Exploring AI Sales

Sales is about finding that edge-the something extra that gets you noticed in a crowded marketplace. Today, that edge comes from integrating artificial intelligence (AI) sales solutions into traditional sales activities. With 81 percent of sales teams already exploring or implementing AI, learning how to use AI-empowered sales tools is critical to winning in the new era of sales [1].

Your role in the sales process remains central, as AI sales tools support building that human connection rather than replacing it. They’re the tools that free you to focus on the other, human-centered parts of selling—building relationships, solving problems, and mastering the art of helping people find exactly what they need (or want).

Definition of AI sales

AI sales refers to the use of AI technologies to help sales teams and individuals work smarter and more efficiently. By automating workflows and providing insight analysis, AI sales can help improve strategic and tactical decision-making.

Technologies for AI sales

As a member of an AI-enabled sales team, you might see any or all of these common AI technologies:

• Machine learning for predictive analysis

• Natural language processing for communication analysis

• Collaborative filtering for recommendations and personalization

• Data analytics for insight analysis

• Automation to streamline workflows

• Generative AI for content creation and personalization

Sales teams often have information overload. Integrating AI-enhanced software with other sales and marketing tools helps translate data, emails, and calls into meaningful insights, recommendations, and actions. These AI technologies really shine because they constantly learn with every new interaction or data point, becoming an increasingly accurate and valuable work partner.

Applications of AI in sales

AI has widespread application throughout the sales cycle, using its powers of analysis and automation to support you to work more efficiently, generate more sales, and strengthen customer relationships. 

Lead generation

AI supercharges lead generation by analyzing massive data sets to pinpoint the most promising leads. By evaluating online behavior, past purchase history, and buyer intent signals, it assesses lead quality. With AI identifying the hot opportunities, you will focus your time on leads with a strong chance to close.

Customer segmentation

Machine learning can detect relationships among variables that other tools cannot, opening a whole new world of segmentation strategies based on behavioral histories and psychographic profiles. You could build campaigns that target narrow groups with precise messages and offers at exactly the right time and through exactly the right channel for maximum impact.

Personalization

Personalization is the art of creating a customer segment of one person. The AI sales approach to personalization analyzes the preferences of each customer dynamically and does it at scale. Using AI, you might be able to analyze customers’ preferences using their browsing and purchasing histories to present them with the products and services likely to interest them. 

Predictive analytics

Predicting future sales and having insight into customers’ changing preferences is a key competitive advantage. AI predictive analysis tools set a higher standard with their accuracy, leaving you more confident in switching messaging or offers or revising entire sales strategies to meet customer demand and take advantage of unexpected opportunities.

Benefits of AI in sales

Expectations of AI in sales are high. According to a recent KPMG survey, executive management’s top priorities for their AI initiatives include growing revenue and improving productivity [2]. Realizing their potential will help sales departments achieve both goals for their organizations.

Enhanced sales performance

AI systems strengthen sales performance by using behind-the-scenes analysis of interactions, outcomes, and prospects’ behaviors to shorten sales cycles and direct your efforts where they’ll be most helpful. For example, these data-driven insights might reveal a deal at risk, giving you the opportunity to take timely action that reinvigorates that opportunity. AI-powered sales coaching tools analyze sales calls and performance data to enhance your sales skills.

Increased efficiency

Salesforce research found that sales representatives spend the bulk of their time on activities unrelated to selling, spending only 30 percent on selling activities [3]. AI sales tools may alter that ratio. Automation and generative AI tools can handle much of the burden of repetitive sales support work, allowing you to devote more time to building relationships.

Revenue growth

Companies that use AI sales tools are more likely to see revenue grow than those that don’t [4]. Combining AI solutions into existing workflows and processes can give you more time, insights, and advanced capabilities to create and seize high-value opportunities and generate more revenue for your organization.

Tools and technologies

Many AI sales tools help streamline sales processes, from automating functions to managing customer relationships. Discover the types of sales AI tools that can elevate your sales workflow, potentially helping you make every step faster, smarter, and more effective.

