AI Lexicon: Common Definitions Every Sales Person Should Know

Machine Learning

Machine learning is a field of studies within artificial intelligence, focusing on developing algorithms that can learn and improve from experience without being explicitly programmed. These algorithms analyze data, identify patterns, and make decisions with minimal human intervention. 

How it’s used in sales: Machine learning can be used to help teams forecast revenue, prioritize deals with lead scoring, analyze sentiment from text, and much more.

Natural Language Processing (NLP)

Natural Language Processing, or NLP, is a machine learning technology that gives computers the ability to understand, interpret, and generate human language. This technology powers AI chatbots and virtual assistants. 

How it’s used in sales: NLP is the powerhouse fueling many transformations in sales. Among its many uses, NLP empowers companies to automate and personalize customer interactions at scale and qualify leads on the website, ultimately improving close rates and shortening deal cycles.

Large Language Models (LLMs)

Large Language Models (LLMs) are at the forefront of AI advancements, capable of generating text that closely mimics human writing. These models are trained on vast datasets, encompassing a wide range of topics and writing styles. So, they can understand context and maintain coherence over long stretches of text. They have a broad range of capabilities, including text generation, translation, summarization, conversation, text completion, and much more.

How it’s used in sales: LLMs can provide automated, yet highly personalized, responses to customer inquiries and generate custom and engaging enablement content at scale.

Neural Networks

Neural networks are computational algorithms modeled after the human brain’s network of neurons, designed to process complex data patterns. Mimicking the brain’s interconnected neuron structure, they excel at recognizing intricate and non-linear relationships within large datasets, making them highly effective for tasks involving prediction, classification, and pattern recognition. 

How it’s used in sales: Neural networks can analyze vast amounts of sales data to unearth underlying patterns, thereby empowering sales teams to accurately forecast revenue and make more informed decisions about deal prioritization.

Computer Vision

Computer vision is a field of artificial intelligence that deals with enabling computers to extract meaningful information from visual data, such as images and videos. By employing sophisticated algorithms to analyze pixels and patterns, computer vision systems can identify objects, classify images, and even interpret scenes, much like the human eye but at a vastly larger scale and speed.

How it’s used in sales: computer vision can be used to unlock insights from visual data, personalize product demos, and improve the user experience.

Conversational Intelligence

Conversational intelligence leverages AI to analyze customer interactions, extracting valuable insights to refine sales strategies and enhance communication effectiveness. Through advanced machine learning and natural language processing techniques, this intelligence can decipher the nuances of human communication, identifying key themes, sentiments, and potential opportunities within conversations. 

How it’s used in sales: Conversational intelligence can digest heaps of data about prospects in record time, cutting research time in half. Plus, it can actively draw insights from your conversations and provide real-time guidance after calls.

Generative AI

Generative AI is a transformative technology capable of creating new content, including text images, audio and more, based on learned data patterns. Utilizing complex algorithms, it can analyze existing text to understand style, structure, and context, then produce original content that mirrors these learned patterns. 

How it’s used in sales: this capability can be harnessed for any job that requires content, from  innovative sales enablement materials, to crafting engaging social media content, and personalizing cold emails at scale and generating images to go along.


A chatbot is a computer program that simulates human conversation allowing humans to interact with digital devices as if they were communicating with a real person. AI-powered chatbots simulate sophisticated conversations with users, providing timely, personalized responses to customer queries. By employing advanced natural language processing and machine learning techniques, these chatbots can understand and interpret the intent behind user inquiries, and respond in a contextually relevant manner. 

How it’s used in sales: chatbots can improve customer service, reduce response times, and even help qualify leads on the website.


ChatGPT, developed by OpenAI, is a conversational AI chatbot capable of generating human-like text. Built on a foundation of extensive training data, it can engage in meaningful dialogues, answer questions, and provide information in a way that closely mimics natural human conversation. 

How it’s used in sales: ChatGPT can be a valuable tool for brainstorming pitch ideas, creating persuasive sales scripts, and crafting professional emails and messages at scale.

