Stop scrambling to figure out how AI fits into your digital transformation, and start using these tools to guide the way.
Technological change is fast. Most organizations are concerned that artificial intelligence (AI) will have a dramatic impact, quickly, especially since the launch of ChatGPT. Everyone is now pondering the potential impact of generative artificial intelligence, both for organizations and society.
Unfortunately, most organizations are not equipped to deal with rapid technological change. They focus on refining what they do today, and understandably so—it has been the basis for their competitive success thus far. With the current explosion of AI applications, organizations will need to find a way to adapt.
I’m here to help. As the author and instructor of the Watspeed Digital Transformation Certificate Program at the University of Waterloo, I’ve studied organizations big and small to learn how to undertake digital change. In seeking to understand the artificial intelligence challenges, my colleagues and I have developed three simple steps for considering your own AI projects.
Recent history has set a strange stage for the AI revolution. Covid-19 forced many organizations to change more quickly than they would previously have thought possible—but it didn’t usually change the fundamentals of their culture or work organization.
The upheaval of Covid-19 has been followed by a period of reflection, with more corporations understanding that the world has changed. This has prompted greater attention to developing a technology-based digital transformation strategy or, for others, finding their own new balance between the old world and the new.
Artificial intelligence is challenging these new normals. Just as organizations have been starting to feel that they are regaining a measure of post-Covid stability, the AI hype is demanding yet more radical change. Many organizations fear that unless they get on the AI train now, they will be left behind.
The fourth industrial revolution requires that organizations be aware of and ready for rapid technological change, understanding the technological developments that are happening in their industry and adopting and implementing appropriate strategies. A digital learning culture is one of the essential elements.
Living in a world of digital transformation should involve the establishment of digital early warning systems. The apprehension with which AI is now being regarded is an indicator that most organizations don’t have them.
What to understand about the AI hype
It is important to understand two aspects of the AI hype. It is certainly true that AI has huge potential to radically impact many aspects of organizational activity, and that you need to carefully consider what it mans for your organization. However:
- The term artificial intelligence applies to many different things and is much abused today. The recent discussion has been about generative AI, which “generates” a response to questions. However, organizations frequently use the term to refer to machine learning and other technologies that have been around for some time. This is confused and adds to the hype.
- Organizations have done very little with generative AI so far. In a 2024 report by ETR, Generative AI Growing in Business, only a minority of organizations surveyed were using it for production tasks, and most of these were relatively simple and unlikely to indicate radical transformation.
So, while it is very important you understand and develop your response to AI, you have time to do this carefully. Our methodology will help you to assess your AI project ideas. Our tools allow you to assess whether artificial intelligence is the appropriate technology to apply to address the need you have identified.
Step 1: Should you be using AI for this project?
If your response is NO to any of the below requirements, you should carefully examine whether artificial intelligence is appropriate for your project.
| AI requirement | Description |
| Does your data change rapidly? | If you are simply trying to understand a set of data that doesn’t change quickly over time, you don’t need AI. You can analyze it with technology that uses basic analytics. |
| Are very complex rules required? | If your data does change quickly, AI is only useful if you need to use complex rules to achieve your objective, answering complex questions or finding complex patterns. |
| Can you tolerate inaccuracy? | AI is not accurate or correct. It cannot be used for any purpose where this cannot be tolerated. |
| Is relevant data available? | Have you got or can you get the data that will be needed? |
| Is representative data available? | Is the data representative so that it will enable your AI to provide results that are of value? |
| Is enough data available? | Is there enough of the data to enable your AI to provide the desired results? |
| Can you adequately protect the data? | If you have good data, will you be able to protect it to ensure personal and organizational interests are safe? |
Step 2: Which project should be my highest priority?
You may have a number of possible artificial intelligence projects in your organization and limited resources to pursue them, so you’ll need to prioritize. The below rating matrix will help. Feel free to add to it if there are additional criteria that are important to you.
The criteria in the artificial intelligence project selection matrix are:
| Factor | Description |
| Measurable benefits | You should be able to measure the impact that the project will have on the metrics that your organization uses to assess its performance. |
| Unmeasurable benefits | Your project may contribute to the organization in ways that are beneficial but impossible to measure. |
| Wider use | Projects that will develop resources or capabilities that will be of value to the organization beyond the initial project scope. |
| Ease of implementation | Easier implementation increases the probability of project success and of its sustainment. |
The matrix is provided below, with sample data provided to illustrate its use. The weight column indicates the maximum score for each factor, which allows you to vary the emphasis given to each Factor in your decision-making. In this example, Project 3 is the best choice.
| Factor | Weight | Project 1 | Project 2 | Project 3 | Project 4 |
| Measurable benefits |
10 |
9 |
6
|
9 |
3 |
| Unmeasurable benefits |
10 |
3 |
5 |
9 |
8 |
| Wider use |
6 |
4 |
6 |
5 |
4 |
| Ease of implementation |
8 |
8 |
6 |
4 |
3 |
| Overall rating |
|
24 |
23 |
27 |
18 |
Step 3: Am I able to use artificial intelligence for this project?
Using artificial intelligence requires that the organization has the necessary resources and capabilities. The below tool helps you review this and develop an action plan to address any deficiencies you find.
| Resource | Description |
| Finance | The budget for your project. This should be in a form used in your organization that may be presented for project approval. |
| Expertise | Do you have the skills to complete the project and support it after implementation? These may include internal and external skills, but must only include those that you are confident will be available for the project. |
| Computing  capacity | Can your computing equipment run the technology you are introducing? Artificial intelligence usually requires substantial, powerful computing capability. |
| Leadership support | Will the senior management team provide the support needed to drive the introduction of the technology in the organization? |
| Legal / regulatory / ethics | Have you reviewed the ethical, legal and regulatory implications of your project and developed plans to ensure compliance and socially responsible technology use? |
| Maintenance capability | Do you have the expertise and resources to maintain the technology, or will your project develop it? |
Review the requirements for successful artificial intelligence adoption using the following tool and develop your own plans to address deficiencies.
| Requirement | What is available | Sufficient? | Action required |
| Finance | |||
| Expertise | |||
| Computing power | |||
| Computing infrastructure | |||
| Leadership support | |||
| Legal / regulatory / ethics | |||
| Maintenance capability |
These three simple steps provide tools to help you consider your artificial intelligence projects. They will enable your management team to carefully consider the use of artificial intelligence in your organization.
