Team Academy/Generative AI For Marketing & Sales

  • $770.38

Generative AI For Marketing & Sales

  • Course

Build future-ready, revenue-focused capabilities through this Generative AI for Marketing & Sales program, designed for professionals responsible for customer acquisition, engagement, conversion, and growth. This hands-on program enables learners to move beyond traditional campaigns and static reports toward AI-powered marketing intelligence and sales enablement.

Participants learn how Generative AI can be applied across the marketing and sales lifecycle, including customer research, content creation, campaign planning, personalization, lead qualification, forecasting, and executive reporting. The program focuses on practical AI usage to analyze customer data, generate high-impact content, simulate campaign outcomes, and support faster, data-driven go-to-market decisions.

Eligibility Criteria - Who Is It For ?

  • This program is designed for professionals involved in marketing strategy, digital marketing, sales operations, business development, CRM, and revenue growth.

  • Professionals who want to enhance traditional marketing and sales practices using Generative AI for deeper customer insights, faster execution, and scalable personalization.

    Best suited for :

  • Marketing Managers & Digital Marketers

  • Sales Managers & Business Development Professionals

  • Growth, Performance & Demand Generation Teams

  • CRM, RevOps & Sales Operations Professionals

  • Brand, Content & Campaign Managers

  • Entrepreneurs and Business Leaders

  • Participants should be comfortable working working with basic data such as customer lists, CRM reports, campaign metrics, or sales pipelines.

  • A strong interest in applying AI to marketing strategy, content, lead generation, and revenue optimization will maximize learning outcomes.

Course Features

  • AI-Driven Marketing & Sales Curriculum – tructured modules covering Generative AI applications across customer research, content, campaigns, lead management, sales forecasting, and reporting.

  • Hands-On AI Training – Practical exercises using real marketing and sales scenarios, AI prompts, and datasets.

  • Capstone AI Marketing & Sales Project – Build an AI-assisted campaign or sales enablement solution demonstrating real-world application.

  • Interactive Learning – Guided prompt labs, assignments, and case-based discussions.

  • Industry-Relevant Use Cases – Applications across B2B, B2C, digital marketing, SaaS, retail, and enterprise sales environments.

  • Expert Guidance – Learn from professionals with deep experience in marketing strategy, sales leadership, and applied AI.

  • Flexible Learning Options – Live instructor-led sessions with access to recordings and materials.

  • LinkedIn Shareable Certificate – Validate your expertise in applying Generative AI for marketing and sales.

Contents

Module 1 : Marketing & Sales Foundations & the Role of Generative AI

1.1 Overview of modern marketing and sales ecosystems
1.2 Limitations of traditional marketing and sales approaches
1.3 Introduction to Generative AI concepts for go-to-market teams
1.4 Where AI fits in the marketing & sales lifecycle
1.5 Responsible and ethical use of AI in customer-facing functions

Module 2 : AI-Assisted Customer Research & Insights

2.1 Using AI to analyze customer personas and segments
2.2 Extracting insights from CRM, surveys, and market data
2.3 Identifying customer intent and buying signals
2.4 Competitive and market intelligence using AI
2.5 Validating AI insights with business judgment

Module 3 : AI for Content Creation & Campaign Planning

3.1 AI-powered copywriting for ads, emails, and landing pages
3.2 Generating content for social media, blogs, and campaigns
3.3 Campaign ideation and messaging frameworks using AI
3.4 Personalization at scale with Generative AI
3.5 Maintaining brand voice and quality control

Module 4 : Lead Generation, Qualification & Sales Enablement

4.1 AI-assisted lead scoring and prioritization
4.2 Improving conversion through personalized messaging
4.3 Sales pitch creation and objection handling with AI
4.4 AI-supported proposal, email, and follow-up generation
4.5 Supporting sales teams with real-time AI insights

Module 5 : Forecasting, Performance & Revenue Insights with AI

5.1 AI-assisted pipeline and sales forecasting
5.2 Campaign performance analysis using AI
5.3 Identifying trends, risks, and growth opportunities
5.4 “What-if” simulations for pricing, offers, and campaigns
5.5 Improving ROI and decision-making speed

Module 6 : AI-Powered Reporting & Executive Communication

6.1 Creating management-ready marketing and sales summaries
6.2 Translating metrics into insights and narratives
6.3 AI-assisted dashboards and leadership reporting
6.4 Presenting AI-driven recommendations responsibly

Module 7 : Capstone AI Marketing & Sales Project & Certification

7.1 Selecting a real marketing or sales scenario
7.2 Applying Generative AI end-to-end
7.3 Building an AI-assisted campaign or sales solution
7.4 Presenting insights and growth recommendations
7.5 Certification upon successful completion

Frequently asked questions

You've got questions. We've got answers.

Do I need prior AI or advanced analytics experience to join this program?

Prior hands-on experience with AI or advanced analytics is not required to join this program. The curriculum is intentionally designed to start with foundational Generative AI concepts explained in a risk management context, rather than technical or coding-heavy explanations. Participants are gradually introduced to practical AI usage through structured prompts and guided examples that align with common risk management activities. This approach ensures that both beginners and experienced risk professionals can comfortably follow the program and progressively build confidence in using AI for risk-related decision-making.

What kind of AI tools or techniques will I use during this program?

Participants will work with Generative AI tools and structured prompt frameworks specifically tailored for risk management use cases. These tools are used to support activities such as risk identification from documents and data, enhancement of risk registers, scenario analysis, impact assessment, mitigation planning, and executive risk reporting. The focus is not on learning multiple complex tools, but on understanding how to effectively interact with AI, frame the right questions, validate outputs, and use AI insights responsibly within governance and decision-support processes.

Will I work with real risk scenarios or only theoretical examples?

The program is strongly practice-oriented and emphasizes real-world risk scenarios rather than theoretical or academic examples. Participants work with realistic cases drawn from enterprise risk,operational risk, project risk, compliance, audit, and governance environments. Exercises and projects are designed to mirror actual organizational challenges such as analyzing incident trends,identifying emerging risks, assessing exposure, and preparing management-ready risk summaries.This ensures that the skills learned during the program can be applied immediately in professional risk roles.

Can the skills learned in this program be applied across different industries?

Yes, the AI-driven risk management techniques covered in this program are industry-agnostic. While examples may reference common enterprise scenarios, the underlying frameworks for risk identification, assessment, scenario analysis, and reporting can be applied across finance, operations, projects, compliance, healthcare, IT, manufacturing, public sector, and enterprise governance environments. This makes the program highly adaptable and valuable for risk professionals working in diverse industries and organizational contexts.


How does this program ensure responsible and ethical use of AI in risk management?

Responsible AI usage is a core focus of the program. Participants are guided on how to apply human judgment, validation techniques, and governance checks when using AI-generated outputs. The curriculum covers topics such as data sensitivity, confidentiality, bias awareness, limitations of AIgenerated insights, and the importance of oversight in risk-related decisions. By embedding ethical considerations and governance alignment into every AI use case, the program ensures that AI is used as a decision-support tool, not a decision-maker, fully aligned with enterprise risk and compliance standards.