Your Artificial Intelligence Business Case

"What are we doing with AI?" said the CEO

Artifical (AI) Intelligence, despite the hype, has the power to help you over achieve on some of your objectives and allow the business overall to see real value. What is the Business case for Artificial Intelligence?

Business case for Artificial Intelligence

Every business is different. You will have different problems and different objectives.Here we look at the business case for Artificial Intelligence.

Artifical (AI) Intelligence, despite the hype, has the power to help you over achieve on some of your objectives and allow the business overall to see real value.

Undoubtedly, there are more and more business leaders looking at what AI can offer them. Often these aren’t fully formed ideas or projects but more leaders are hearing that similar businesses are doing well, or particular projects are showing beneficial signs.

To be successful you will need to think about how robust you can make the business case. Here are some pointers to help you.

The key reason you’re going to want to go ahead is that there are significant gains to be had. You can speak to us directly about how FTSE 100 b2b and b2c businesses are tackling key customer problems using our methodologies. Here’s our calendar.

4 things to cover in your Business case for Artificial Intelligence

This framework is useful to look at two different types of project.

The first is how do you start to modernise and optimise a current objective or process that you know isn’t delivering the value that it should, or has become too burdensome on resource.

The second, is how could you start to put into practise some of the innovation ideas that you have previously been less inclined to fight for, due to clear barriers. You may have already seen a great opportunity but been unable to look to take advantage.

Each of these points should help you see through the issue with more clarity and help make the case.

1. Tackle a Problem of Value

You probably already know this, or you may have responsibility across 3 or 4 key areas that you want to investigate. See the table adjacent that might help. Your domain expertise, and that of your team, will be critical to determining this.

You may be looking at recommendations and product up/cross sell. It may be media spend that needs to be optimised, or how to better understand how AI can help with marketing on mobile.

AI will help you take a great deal of friction out of your customer journeys.

It may be that you’ve already looked at some of these issues but have struggles to find a sustainable solution. It may have always been a point of ‘it worked for a while, but we couldn’t keep it up’, or someone left the business who did it and we didn’t really know how they did it. Potentially those solutions can now be done with AI. 

By being able to show how valuable is 

2. Do your Due Diligence

Data has to be available. That kind of needs to be said. We’ve found that there are two sides to due diligence, is there a great enough business impact – will you answer the CEO’s “So what?” question, and is it feasible to do it with AI.

Does the data exist to solve the problem? There may be some functional silos that will need to be overcome. You may need to focus on your own knitting to begin with, perhaps augmented with external data.

It’s a good idea to plot each use case against Impact and Feasibility. See the illustrative chart to the right. This will help you prioritise but can also help breakdown some of those silo issues. This is illustrative and won’t be representative of your business. However, what you are looking to do is to evaluate the Impact and Feasibility of your projects. We can help you do this. There may also be other dependencies, like getting a 360 degree view of the customer, that may not generate a high impact by itself, but is necessary for some other areas to work.

You may discount some areas because although they would be something that can help some activity, getting other areas optimised first will free up the bandwidth or the budget to that later.

impact feasibility

3. How would implement and sustain it?

Moving from test and pilot to production can be daunting. You will need a plan of a plan. However, in our experience this will change as you and your team become more aware of what the changes are that need to be managed. Many of us have grown up in a work environment where we are constantly trying to optimise a workflow process. AI is about a decisioning process. Cross team collaboration – a wider church? It may be that this is the beginning of something. Having you as a champion and then 2 or 3 really keen colleagues that can help. Training is absolutely key. There is a mindset change that will probably need to happen or accelerate.

4. Senior buy in

As ever. You will be best placed to answer this. This may come because AI is already on the radar and the CEO wants to know what you should be doing. It may be that you’ve already done some work together that cannot be progressed because of some limitations. It may be that actually there are issues that the board and all aware of that have felt unsurmountable. One of the first things that we advise to do is a senior leaders workshop on AI. This helps to clarify what AI can do for your business and how it can help to solve some cross-departmental issues.

You never know, when the numbers start building around some of the CRM improvements you have made by just reallocating some budget, optimising some processes and working with some fresh, keen talent, things might just get a bit easier.

Inevitable Obstacles

It won’t be plain sailing. Here are five things that you are almost guaranteed to come up against.

  • Clear AI strategy missing – this is where you need to tie it in to business objectives and business strategy.
  • Lack talent with AI skills – that’s one of the reasons we can help. We’re a key partner.
  • Functional silos constrain end-to-end AI solutions – always a tricky one, but bear in mind that partnerships between departments and shared risk makes for a stronger solution.
  • Lack of leadership ownership and commitment – always a problem, but this is why the right projects that will show value are important, do the due diligence, what’s feasible, what has impact?
  • Technological infrastructure doesn’t support AI – again you may not have ‘an anything’s possible’ view of the world. But infrastructure doesn’t need to be a hindrance.
 If you were looking to start a project, or had some data you wanted to use to ‘see’ if AI could help you, Databuilder could be an option. This is a No-code tool that allows you to safely and securely use 1st and 3rd party data to get outputs that you need. It uses AI under the hood. 

You might feel that some consultancy on getting started may be worthwhile, have a look here. It is also possible to schedule time with us. 



You might feel that the odds are stacked against you. Even reading this you’ve got more obstacles than pointers! Do not be disheartened. You will probably need some half relevant references to deplete even your own trepidation. You will also want to make sure that any numbers you put in from of people are robust. It makes sense therefore to be able to speak to people who are already on the journey. Speak to people who are on a mission to make each step easier for you.

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