Gemini (formerly Bard)

Google’s newest conversational AI model, which is built on top of Bard and trained on a much larger and more diverse dataset, including text, code, images, and audio, allowing it to now generate images. Plus, it can search the web in real time and access Google Workspace. 

How it’s used in sales: Gemini can help speed up the research process by bringing up specific sources quickly, and because it integrates with Google Calendar, it can help salespeople manage their schedules, set reminders for follow-ups, and keep track of their sales goals and performance metrics, acting as a personal assistant.


DALL-E, another innovation by OpenAI, generates images from textual descriptions. This AI model utilizes deep learning techniques to interpret written prompts and translate them into detailed, relevant visual content, bridging the gap between textual concepts and visual representation. 

How it’s used in sales: DALL-E can help salespeople create customized visual materials that can make pitches and presentations more engaging and memorable, aiding in storytelling and product visualization, and ultimately enhancing the persuasive power of sales communication.

Predictive Analytics

Predictive analytics uses data, statistical algorithms, and machine learning techniques to forecast future outcomes based on historical data. This approach involves analyzing past and current data trends to make educated guesses about future events, enabling a data-driven anticipation of what might happen next. 

How it’s used in sales: Predictive analytics can help salespeople forecast future sales trends, provide a real-time view of the sales pipeline’s health, and uncover patterns in user behavior.

Predictive Contact Scoring

Predictive contact scoring employs AI to evaluate leads based on their potential to convert into customers. By analyzing various data points such as past interactions, demographic information, and engagement levels, AI algorithms assign scores to each lead, indicating their likelihood of making a purchase. 

How it’s used in sales: This technique helps sales teams prioritize their outreach efforts, focusing on leads with the highest likelihood of success, thereby optimizing efficiency and improving win rates.


Priming in AI refers to the initial setup or input given to tools like ChatGPT to generate specific outcomes. This process involves providing a detailed context or a set of instructions that guide the AI in generating responses or content that aligns with desired objectives or themes. 

How it’s used in sales: Salespeople can use priming to generate responses that are better suited to each individual prospect, so they’re more personal and relevant. 


Prompts are textual inputs provided to AI tools like ChatGPT to elicit particular responses. These inputs act as catalysts, directing the AI’s response generation process to align with specific topics, styles, or objectives. 

How it’s used in sales: Prompts can be strategically used to generate content for sales pitches, emails, and marketing materials, ensuring consistency in messaging and brand voice across all sales communications. 

Prompt Engineering

Prompt engineering involves the skillful crafting of prompts to guide AI tools to produce the most useful and relevant responses. This practice requires a deep understanding of the AI’s capabilities and the specific objectives at hand, allowing for the creation of prompts that precisely target the desired outcome. 

How it’s used in sales: By optimizing the way prompts are constructed, sales teams can harness the full potential of AI to support their goals, from improving lead generation to developing compelling sales narratives.

Dynamic Prompting

Dynamic prompting refers to the adaptation of prompts in real time to improve the relevance and accuracy of AI responses. This approach involves continuously refining and adjusting the prompts based on ongoing interactions and feedback, allowing the AI to better align with the evolving context of the conversation. 

How it’s used in sales: Dynamic prompting ensures that the AI responses you get back are more and more relevant to your specific industry or prospect.


Role-play using AI tools, such as ChatGPT, provides a platform to mimic a range of scenarios, from everyday conversations to specific professional situations. This interactive form of training creates a risk-free space where individuals can hone their skills, tackle challenges, and refine their strategies across various contexts. 

How it’s used in sales: This innovative training method offers a safe and dynamic environment for salespeople to practice giving their pitch, handling objections, and closing deals. 

Buyer Intent Data

Buyer intent data includes details analyzed to guess when potential customers might decide to buy something. This data comes from different places, like when someone visits a website, interacts with content, or asks about a product, giving clues about a customer’s interest and where they are in the decision-making process. 

How it’s used in sales: This information is crucial for spotting the most promising potential customers. It helps sales teams concentrate on those most likely to close, improving their chances of making successful deals.

