: predictive forecasting. 

Sales AI systems specialize in predicting various outcomes. Examples include the likelihood of closing deals or targeting prospective clients. They identify potential customers likely to engage with offered products or services. 

The accuracy of these forecasts depends on the system’s sophistication and the quality of input data. With appropriate historical and current data, AI effectively identifies prospective buyers. 

Predictive forecasting also aids internal sales operations by enabling managers to anticipate team performance. Armed with this insight, they can proactively optimize team productivity. 

Ultimately, AI-driven predictive forecasting enhances sales strategies by providing actionable insights derived from data analysis.

Condensing and generating actionable insights from meetings and calls

Every sales representative participates in interactions with potential clients and existing customers. Reps dedicate substantial time and effort to condensing the content of each sales call and devising action plans for sales teams accordingly. However, this manual approach is outdated.

Today, AI technology can swiftly and accurately summarize sales calls. It does this by providing instant summaries shortly after the call concludes. It can automatically email summaries to all involved parties. Furthermore, AI can generate the next steps for each participant based on the call’s content.

Although these tasks may seem basic, delegating them to AI conserves significant human resources. Staff can then redirect these energies toward more strategic activities, like enhancing deal closures. 

Suggesting follow-up steps for sales representatives

Determining what tasks to prioritize next is a substantial obstacle to sales employee productivity. Sales teams handle multiple deals simultaneously, facing the challenge of managing their workload effectively. The inability to prioritize tasks and execute them in the correct sequence leads to missed revenue-generating opportunities.

AI utilizes deal-specific data to recommend real-time actions for sales reps. It is like an always-available coach and manager. By analyzing the current stage of each deal, AI guides reps toward the precise steps required for maximum sales productivity.

Automatically generate sales subject lines and emails

Email outreach is a vital aspect of sales operations. It encompasses employee engagement with both inbound leads and outbound prospects. 

However, conducting this outreach manually proves repetitive and less effective than desired. Generative AI offers a solution by swiftly producing high-quality email content and subject lines from scratch. 

This capability enables sales professionals to significantly scale their outreach efforts by generating initial drafts for subsequent personalization or fully automating email creation. Additionally, AI’s capacity to create numerous engaging subject lines rapidly enhances the likelihood of email opens. 

By leveraging generative AI, sales organizations can streamline their email outreach processes, increase efficiency, and improve the effectiveness of their communications with prospects and leads.

Identifying new in-market leads

Employing extensive data analysis capabilities, AI can detect patterns within lead data, facilitating the identification of new, in-market leads aligned with your business criteria. 

AI can subsequently scrutinize third-party lead databases and platforms by analyzing the characteristics of existing high-quality leads to pinpoint individuals who closely match the desired lead profile. 

This process enables businesses to efficiently generate leads that align with their target audience, leveraging AI’s ability to sift through vast amounts of data to identify promising prospects.

Predict close likelihood

Utilizing predictive capabilities, AI can provide more precise estimations of the likelihood that leads within your database will convert. 

By scrutinizing extensive historical and market data, AI identifies lead profiles with higher closing probabilities and optimal timing for conversion. 

This approach enhances predictability and efficacy within your sales pipeline, offering insights that empower strategic decision-making and resource allocation. 

Leveraging AI’s predictive analysis elevates the efficiency and accuracy of your sales operations, enabling proactive measures to capitalize on high-conversion opportunities.

Predict buy-readiness

AI’s predictive capabilities extend to determining when leads are poised to make a purchase, drawing insights from historical data and behavioral cues. 

This approach enables prioritization and focused engagement with leads nearing the buying stage, resulting in a notable boost in conversion rates. 

By leveraging AI, businesses ensure they don’t miss out on opportunities presented by leads primed for conversion, emphasizing the importance of timely sales interactions. 

With AI-driven insights guiding lead management, organizations can optimize their sales efforts, efficiently capitalizing on prospects ready to commit, thus maximizing revenue potential.

Automatically score leads 

While manual lead scoring offers assistance, automating the process elevates its utility. 

Nonetheless, this approach remains relatively static, demanding substantial effort, assessment, and upkeep to guarantee accurate lead evaluation. 

Enter AI can alleviate this burden by instantly scoring leads upon arrival, autonomously factoring in behavioral metrics, lead information, and predetermined scoring parameters. 

Furthermore, AI has the agility to dynamically adapt scoring criteria in response to evolving data, updated close rates, and emerging insights into indicators of a promising lead. 

By harnessing AI, businesses streamline lead-scoring processes, ensuring precision and responsiveness to changing market dynamics. 

This technological advancement empowers organizations to optimize resource allocation and focus efforts on leads with the highest potential, thus enhancing overall sales effectiveness.

Promoting automatic cross-selling and up-selling

AI revolutionizes cross-selling and upselling in sales departments by leveraging customer data to identify opportunities and personalize recommendations. 

AI algorithms can predict which products or services are most relevant to individual customers by analyzing purchase history, browsing behavior, and demographic information. 

Through targeted marketing campaigns and personalized offers, AI enables sales teams to proactively suggest complementary or upgraded items, enhancing the customer experience and increasing sales revenue. 

Additionally, AI-powered chatbots and virtual assistants can engage customers in real-time, guiding them through decision-making and making relevant suggestions based on their preferences. 

This automation of cross-selling and upselling boosts sales performance and strengthens customer relationships by providing tailored solutions that meet their evolving needs and preferences.

Dynamic content generation

In the realm of dynamic content creation, AI aids marketers in processing vast data volumes, spot patterns, and insights. They also craft and refine content and deliver it to precise users at optimal times and locations. 

For instance, AI leverages natural language processing (NLP) to grasp textual meaning and sentiment. It also uses natural language generation (NLG) to produce compelling and coherent text and computer vision to detect and handle images and videos.

Leveraging AI for dynamic content creation provides numerous advantages for marketers and their target audiences, including increased efficiency and productivity, heightened personalization and relevance, and enhanced performance and conversion rates. 

By automating and streamlining content creation, AI conserves marketers’ time and resources while customizing content to match users’ unique interests, requirements, and preferences. 

AI optimizes content for various channels, devices, and formats and conducts testing and measurement to improve effectiveness and impact, resulting in higher conversion rates and customer retention.

Define your needs before investing in AI for sales

AI is mighty, but try to avoid getting up in the hype before investing millions. Learning to use AI for sales correctly is essential, as it can save you money for growth.

First, identify specific pain points, such as lead generation or sales forecasting. Second, objectives and goals should be clarified, such as improving conversion rates. Next, assess your data availability and quality for meaningful insights. 

The next point is considering how well a new AI tool might integrate with your existing tech stack. Would investing in AI for sales require investing in new software that would integrate with it?

The final step is to consider your budget and ROI expectations. To justify the investment, consider the potential ROI, including increased productivity, higher conversion rates, and improved customer satisfaction.

Once you have completed all these steps, you may or may not decide to invest in AI for your sales departments and reap the benefits of revenue and employee retention. Sales reps will then be able to do what they love best: Spending time with customers to secure sales. 

Tristan Ovington
By Tristan Ovington
Tristan Ovington, an accomplished senior writer and journalist, typically contributes his expertise to the Enterprisers Project. Renowned for his valuable perspectives on digital adoption, digital transformation, change management, and Cloud applications.