Sales & Marketing · Professional · MBE™

AIS

Mastering AI in Sales

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Sales & MarketingProfessional level
30 Hours18 Modules
Self-pacedLearn at your own pace
CertificationEarn an MBE™ Credential

About the AIS Certification

Sales teams are being handed AI tools faster than anyone is teaching them what to do with the output. One rep trusts a lead score blindly, another ignores it, a third pastes a generated email without reading it. The result is inconsistent use and a good deal of wasted license spend.

Participants learn how the models behind these tools work, how to judge their output, and how to apply them at each stage of the cycle: finding buyers, scoring them, personalizing outreach, running discovery, reading pipeline risk and drafting proposals.

What You Will Learn

  • Distinguish sales tasks that AI should automate, augment or leave to the seller
  • Explain how machine learning models and large language models produce their output
  • Design a conversational AI flow for a defined stage of the sales funnel
  • Combine intent signals, predictive lead scores and enrichment data to prioritize accounts worth pursuing
  • Build personalized outreach sequences, content and proposals with generative AI while protecting trust and voice
  • Use conversation intelligence to review discovery calls and prepare negotiations with AI insight
  • Read AI deal-risk and forecast signals as evidence to inspect in a pipeline review
  • Apply responsible AI, data governance and change management when embedding AI in daily sales workflow

What you take away

Skills You’ll Build

Mastering AI in Sales skills
AI literacy for sellers
Conversational AI design
Signal-based prospecting
Predictive lead scoring

Core Topics

  • AI-Powered Selling
  • Sales Productivity Enhancement
  • Customer Engagement Optimization
  • Intelligent Prospecting
  • Sales Analytics
  • Forecasting & Planning
  • Digital Sales Transformation
  • Ethical AI Usage
  • Strategic Sales Execution
  • Customer Insights

Who Is This Course For?

Any revenue team that has already bought AI tooling, or is about to, has a reason to enroll. Sales professionals and business development executives learn to prospect from signals rather than lists. Account managers use conversation intelligence and CRM insight to spot expansion and risk in their accounts.

Sales leaders and sales operations staff gain the literacy to choose tools, set guardrails and interpret AI forecasts without taking them on faith. Channel and partner managers apply the same methods to partner pipelines. A mixed cohort of sellers, managers and operations works well, since the modules alternate between hands-on workflows and the judgment needed to govern them.

  • Sales professionals
  • Business development executives
  • Account managers
  • Sales leaders
  • Entrepreneurs
  • Channel and partner managers

What’s Included?

  • Self-paced modules you can revisit anytime
  • Digital study resources and templates
  • Knowledge checks and practice assessments
  • A digital, verifiable MBE credential on completion

Course Outline

18 Modules30 hoursSelf-paced

Eighteen modules move from literacy to a working system. Module one reframes the seller's role as AI absorbs activity-driven tasks, and module two supplies the vocabulary of data, models and large language models. Modules three to seven cover the front of the funnel: conversational AI, signal-based lead identification, predictive scoring, personalization at scale and conversation intelligence.

Modules eight to twelve apply AI to pipeline and forecasting, the CRM stack, proposals, content at scale and negotiation preparation. Modules thirteen and fourteen address responsible AI, privacy and governance; fifteen and sixteen the human skills and change management adoption needs. Module seventeen designs the daily workflow and the capstone assembles an AI-augmented playbook.