Popular AI tools

• Sales automation software: These tools generally include a variety of AI-enabled functions, such as automating repetitive tasks, lead scoring, workflow and pipeline management, and personalizing interactions. 

• Customer relationship management (CRM): CRM is a familiar software salespeople have used for some time now. AI-enabled CRM can help deliver more advanced lead and pipeline management, segmentation, and personalized communication, which could lead to improved close rates and increased customer retention. 

• Chatbots and AI assistants: These tools can handle many repetitive tasks, including 24/7 sales support, capturing and qualifying new leads, and letting you spend more time on more creative sales tasks.

• Lead generation and qualification: These AI sales tools help identify and qualify high-potential prospects from various data sources (e.g., social media), making your outreach more targeted and efficient.

• Sales forecasting: Analyzes pipeline and sales data to predict expected sales and revenue to optimize sales strategies and allocate resources.

• Sales analytics: Focuses on improving sales team and individual performance through historical analysis of sales data and sales team interactions. You can also use them to better understand areas primed and ready for growth.

• Post-sales support: Automates onboarding, simplifies support, and analyzes customer interactions to promote long-term, high-value customer relationships.

• Generative AI: Simplifies and speeds up how you create personalized content and proposals, enhancing the quality of your pitches and prospect engagement.

• Sentiment analysis: Assesses call transcriptions and digital communications to gauge buyer sentiment and provide insight for follow-ups.

Integrating AI into the sales workflow.

Integrating AI sales tools with each other and into your workflow lets you focus on the human side of selling, responding in a timely and personal way to leads and customers, closing deals, and building customer loyalty. 

On a typical day, you might start the morning by checking your sales dashboard, which highlights three priority leads identified by its lead scoring analysis. Your integrated CRM system has already scheduled follow-up interactions with these leads, with suggested sales enablement content for you based on their past engagement.

After your first call, you get sentiment analysis feedback based on the lead’s reactions, with suggested next steps. Meanwhile, your CRM system has automatically updated the lead’s record regarding your call. The sales chatbot has qualified new inbound leads assigned to you. Using the suggested email template from your sales automation software, you use the generative AI integrated into your email to personalize the template for these new leads.

Valuable case studies on AI sales tools

Sales teams use AI sales tools at every stage of the sales cycle, from first outreach to cultivating lifetime customer loyalty and increased value. These case studies show you how different organizations already benefit from incorporating AI into their sales processes.

Successful implementations

• HubSpot, a CRM solution, increased its email conversions by 82 percent using AI technologies, including personalizing content, predictive lead scoring, automation, and analysis of past performance to optimize email delivery times [5].

• AIC Corporation increased its qualified leads from 45.5 percent to 64.1 percent by using Salesken AI to analyze customer sentiment during agent calls and provide sales insights in real time [6].

• Netflix estimates it's saved $1 billion in indirect costs by improving customer retention with highly personalized recommendations. The company’s personalization algorithm uses natural language processing, deep learning, collaborative filtering, and neural networksto analyze each user’s visual and audio preferences to serve up the content most likely to keep users engaged and subscribed [7].

Best practices for AI implementations

These case studies address different points of the sales cycle but share a common playbook for success with AI sales. They gather a broad collection of meaningful data. Each organization had clear business goals and metrics to test the value of the AI sales technologies they use. They

monitored the performance of the AI-based tools and adapted their application. They also kept people at the center of their efforts.

Skills required for AI sales roles

As an AI-driven sales professional, you’ll rely on a mixture of technical skills to enhance your traditional sales skills.

Essential skills

• Understanding AI technologies: When you’re comfortable with concepts like machine learning and natural language processing, you’ll be able to use the AI sales tool more effectively and help identify potential use cases for your sales department’s AI stack.

• Data analysis: AI sales tools will do the bulk of analyzing data from multiple sources. However, with strong data analysis skills, you’ll be better able to interpret the information on your AI sales dashboard.

• Sales strategy development: Using insights from AI solutions, you’ll be able to make data-driven decisions to customize sales approaches for individual leads or refine broader sales strategies for product lines.

• Consultative Selling and Problem Solving: Integrating AI tools like generative content creation and objection analysis will help you get creative with targeted pitches and conversations that directly address a lead’s needs and fears.