Sales Pipeline Intelligence

Sales pipeline intelligence offers insights and analytics specifically tailored to understanding and optimizing the sales pipeline. By analyzing each stage of the pipeline, this intelligence provides a clear view of the sales process, from initial contact to closing the deal. 

How it’s used in sales: This detailed analysis helps sales teams identify where leads tend to stall or drop off, strategize how to move leads through the sales funnel more efficiently, and ultimately increase the velocity of deals.

Sentiment Analysis

Sentiment analysis involves examining communication, such as calls or emails, to determine the emotions and engagement levels of the receiver. This technique helps in understanding the underlying feelings of the other, whether they’re interested, indifferent, or even skeptical. 

How it’s used in sales: Applying sentiment analysis empowers reps to fine-tune their strategies, and prioritize deals more effectively.

AI-powered Search

AI-powered search goes beyond regular search tools by using complex algorithms that make search results more relevant and accurate. This advanced search system gets the context and subtle details of searches, providing very specific information. 

How it’s used in sales: These improved search features are extremely useful for finding potential leads, doing detailed market research, and analyzing competitors deeply.

Data Visualization for Sales

Data visualization for sales converts complex sales data into user-friendly graphical formats like charts, graphs, and dashboards. That way, it’s far easier to understand complicated data sets. 

How it’s used in sales: These visuals help sales teams quickly notice patterns, evaluate their sales metrics, and spot new trends that raw data alone might not reveal. 

AI Email Assistant

An AI email assistant uses artificial intelligence to manage and optimize email tasks, like drafting, organizing, and replying to emails. It learns from your email habits and preferences to automate routine tasks, saving time and increasing efficiency. 

How it’s used in sales: This tool can help salespeople automate follow-ups and personalize communication with leads, making the sales process more effective and less time-consuming.

AI Meeting Assistant

An AI meeting assistant is a digital tool that uses conversational intelligence to transcribe, highlight key points, and provide real-time insights during meetings, making it easier to capture and follow up on important details. This assistant acts as a combination of a personal coach, an invaluable aid for note-taking, and an analytical tool, streamlining meeting processes and enhancing productivity.

How it’s used in sales: This assistant streamlines meeting management, ensuring that sales teams can focus on strategy and customer engagement without getting bogged down by administrative tasks.

AI Note-taker

An AI note-taker is a tool that automatically transcribes spoken words during meetings or conversations into written text, using artificial intelligence to recognize and record speech. It can also highlight key points and action items from discussions, making it easier to review and follow up. 

How it’s used in sales: An AI note-taker ensures that important details and commitments from sales calls are accurately captured, helping salespeople track product feature requests, integration discussions, and follow-up actions effectively, thereby streamlining the sales cycle and fostering stronger client relationships.

AI Task Automation

AI task automation involves using artificial intelligence to automate repetitive and routine tasks that don’t require complex decision-making. This technology can handle tasks like data entry, scheduling, and sending standard emails, freeing up time for more strategic work. 

How it’s used in sales: AI task automation can streamline processes like lead qualification, CRM updates, and post-call follow-ups, allowing sales teams to focus on building relationships and closing deals.

AI Virtual Assistant

An AI virtual assistant is a software agent that uses artificial intelligence to perform tasks or services for an individual, often including tasks like scheduling appointments, setting reminders, or answering questions. It understands natural language, making it user-friendly and efficient in managing day-to-day activities. 

How it’s used in sales: An AI virtual assistant can significantly improve productivity by handling administrative tasks, allowing sales professionals to dedicate more time to engaging with clients and focusing on sales strategies.

Automated Follow-ups

Automated follow-ups are a system that uses software to automatically send messages or emails after a specific action or period, ensuring consistent communication. This system can schedule and personalize messages based on previous interactions and preferences, maintaining engagement without manual intervention. 

How it’s used in sales: Automated follow-ups keep potential leads warm and engaged, increasing the chances of conversion by ensuring timely and relevant communication throughout the sales cycle.

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