16 Jun
995 CAD

AI solution design


What is artificial intelligence (AI)? In terms of public and private affairs, what does this mean? In what ways can artificial intelligence benefit your organization?

The objective of this training is to provide an engaging blend of applied concepts, examples of key technologies, and examples of how AI can be used in business to demonstrate the realities of AI technology today and show how it can be used to meet a current or future business need.

The training will help you understand how AI can support business and service strategies, as well as the opportunities that AI presents to society. This course will cover key AI technologies such as machine learning and deep learning, image processing, and natural language processing.

In this training session, we will show you how to design, implement, manage, and govern your digital solutions, combine AI with the right resources, and evaluate their performance.

Audience: Public and private sector business managers and architects

Prerequisites: None


Participants will explore AI: the practical opportunities it offers, its different domains, its governance, its prerequisites, the design process and implementation of an AI product, its future and the importance of ethics in AI. More importantly, they will understand the fundamental differences between the design process of an AI solution and that of an information system.

Lesson plan

  1. Part one
    1. AI concepts and definition
    2. Domains of AI and practical examples of its uses
    3. Essential factors for success
    4. The governance of AI in an organization
  2. Part Two:
    1. The 6 stages of designing and implementing an AI product
    2. Significant differences between AI solution design and information system design
    3. AI ethics
    4. The future of AI

Training Method

During the training session, participants will have the opportunity to apply their new knowledge to practical case-scenario exercises, individually and as a group.


  1. Introduction to AI
    • Context and history
    • Concepts and definition
    • The different domains of AI illustrated by real cases
  2. The 6 stages of designing an AI solution
    • Define product goals
    • Establish criteria for data and data access
    • Assign responsibilities for the design and development (profiles, expertise, roles, etc.)
    • Elaborate new processes and manage change
    • Plan for validation and continuous training of the AI model
    • Assess the commercial value of the AI solution
  3. Significant differences between AI solution design and information system design

Beyond the 6 stages of designing an AI solution, we will take a step-by-step look at the differences between AI solution design and information system design.

  • Analysis of AI maturity
  • Approach to needs identification
  • 21 questions to help identify the best AI model
  • AI business case analysis (data-driven)
  • AI solution design and development/implementation team (RACI)
  • AI solution maintenance/sustainability and evolution
  1. AI ethics
    • The basic premises in AI ethics
    • Understanding the potential ethical issues associated with an AI solution
      • Black box vs glass box
      • Data sharing and correlation
      • Discrimination or inequity (bias)
      • Etc.
  2. The future of AI
    • Future developments: What can we expect?
    • How to prepare your organization in order to maximize the use of AI
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