Insight

Make the Artificial Real: AI, automation and you

Google ‘artificial intelligence’ and you get almost 97 million results. Is it any wonder many organisations and businesses are so overwhelmed by the possibilities of AI and automation they don't know where to start? Or, like some clients we've been speaking to, they're implementing AI but aren't sure whether it's delivering as it should or what to do next.

AI and automation are more straightforward than all the hype would suggest. Yes they're talked about a lot and in dramatic and sensational terms – and the technology will fundamentally change all our lives. But the scale of change and number of people talking about all-things AI needn't cause organisations to fret.

In the months to come, we'll be taking you on a journey to help you sort through the noise and complexity and make smart, strategic decisions for how AI and automation can help your organisation.

Today, we go back to basics with a primer on the key aspects of what AI and automation can achieve and how best to achieve these outputs.

Cut through the confusion

There are three broad areas that AI and automation can help with:

Leveraging the power of data

Machine learning loves data, and most organisations have troves of it. Establishing a machine learning capability is an investment in the long term, but can also provide quick wins. For example, using predictive algorithms, we helped one of our public transportation clients improve their ability to maintain trams to avoid costly repairs.

Interacting better with customers or co-workers

Banks and local governments are experimenting with chatbots to engage with customers and citizens. Using the right technology can solve easier requests faster, freeing up humans to focus on more complex cases. The same technology can be used internally or in a business-to-business context.

Automating support processes

We've helped clients understand how to get started with broad robotic process automation (RPA) transformations, taking repetitive processes away from employees, and freeing them to do more interesting and value adding work. Another great example is how predictive technologies are reinventing the HR process by finding better candidates with less effort.

Think big, start small, scale fast

This is our tried and tested approach and it applies to both organisations just starting out and those already well along in their AI journey. Remember, the further along you are, the more important it becomes to take time to reassess your performance.

The first step in 'thinking big, starting small and scaling fast' is to establish a general direction for your organisation. It's best to keep this as simple as possible. At this point, nothing needs to be set in stone. But you do need somewhere to start. When you get into the next phases, you'll be learning more and more. That means you'll likely want to revisit your goals when you realise the breadth of opportunity that AI and automation open up.

It could be as simple as adopting an 'AI and automation first strategy': for every business problem you encounter, you look at how AI and automation can fix it. Your business might require a vision that is more detailed, supported by a strategy paper and business case. Both approaches are equally valid depending on the organisation, but the key is to progress through this phase quickly and begin using the technology.

Starting small means finding business problems or opportunities like the ones we've described above and scanning the market for AI and automation solutions. Chances are something exists already. Test the technology in a controlled way. It could be open source technology you can develop internally or off-the-shelf licensed software. When working with the public transport company mentioned above, we started by simply focusing on the brakes and were able to build a model to identify patterns in different types of data that occur prior to a brake incident. It was a great success and the organisation could see they'd save hundreds of thousands of euros by preventing incidents rather than having to make emergency repairs. Starting small like this allowed them to understand the value in the technology. They've now expanded the process for other types of maintenance and are exploring where else in the business they can use AI.

Getting ready to expand does take preparation – but the sooner you can do that, the sooner you see the benefit, both financially and in terms of learning. We helped a bank apply an approach used to improve mortgage sales to more than 25 different products. You'll need to commit resources and management effort to drive scaling efforts quickly and in an agile fashion. That means making decisions quickly, removing obstacles to progress and adapting to change. The good news is that this isn't too different from other agile projects.

What are you waiting for?

Adopting or expanding your use of AI and automation technology as soon as possible will maximise your chances of success. We're looking forward to seeing more and more organisations exploring the possibilities.

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