Course
Implementing AI Solutions in Business
BasicSkill Level
Updated 01/2026Start Course for Free
Included withPremium or Teams
TheoryArtificial Intelligence2 hr16 videos56 Exercises3,700 XP48,240Statement of Accomplishment
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Discover how AI can deliver business value
The latest AI tools and technologies, such as ChatGPT, have truly spectacular capabilities, but how does this translate into business value? In this course, you’ll learn about the capabilities and limitations of AI and how it can improve employee productivity, automate business processes, and provide better, more personalized customer experiences.Learn how to build an AI Proof of Concept (POC)
The most amazing AI products and services likely started out as basic proof of concepts (POCs). You’ll learn about the various stages and personas involved with creating a POC, all the way from scoping opportunities to building a project team and understanding resource limitations. You’ll also learn about data management, storage, and privacy to ensure that your POC is compliant with the relevant governing regulations.Build a case for AI implementation in the business
A single AI POC is often the start of a much wider discussion on implementing more AI solutions across the business. In this course, you’ll understand when and how to turn a POC into a full-fledged solution, how to identify points of resistance to AI adoption, and how to communicate the value of AI to the wider business and customers.Feels like what you want to learn?
Start Course for FreeWhat you'll learn
- Assess success metrics that measure business value, model performance, explainability, and solution reliability for an AI initiative
- Differentiate between the data, infrastructure, and talent needs of an AI proof of concept and those of a full-scale deployment
- Evaluate potential AI use cases by applying value, risk, data availability, and feasibility criteria
- Identify the five implementation phases required to deploy AI solutions in a business environment
- Recognize the core principles of a Responsible AI framework that ensure ethical and compliant AI use
Prerequisites
There are no prerequisites for this course1
Getting Started with AI
Learn what AI is, how it has evolved, and how it is different from other non-AI data solutions. In this chapter, you will begin building a framework for how to implement AI into your business, including key elements to an AI strategy, phases for implementation, and basic technical design. Finally, you'll learn about the importance of Responsible AI governance throughout the entire process.
2
Benefits, Limitations, and Use Cases of AI
You now know what AI is and how to think about it responsibly. It's time to gain a better sense of its benefits, limitations, and use cases in business. In this chapter, you'll do just that! You'll understand the value AI can bring to an organization as well as the areas it lacks in. You'll go through some high-level use cases across different departments in a business. Finally, you'll learn about principles for choosing a great use case for an AI solution.
3
Building a Proof of Concept
With use cases in mind, it's time to build a proof of concept! This is a small project that will determine the feasibility and estimate further business value if fully implemented. In this chapter, you will learn the phases of a POC, what makes them successful, and the important components to think about regarding technical infrastructure and data. Finally, you'll learn about the types of roles required for your POC project team.
4
Beyond the POC
In this final chapter of the course, you will learn the final steps of an AI solution implementation - assessing the POC, scaling, and aligning culture and skills. You will understand the areas in which a POC can be evaluated as well as what are good indicators for moving forward with scaling the solution. You will go over the big components to focus on for scaling to a full implementation, including requirements for culture and upskilling folks in your business.
Implementing AI Solutions in Business
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