Executive Certification Program

Total Economic Impact of Artificial Intelligence

An executive-level course designed to help leaders evaluate, quantify, and communicate the financial value of AI initiatives using ROI, NPV, payback, and the TEI framework.

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AI Financial Impact
Measure ROI, cost savings, and business value of AI initiatives.
📈
TEI & Financial Models
Build credible AI business cases using NPV, payback, and risk analysis.
🎯
Executive Decision Support
Present AI investments with clarity, confidence, and data-backed narratives.

What you will learn

Quantify AI Value with
Financial Confidence

In Total Economic Impact of AI, you will gain the skills to evaluate, model, and communicate the financial impact of AI initiatives. This course enables leaders to move beyond hype and make data-driven AI investment decisions grounded in measurable business value.

  • ✔ Understand the Total Economic Impact (TEI) framework and its application to AI investments.
  • ✔ Calculate ROI, cost savings, payback periods, and NPV for AI initiatives.
  • ✔ Build detailed financial models covering costs, benefits, risks, and assumptions.
  • ✔ Identify productivity, automation, revenue, and compliance value drivers of AI.
  • ✔ Align AI investments with enterprise strategy, KPIs, and executive priorities.
  • ✔ Present credible, executive-ready AI business cases to boards and stakeholders.
Executives analyzing AI financial impact and ROI dashboards

There are 4 modules in this course

This executive course helps leaders evaluate the financial impact of AI using the Total Economic Impact (TEI) framework. You’ll learn to quantify ROI, model costs and benefits, manage risk, and present executive-ready AI business cases.

Foundations of AI Economic Impact
Module 1  •  3 lessons
Module details

Understand how AI creates economic value in enterprises. This module introduces the Total Economic Impact framework and explains key financial concepts such as ROI, payback, and NPV in the context of AI initiatives.

What's included
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3 lessons
  • Understanding the TEI Framework
  • AI Investment Drivers: Productivity, Automation, Innovation
  • ROI, Payback Period, and NPV Explained
Building Financial Models for AI
Module 2  •  3 lessons
Module details

Learn how to build structured financial models for AI initiatives by identifying costs, benefits, and assumptions. This module covers infrastructure, training, efficiency gains, revenue impact, and compliance benefits.

What's included
▶
3 lessons
  • Cost Modeling: Infrastructure, Data, Training
  • Benefit Modeling: Efficiency, Revenue, Compliance
  • Assumptions, Sensitivity, and Risk Adjustment
Strategic Decision Support & Stakeholder Alignment
Module 3  •  3 lessons
Module details

Translate financial analysis into executive decisions. This module focuses on building persuasive AI business cases, aligning investments with strategy, and communicating value to boards and senior stakeholders.

What's included
▶
3 lessons
  • Creating TEI-Based AI Business Cases
  • Visual Storytelling for Executives
  • Aligning AI Metrics with Strategy & KPIs
Embedding TEI into Organizational Practice
Module 4  •  3 lessons
Module details

Learn how to operationalize TEI across the organization. This module covers governance, ongoing evaluation, and tracking realized value against forecasts to ensure long-term AI success.

What's included
▶
3 lessons
  • TEI Governance and Model Maintenance
  • Scaling AI Value Across Departments
  • Post-Investment Value Tracking
🎓
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV and demonstrate your ability to evaluate AI investments with financial rigor.

What leaders say about Total Economic Impact of AI

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CFO / Finance Director, [Industry]

“(Replace with verified quote) This course helped us build a credible TEI-based business case for AI. We aligned costs, benefits, and risk adjustments, and presented ROI/NPV clearly to leadership for faster approval.”

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Head of Data & Analytics, [Company]

“(Replace with verified quote) The modeling approach was practical. We mapped infrastructure and change costs, quantified productivity gains, and used sensitivity analysis to defend assumptions during stakeholder reviews.”

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VP Strategy / Transformation, [Industry]

“(Replace with verified quote) The best part was stakeholder communication. We turned AI metrics into executive-ready storytelling and connected TEI outcomes directly to KPIs and strategic priorities.”

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Program Manager, AI & Automation, [Company]

“(Replace with verified quote) This gave us a repeatable way to track value after deployment. We set governance for TEI updates, monitored realized benefits vs forecasts, and improved decision-making across teams.”

Frequently asked questions

What is “Total Economic Impact of AI” about?

This course helps leaders quantify the business value of AI initiatives using the Total Economic Impact (TEI) approach—covering costs, benefits, risk adjustment, ROI, payback, and NPV.

You’ll learn how to build credible, decision-ready AI business cases and communicate them clearly to executives, finance teams, and stakeholders.

Is this course only for finance or CFO teams?

No. It’s designed for business leaders, transformation teams, product leaders, and AI program owners who need to justify AI investments with financial clarity.

If you collaborate with finance (or need approvals), this course helps you speak the same language and defend assumptions confidently.

Do I need to be good at finance or advanced Excel?

No advanced finance background is required. We explain ROI, NPV, payback, and modeling logic in a practical, step-by-step way.

You should be comfortable with basic numbers and business thinking, but you don’t need to be a finance expert.

Will I learn how to calculate ROI and NPV for my own AI project?

Yes. You’ll learn how to structure costs and benefits, choose assumptions, and compute ROI, payback period, and NPV for real AI initiatives.

You can apply the same approach to automation, productivity, customer experience, and revenue-impact AI use cases.

What costs should I include in an AI business case?

Many teams underestimate total costs. We cover common categories such as data preparation, infrastructure, licenses, implementation, change management, training, security, and ongoing maintenance.

You’ll learn how to avoid “hidden costs” that weaken credibility during stakeholder review.

How do I quantify benefits like productivity or time savings?

You’ll learn practical methods to convert time savings into monetary value, estimate adoption, and map benefits to measurable KPIs.

We also cover how to separate potential value from realized value so your model stays realistic.

How does the course handle risk and uncertainty in AI value estimates?

We address risk by teaching sensitivity checks, scenario thinking, and risk-adjusted assumptions—so your case remains defensible even when outcomes vary.

This helps you present a balanced view instead of overselling AI impact.

Will this help me get faster approval from stakeholders?

It can. A strong TEI-based narrative makes it easier for leadership and finance to evaluate your proposal and compare it against other investments.

You’ll learn how to present assumptions, value drivers, and KPIs in an executive-ready format.

Is the course self-paced and how long do I have access?

Yes, it’s self-paced so you can learn around your work schedule and revisit modules when needed.

You’ll retain access to the course materials for an extended period after enrollment, so you can reuse the framework as your AI initiatives evolve.

Will I receive a certificate of completion?

Yes. After completing the course requirements, you’ll receive a digital certificate you can share on LinkedIn, your resume, or within your organisation.