Artificial intelligence and its subset, machine learning, have undoubtedly been the buzzwords of 2019, especially within the business and technology worlds. With hundreds of articles making grandiose claims regarding how AI will transform businesses, many organizations who have already deployed AI within their businesses are struggling to see results, often deeming the projects as failures.

Why is this? More often than not, it’s because the business decided on where to implement AI, instead of discovering where it would have the most beneficial impact within the organization.

Just because a given process is the most painful, labour-intensive or inaccurate, it doesn’t mean that it is the most suitable process in your organization for the introduction of AI.

So, how do you discover where the most profitable and practical use case for AI within your business is? Our Data Insights team believes there are three stages to successfully discovering where AI is most beneficial within your business.

Step 1: Data Ethics

Data ethics is an important starting point for any data-orientated project and has been a popular discussion point in 2019, especially when it comes to AI.

But what does data ethics entail? Here are some of the questions our Data Insights team pose during our projects:

  How will you ensure that AI treats your customers and employees appropriately and that decision-making is transparent?

   How will you identify and mitigate risks to safety, happiness or profit?
   Do you have the right permissions to use personal data for automated decision making?

  Do you have the skills and deep understanding of your internal data processes to ensure your AI project will be built on ‘privacy by design’?

Step 2: Data Maturity

Before searching for where to deploy AI, you need to be sure that your business is even capable of taking advantage of it. This is a multi-faceted requirement, ranging from your business’ technology infrastructure and skills to your data discipline and even your board-level and wider culture. Only once all of these pre-requisites are met can you start investigating where AI can be deployed.

   Is your strategy data-led?

  Is your day-to-day operational execution data-led?

  Is your technical architecture suitable?

   How robust is your data governance? And importantly in terms of historic data-gathering, how robust has it been up until now?

Step Three: Discovering the right use case

Now that your data insights project will be ethical, appropriate and you can be sure that your business is prepared for both the introduction of the project, and to make best use of the outputs, you can start the search for the best place to implement it.

But how do you find it?

  Strategic Review

Apply your strategic objectives to each of your business functions to identify where the most urgent needs, shortfalls and challenges exist.

  Impact Assessment

Identify what benefits can be anticipated from tackling each of these, whether hard (cost reductions, revenue generation, compliance, etc) or soft (culture evolution, digital transformation, competitive advantage, etc)

  AI Relevance

Once you can see where the greatest benefits are to be gained, is AI the right technology for delivering them? AI is most impactful when it is given the freedom to be creative – you might find analytics or automation may be more appropriate.

  Data Audit

What relevant and useful data do you have available to you, whether proprietary or external?

To find out more about each of these questions in all three stages and how to answer them all – and others – download our guide to finding the right use case for AI in your business.