Philip White: Why the right decisions are vital on the Artificial Intelligence journey

Improved agility, better customer experience, reduced costs. These are the top three benefits fuelling organisations’ sustained interest in Artificial Intelligence (AI) and Machine Learning (ML).

Scientists have long been fascinated by artificial intelligence. This The Cybernetic Tortoise was invented by neurologist William Grey Walter and sprang from the growing interest amongst researchers such as Alan Turing in artificial intelligence in the 1950s. Photo: Geoff Caddick/PA Wire

And with a recent report from Capgemini showing that nearly half of UK office workers are optimistic about the impact automation technologies will have on the workplace of the future, it’s no surprise these benefits are already starting to build its reputation.

However, AI and ML are the latest IT buzzwords that can easily be dismissed for fear of being introduced for the sake of it, or with the wrong intention.

Sign up to our Business newsletter

Sign up to our Business newsletter

That’s why it’s important to understand more about this technology and how to implement it quickly and cost-effectively, so you can put in the foundations for technology that will soon be ubiquitous, improve your operations and help gain a competitive advantage.

When applied to the right business challenges, AI can demonstrate a great return on investment. Many firms have already integrated AI and ML within their business processes, such as automated vehicle checks that enable staff to tackle other priorities, identifying data anomalies in transactional businesses and predicting important component failures.

However, investing in this technology needs to have a sound business case and rationale. By being really clear about the problem you want to fix, understanding the value to the business and setting clear measures, you’ll be able to demonstrate your return on investment.

AI development exists on a spectrum with inventors at one end and installers at the other, raising the question of how businesses should adopt AI. Depending on your business project, you may find that the middle position is the sweet spot where you get the best of both worlds.

Inventors create new models and techniques which require in-house skills and significant time and investment. You’ll hold the intellectual property rights to what you’ve created. However, it’s unlikely that you’ll need to invest this much time and money unless you’re a futuristic business that isn’t served by existing AI software. Tesla is a great example of an inventor, as it builds deep learning algorithms from the ground up.

Innovators develop existing technology frameworks with embedded AI to improve processes. This route involves taking off-the-shelf models and customising them to fit your business requirements.

Lastly, installers use and tweak pre-existing technology. With pre-packaged software solutions often good enough, this route can get you to where you want to go quickly and easily. However, it’s unlikely to give you a competitive advantage as your rivals are able to buy and install exactly the same piece of software. Mastercard has gone down this route through its implementation of chatbot to enable customers to easily check on account transactions.

Whichever route you pick, you’ll need to ensure you operationalise your AI effectively – managing it on an ongoing basis and anticipating its evolution as your business needs change. But before you take your first step on your AI journey it’s vital to consider carefully whether AI is the right tool to solve the problem. Traditional tools can often be perfectly adequate for what’s required so you might want to consult with a trusted development team to understand whether AI is indeed the right option to add value to your business.

If AI is the right option, it must be adopted at a pace that suits your needs. You should identify a few potential projects or challenges and review how AI could provide a solution.

If your organisation is sitting on data you are well positioned to leverage AI by introducing machine learning into your processes and systems. Review where your data is coming from now and where it will come from in the future. Clarify how much work is going to be required to clean and transform the data.

Businesses must understand that the model is only as good as the data it is provided with, so during development, testing and launch, make sure you continuously review the process for validating your data.

Developing a plan for advancing your models is vital. This could be due to higher volumes of data you need to store, enabling you to provide better insights, or having to react to changes in your underlying business environment.

There’s little doubt that AI and ML will become an indispensable part of the way we work and live. Before taking the plunge, businesses must ensure they are investing for the right reasons, and in the right technology, to enable them to harness the power of this technology and stay ahead of the pack.

Philip White is the managing director of Audacia