As Artificial intelligence continues to transform industries, with very few exceptions, there are only two main ways that companies can gain a reliable competitive advantage with artificial intelligence:

• Data Dominance: Monopolizing data within a particular industry and/or business function to make sure that their product is so much better than its competitors so much so that they can’t compete anymore; and
• Critical Capabilities: Building the internal skills, resources, and culture needed to leverage AI well into the company’s future, providing the company with the ability to wield artificial intelligence towards company objectives quickly, with the highest chance of success, and without costly waste or risk.

The fact of the matter however is that only a small portion of AI projects are successful with millions being wasted on Artificial Intelligence initiatives every year. This is because most companies are just starting to learn about AI use-cases in their industries; they haven’t even begun to think through the skills, resources, and culture that their company needs if they want to use AI to win market share and achieve data dominance.

In this best practice training bundle, we break down data dominance and these critical capabilities to provide guidance on how to bolster them within any organization to deliver ROI and avoid risks.

What will set you apart:

On completion of this course, you will walk away with:

• The ability to assess the AI readiness of any business organization;
• A practical plan to successfully drive and implement an AI strategy within a business environment;
• An understanding of the various internal and external considerations to ensure successful AI project delivery; and
• Insight into the value, risks, and opportunities associated with implementing an AI strategy.

Takeaway resources:

• AI Readiness Canvas;
• AI Project’s Data Worksheet;
• AI Adoption Essentials Cheat-sheet;
• AI Career Roadmap for Non-technical Professionals Bundle;
• AI Adoption Strategy Bundle;
• AI Terms and Components Definitions (ML, Chatbots, NLP, RPA, etc.).

Bonus Resources:

• Full training kit on "How to run your own AI Strategy Design Sprint";
• AI Design Sprint Facilitator's Checklist;
• The AI Design Sprint Preparation Guide.

Benefits:

• Understand AI, what to do with it, how, when, where, and why;
• Have a clear understanding of the enterprise problem AI is intended to be applied to;
• Build successful AI projects with tailored consulting;
• Be able to translate business/enterprise problems into data questions;
• Have the requisite knowledge to assemble and maintain teams to develop and deploy AI projects.

Course Curriculum

Learn to develop an AI strategy that aligns with the organization’s goals as you work through the modules of this online short course.

Module 1: AI Strategist Role Definition

• The job of an AI Strategist;
• Analytics Awareness;
• Delivering AI Use-Cases.

Module 2: AI Strategist Skills Definition

• Necessary Skills for AI Strategist;
• Developing the Ability to deliver AI Use-Cases;
• Defining a Business Problem;
• Prioritizing Business Problems.

Module 3: Managing AI Adoption Phases

• Building blocks of AI and Strategy;
• Understanding the AI Project building blocks;
• Knowing when AI Isn't for Your Client.

Module 4: Challenges of Integrating AI

• Framework for enterprise AI adoption;
• The Challenges of Integrating AI;
• How to Overcome these Challenges.

Module 5: Ethical implications of AI

• Transparency;
• Accuracy;
• Accountability;
• Job security and AI;
• Rules of Thumb on AI and Job Security.

Module 6: Vendor Selection Process

• Support for the AI lifecycle (Problem Scenario);
• Viability (Motivation);
• Modern software engineering (Architecture);
• Support for a broad range of users (Usability).

The recommended weekly time commitment for core content is 4-5 hours, taking into account the busy lifestyles of working professionals, with an additional 2-3 hours recommended for non-compulsory weekly extension activities, should you have the time. Each part of the course curriculum is released weekly, allowing a flexible but structured approach to learning. You’ll be supported as you engage in individual activities and group discussions, ensuring you feel confident to submit your best work at each weekly deadline.

Workshop key takeaways:

The key takeaways from this workshop are:

• AI or data science is not magic and will not solve business problems instantaneously; The main takeaway shall be on how to Avoid AI Novelty;
• AI and data science is still a dark art; Takeaway the understanding of the required framework commitments to build successful AI applications;
• AI for AI’s sake is a bad idea; Takeaway is the understanding of how to choose tools for the value it can deliver to your business, and not because it uses AI in some form.

The 3 core competencies an AI strategist should have, covered in this workshop include:

• Deep understanding of a business domain: An AI strategist is typically a non-technical professional with knowledge about a certain sector(s) or industry; A fundamental grasp of the business’s customers, sources of revenue, costs, operations etc. will help the strategist understand and prioritize where in the value chain AI implementation will have the most impact. This is where the Data scientists and Engineers fall short. Most of them do not understand the business problem to be solved.
• Knowledgeable grasp over the fundamentals of Machine Learning: The AI strategist should have an understanding of the fundamentals of the AI language, making it easier to communicate with the data scientists and engineers and make the bridging of the gap between IT and business that much easier.
• Ability to separate AI myth versus reality: Most of the disappointments in AI implementations arise because of misguided expectations. An astute AI strategist will be able to articulate in solving a business problem, how much will be done by an AI system and how much by the human system hence setting the right expectations.

Individual Benefits:

With the advent of AI in virtually all industries, non-technical professionals with initiative are gaining valuable and rare AI knowledge and experience, setting themselves up for vastly more career opportunities and income as AI Strategists, Consultants, and Capability Map advisors. The interesting bit is that these Non-technical professionals did not need to:

• Go to AI events every month, spending thousands on tickets and airfare;
• Get online Executives; or
• Learn to code

Who should take this course?

This workshop is suitable for both graduate-level business and related students, C-Level executives or business leaders, and managers looking to gain and/or maintain their career competitive advantage in successfully guiding AI strategy and AI technological advances into enterprise business strategy. Be prepared and stay relevant with program insights presented to assist decision-makers with embracing AI adoption at scale.