• Colin Hayhurst

Aligning your business and AI strategy

Updated: Jul 31, 2019



Artificial intelligence can have a profound and positive impact on your business, but only if there is a company commitment to developing and exploiting it as part of your business strategy. In this post, I make the case for leaders moving past introducing AI for its own sake, to organising a plan around business problems and goals. It follows the previous post, in which all of the steps to becoming an intelligent, “AI-first” business were outlined.


Eventually, AI is going to impact. all areas of your business. How it will affect you depends upon the nature of your business and the sector you are in; particularly when it comes to the relevance of AI to your value proposition. On the other hand, there are aspects of AI adoption that will be common to many businesses, notably those around increasing efficiency and effectiveness; of operations, employees and customer experiences (e.g. chatbots, product recommendations). With potential effects on the top and bottom line, AI strategy is self-evidently a matter for CEOs and Managing Directors.


As a business leader, it’s worthwhile investing some time to get more familiar with AI; beyond what you are exposed to in the general press and social media. Learning about the realities of AI, rather than the hype, is relatively easy with a little bit of effort; there is a wealth of quality content you can dip into including podcasts, articles and videos. You can even dive deeper with fantastic online courses; though that might be something you support and encourage your specialists to do.


You don’t need to worry too much about understanding how machine learning works in detail; instead, think about what it might do for you. As an analogy, consider a car. Do you need to know how it’s engine works? Probably not; although you might be interested. What you will care about is how far and quickly it gets you somewhere, how safely, and at what cost. Machine learning is similar; you do not need to personally learn about the mathematics of machine learning to make good use of it.


Don’t think of AI as being about cost cutting


Companies that view intelligent machines merely as cost-cutting tools are likely to push them into the wrong places. AI can reduce the repetitive, dull parts of some jobs, but this doesn’t always mean you’ll require less staff. In fact, as companies increasingly compete using AI and augment it into their workflow, you may need more highly trained employees to work on the more creative, less routine aspects of your business.


Of course, AI has the potential to increase automation and reduce labour costs; a fact which leads to much of the scaremongering around the impact of AI on society and a hypothecated outcome of increased unemployment. In my opinion, and in most cases, AI will have the benefit of augmenting and assisting human performance rather than replacing it. However, that’s a debate for somewhere else. Whatever your views as a business leader, you have no choice but to examine how AI might help you to reduce costs.


In the medium term, we should expect the majority of savvy businesses, to be using AI for operational matters such as recruitment (e.g. bias correction), accounting (e.g. bank account analytics) and customer interactions (e.g. intelligent chatbots). AI-powered web services like this are emerging rapidly; intelligent businesses will gradually and increasingly adopt them into their operations.


How can AI be used to expand your business?


Where AI has the most potential to impact you positively, is in expanding your business and market share. However, compared with operations, you will need more creativity to implement AI which increases your revenue.


Off-the-shelf AI solutions for increasing revenue are less common than those for the operational side of the business. An exception is AI-powered sales tools which are being integrated into CRM systems. However, all of these off-the-shelf tools are also available to your competitors.


Here are some generic questions to help you think about expanding your business:

  • How might new AI underpin an expanded portfolio of products/services?

  • Could AI-powered tools enable you to charge more for products/services?

  • With AI could you differentiate yourself from competitors?

  • Can you leverage AI technology to enter new market sectors?

Bespoke AI is where the most important gains and differentiation can be made; building machine learning models that are about your business, it’s products/services, and your specific customer offer. It requires you to capture the right data, and use it creatively, rather than simply using or procuring AI-based tools.


The specific approach you take will be very dependent on the nature of your particular business. Nevertheless, it’s always useful to consider how AI might help you build upon the strengths that you already have. In other words, think about how you might exploit AI in your value proposition.


In later posts, we will focus on the detailed steps you need to consider, and take, as you integrate AI into your value proposition. We will specifically address the development of machine learning models which will result in the growth of your revenues. In other words, the steps needed for developing a machine learning strategy.


Ask yourself if you are ready


Before examining these steps it’s worthwhile considering whether your business is ready for the changes required. Here are some questions you might ask:

  • Do you have an appetite for risk and the agility needed to continuously test and evolve machine learning models?

  • Do you have the leadership and talent needed to support a long-term AI strategy, with roles and responsibilities to ensure accountability and successful delivery?

  • Do you have people to implement this and do they have the skills that will be needed?

  • Do you have staff that can effectively engage with, if needed, external providers?

  • And finally, do you feel familiar enough with AI to direct and manage your people and suppliers?

Last but not least, you need to consider the crucial aspect of data; that will be the focus of my next post.


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