1. Redefining Sales: The Impact of AI on the Sales Professional
  • The Evolution of the Sales Role: From Persuasion to Insight
  • How AI Reshapes Sales Strategy: Automate, Augment, Replace
  • From Activity-Driven to Insight-Driven Selling
  • AI Adoption in Sales: Trends, Data, and the Skills Gap
2. Foundations of AI Literacy for Sales
  • What Artificial Intelligence Actually Is
  • How Machines Learn: Data, Models, and Training
  • Generative AI and Large Language Models for Sellers
  • Mapping AI Across the Sales Cycle
3. Conversational AI and Chatbots for Sales Engagement
  • What Conversational AI Is: From Scripted Bots to LLM Assistants
  • Conversational AI Across the Sales Funnel
  • Designing Effective Sales Chatbot Conversations
  • Deploying Conversational AI Across Channels
4. AI for Lead Identification and Opportunity Discovery
  • From Cold Lists to Signal-Rich Prospecting
  • Defining the ICP and Buyer Personas with AI
  • Buyer Intent Signals and Opportunity Discovery
  • AI Prospecting Tools and the Enrichment Workflow
5. Predictive Lead Scoring and Sales Intelligence
  • From Rules to Prediction: The Evolution of Lead Scoring
  • The Data Behind the Score: Signals, Sources, and Features
  • How a Predictive Lead-Scoring Model Works
  • Sales Intelligence: Enriching the Picture Beyond the CRM
6. Scaling Personalized Communication with AI
  • The Personalization-at-Scale Problem
  • How AI Personalization Engines Work
  • Building Personalized Sequences: A Practitioner Workflow
  • Measuring, Tuning, and Protecting Trust
7. Enhancing Discovery and Customer Conversations with AI
  • Discovery in the Age of AI
  • Conversation Intelligence: What AI Hears
  • Running Better Conversations: A Practitioner Workflow
  • Reading the Signals Critically: Accuracy, Trust, and Consent
8. AI-Driven Pipeline Management and Forecasting
  • Why Forecasts Miss and Pipelines Rot
  • The Anatomy of a Healthy Pipeline
  • How AI Reads Deal Risk and Pipeline Health
  • How AI Forecasting Works
9. CRM Intelligence and the AI-Enabled Sales Technology Stack
  • From Filing Cabinet to System of Intelligence
  • Anatomy of the AI-Enabled Sales Stack
  • How AI Makes the CRM Intelligent
  • Data Quality and the Single Source of Truth
10. Creating High-Impact Proposals with AI
  • Why Proposals Decide Deals
  • The Proposal Lifecycle and Where AI Fits
  • How Generative AI Drafts and Personalizes at Scale
  • The Risks: Hallucination, Filler, and Voice Drift
11. Generative AI for Sales Content and Outreach at Scale
  • The Content Bottleneck in Modern Selling
  • How Generative AI Produces Sales Content
  • Personalization at Scale: Resolving the Core Tension
  • Failure Modes and Guardrails
12. Preparing for Negotiation with AI Insights
  • Why Preparation Wins Negotiations
  • The AI Inputs to a Negotiation
  • From Data to Negotiation Signal
  • Failure Modes and Guardrails
13. Responsible and Ethical AI Use in Sales
  • What Responsible AI Means for Sellers
  • Where AI Selling Goes Wrong: Bias, Opacity, and Manipulation
  • The Governance Frameworks: NIST AI RMF and the EU AI Act
  • Putting It Into Practice: Disclosure, Checklists, and Human Oversight
14. Data Privacy, Governance, and Building Customer Trust in AI-Driven Sales
  • Why Privacy and Trust Decide Whether AI Sells
  • How Customer Data Moves Through the AI Sales Stack
  • Building a Sales-Data Governance Program
  • Vetting AI Sales Tools: DPIAs and Vendor Due Diligence
15. Human Skills for the AI-Augmented Sales Professional
  • Why Human Skills Rise in Value as AI Rises
  • The Division of Labor Between Seller and Machine
  • Empathy, Listening, and the Trust AI Cannot Manufacture
  • Judgment: Deciding When to Trust the Tool
16. Driving AI Adoption: Change Management for Sales Teams
  • Why Sales-AI Rollouts Stall
  • How Change Actually Spreads Across a Sales Team
  • A Change Model for the Sales Floor
  • Enablement, Incentives, and Making AI the Default
17. Integrating AI into the Daily Sales Workflow
  • The Seller's Day, Reimagined
  • The Integrated AI Sales Stack
  • Deciding What to Automate, Augment, or Keep Manual
  • A Personal AI Operating Rhythm
18. Capstone: Building Your AI-Augmented Sales Playbook
  • From Skills to System: What a Playbook Is
  • Mapping AI Across Your Sales Cycle
  • The Human-Judgment and Governance Backbone
  • Building Your Playbook: A Step-by-Step Method

Complete the course assessments to earn the AIS credential

Frequently Asked Questions

Do participants need a technical background to follow the AI content?

No. Module two exists precisely so that sellers without a data background can follow the rest: it explains what artificial intelligence is, how machines learn from data, and what a large language model does, all at the depth a practitioner needs to judge a tool rather than build one. Everything after that is framed as sales workflow, not engineering.

Which parts of the sales cycle does the program cover?

Nearly all of it. Lead identification and opportunity discovery come first, followed by predictive lead scoring, personalized outreach sequences, discovery conversations supported by conversation intelligence, pipeline management and forecasting, the CRM and wider technology stack, proposal creation, sales content at scale and, in module twelve, negotiation preparation using AI inputs. Later modules then step back to governance, human skills, adoption and the design of a daily workflow.

How is the question of trust and ethics handled?

Both inside the practical modules and in dedicated ones. The personalization module ends with measuring, tuning and protecting trust, the discovery module asks participants to read AI-generated signals critically, and the proposals module names hallucination and voice drift. Module thirteen covers responsible AI, including bias, opacity and manipulation, disclosure and human oversight, and module fourteen covers data privacy, a sales-data governance program and vetting AI vendors. Sellers finish knowing where a human must remain accountable.

Will the content work with the tools we already use?

The program teaches categories and workflows rather than one vendor's product, which is what makes it transferable. Participants learn the anatomy of an AI-enabled sales stack, how a predictive scoring model is built, how personalization engines operate and how conversation intelligence listens, then map that understanding onto whatever CRM and prospecting tools your organization has licensed.

How does forecasting change when AI is involved?

Module eight starts with why forecasts miss and pipelines decay, then shows how AI reads deal risk from activity, engagement and timing data and how an AI forecast is assembled. Participants learn to treat the output as evidence to inspect in a pipeline review, not as a replacement for the review, and to ask what data the model was missing.

What does the credential represent and how is it tracked?

Each participant who completes the modules and assessments is issued a digital, verifiable MBE credential by Blue Ocean Corporation, which they can share on a professional profile. On the organization's side, the administrator dashboard retains enrollment and completion records for every cohort, so capability planning and audit questions can be answered without collecting certificates by hand.

How do I register for this course?

Use the Register Now button on this page. It opens Mastering AI in Sales on the Blue Ocean Academy website, where you can enroll and start learning at your own pace.

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Your MBE credential is issued digitally and can be verified by employers. It carries the Mastering Business Excellence name, so you can add it to your professional profile as soon as you complete the course.

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