Educational background

You can find a range of educational opportunities to enhance your skills and job prospects as a sales professional well-versed in using AI sales tools.

• Develop your knowledge and skills of AI technologies: When you have a strong understanding of what different AI technologies can do, you’ll be in a better position to take advantage of them in your work.

Example courses: IBM’s Introduction to Artificial Intelligence or the Coursera Instructor Network’s GenAI for Sales. 

• Become an expert in specific AI sales solutions: Having demonstrated experience in a major AI sales tool can help you position yourself as a valuable asset. 

Example courses: Salesforce Sales Operations Professional Certificate, Sales Analytics with Claude: Data-Driven Sales Analytics.

• Open programs offered by universities: These programs offer a structured path to get a broad understanding of how AI technologies are shaping the new sales frontier.

Example programs: The University of Pennsylvania’s AI for Business Specialization or Generative AI Leadership & Strategy from Vanderbilt University

Industry demand

According to McKinsey, marketing and sales are the most common function areas adopting AI, with 34 percent of respondents across industries reporting use of generative AI technologies [8]. This trend is an encouraging sign that a growing field of businesses will seek professionals who can show an aptitude for combining traditional and AI sales skills.

People with a background in professional services, scientific fields, technical services, retail, or financial services may be particularly well-positioned to join an AI-enabled sales team as these industries show growth in their adoption of AI in sales. 

Challenges and considerations with AI

AI sales tools have tremendous potential and some potential limitations, including issues with data privacy. Understanding how to address these challenges can maximize their impact.

Data privacy issues

AI thrives on data, including personal and confidential data, making it essential that businesses meet their data privacy and use legal obligations. Responsible use of lead information and customer data will help you foster the trust that’s essential to maintaining the goodwill needed for selling.

Human oversight

AI can automate and analyze but requires human oversight for interpreting insights. It also needs humans to help make ethical decisions about how to use AI tools and output and maintain the personal touch that’s vital for long-term sales success.

Risks of over-reliance

Over-reliance on AI to build account or team sales strategies could lead to homogenized approaches that lack personalization. AI can’t quite replicate the creativity needed to help you foster relationships and close deals. 

Future trends

Changes in technological advances and consumer expectations will shape the future of AI sales. As these forces intersect, they’ll continue to push how you can connect, assess, and engage with your market.

Emerging technologies

AI technologies continue to progress swiftly. Edge computing will make AI tools work even faster, helping you personalize communication in real time. Multimodal AI is a growing technology that allows AI tools to analyze unstructured data, along with traditional data formats. Unstructured data includes visual content and audio recordings, which account for a good amount of your sales information. In the future, a multimodal AI analysis may help you determine how different audiences react to a promotional video or let you know when a buyer lost confidence during a sales call.

Together, these emerging technologies strengthen AI’s ability to analyze structured and unstructured data and, in context, fuel the power of tools like conversational AI. Improved conversational AI technology will raise the capabilities of chatbots, voice assistants, and AI-generated emails to communicate in a natural voice with precisely relevant responses.

Changing consumer behaviors

Consumers' expectations for personalized, instant communications and offers are growing. Successful sellers will have to meet those expectations, something AI sales tools can help with.

PwC estimates that AI could add $9 trillion to global gross domestic product (GDP) in 2030 by increasing consumer demand, indicating, “Consumers will be mostly attracted to higher quality and more personalized products and services … In turn, increased consumption creates a virtuous cycle of more data touchpoints and hence more data, better insights, better products and hence more consumption” [9].

Explore AI sales implementations on Coursera

Effectively implementing AI in sales processes can increase efficiency, potentially boost profits, and improve the customer experience. Take the next step towards using AI in sales or preparing to get a sales position that uses AI with online programs like AI for Everyone from DeepLearning.AI, a beginner-friendly course that can help you become familiar with AI terminology, strategy, and workflows. Another option, Salesforce Sales Operations Professional Certificate explores how to build reports, charts, and dashboards in Salesforce to communicate relevant information about sales performance to stakeholders and executives. You’ll find these options and more on Coursera.