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Is AI Transforming Your Business? Identifying AI Use Cases

Technology

Oct 18, 2023 - 4 minute read

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Matthew Weaver Consultancy Director

I’ve worked in the IT industry for the last 20 years with almost half of that time in my current role as Consultancy Director. At Objectivity, I’ve met some exceptionally talented people that share similar views and ambitions to my own. I realise now that building great software starts by building great teams. I spend my spare time learning how little I know about my passion for photography. And when the weather doesn’t permit, you’ll find me rolling back the years writing code on various platforms and updating my blog.

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2988 HC Digital Transformation 476X381

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Harnessing the power of artificial intelligence (AI) has become imperative for modern organisations. The capabilities that these technologies provide seem vast, and progress is relentless. And yet, many organisations fail to deliver value from investing in AI. Back in 2018, Gartner suggested that as many as 85% of Machine Learning projects will fail to deliver. Many report that this has not changed significantly since publication.

What Hampers AI Initiatives

Many factors influence success (or lack of it), including:

  • A clear and realistic problem statement.
  • Sufficient and relevant data.
  • Ability to scale from a proof of concept or proof of value to a production solution.
  • Appropriate infrastructure and technical expertise.
  • Resistance to change and a lack of organisational support.
  • Difficulty in integrating models and insights into new and existing business processes.

It’s easy to mistake the features that AI promises with solutions to specific business problems. Knowing what a technology can do is insufficient — we must start with a problem before looking for a solution. Creating well-defined AI use cases that address challenges within your business is a great way to start.

Features Are Not Use Cases

People often use the terms 'features' and 'use cases' interchangeably when, in fact, there are fundamental differences.

Features describe the capabilities of a system or technology. As a simple example, a feature of a kettle may be that it can heat 2 litres of water from room temperature to 100 degrees in 90 seconds. While this may be impressive, it's of little value unless you need boiling water in the next couple of minutes.

Use cases, however, can represent actual problems within your organisation that need to be addressed. They are not just features of a technology without context. Creating use cases can significantly increase the likelihood that your investment in AI technology will provide real value and drive meaningful change.

Without context, it is not possible to understand risks and constraints. There may be assumptions that do not apply when considering your particular needs. For example, an electric vehicle may report a range of 320 miles — in reality, this can be closer to 250 miles when operating in a real-world environment. Use cases, and the steps that follow, can help to avoid unwelcome surprises.

Figure 1: Typical elements of a use case

So, features, while essential, are only one stage of your AI journey. They represent the ‘what’ but often fall short of answering the ‘why’ and ‘how.’ The approach taken here will help us to fill the gaps, taking us from the realm of possibilities to the realm of solutions. 

How To Start Creating AI Use Cases

Begin by identifying and listing pain points or gaps within your business processes. Speak with stakeholders, department heads, and end users to confirm the relevance and value of the items on your list. 

It is not necessary to consider all of the elements of a use case at this point. The initial goal is to define potential areas for improvement. With this done, it’s time to prioritise your list based on the positive impact on your business. One way of doing this is to create a use-case scorecard for each improvement you have identified. 

Each use case will have a simple scorecard consisting of a set of evaluation criteria. The criteria you choose will depend on your specific circumstances — the image below provides an example of a use case scorecard. 

Figure 2: Example of a use case scorecard

A score between 1 and 5 combines with the weighting to give a total outcome rating for the use case. The weighting allows us to set relative importance for each of the criteria. We can now create a prioritised list of use cases providing an initial running order for the next steps. 

The scorecard and assessment process can usually take place without full details of a use case (as shown in Figure 2). Spend only as much effort as you need to during the evaluation stage. 

Final Thoughts

Thinking in terms of use cases rather than features will help to align AI capabilities with specific business challenges. Creating a prioritised list of potential AI use cases is an iterative process rather than simply going sequentially from start to finish. Often, there will be a need to re-examine one or more steps and capture a little more detail. The overall process will look something like Figure 4. 

Figure 3: Composition of a well-defined use case 

Scorecards provide a reference point to review priorities when necessary. If circumstances change, the cards may be updated and re-evaluated. Few people will want to invest in a venture that has an 85% chance of failure.  

By themselves, use cases do not guarantee success. They will help to achieve stakeholder consensus, ensure business context is considered, and clearly outline how to proceed. Don’t rely purely on features to deliver value for your organisation — move the odds in your favour by creating use cases that align with your unique business needs.  

2988 HC Digital Transformation 476X381
Matthew Weaver Consultancy Director

I’ve worked in the IT industry for the last 20 years with almost half of that time in my current role as Consultancy Director. At Objectivity, I’ve met some exceptionally talented people that share similar views and ambitions to my own. I realise now that building great software starts by building great teams. I spend my spare time learning how little I know about my passion for photography. And when the weather doesn’t permit, you’ll find me rolling back the years writing code on various platforms and updating my blog.

See all Matthew's posts

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