Finding success in an automated world

Tackling AI head-on

Looking at internal processes and the way their organisations operate is one way for businesses to make improvements. However, many remain in the dark about where the roadblocks are in their operations, and how to find them. They often don’t know where to start in terms of which of their business processes are ready for automation, if their processes are too complex for automation, and how to monitor bots after they have been deployed. This is a common theme amongst many enterprises, and more guidance is needed if they’re to use AI to see legitimate results and remain competitive.

Another challenge that businesses face is changing the perception of automation within their organisations. A narrative has emerged around the disruptive nature of AI, with many fearing that jobs are at risk of being replaced by bots that are more skilled, and don’t tire as easily as humans. In reality, AI will create as many jobs as it will replace, according to a new PwC report. Some sectors will naturally see more displacement than others – such as transport and manufacturing – with time-consuming, repetitive, and menial tasks being carried out by machines in future. This will free up human brains to focus on more complex tasks, enabling people to concentrate on strategy, creative innovation and problem solving; which in turn, will help create new roles that don’t exist yet.

Knowing where to start

For those businesses that are ready to deploy AI, it’s important to remember that every successful automation initiative starts with a solid analytics foundation. The ‘magic’ of AI is built on pattern recognition and machine learning, which requires data to learn from. Common concerns for businesses are that they don’t have data that’s ready for AI, they aren’t collecting the right data, and/or they’re collecting it from too many separate sources. But technology has evolved to a point where algorithms are powerful enough to help enterprises use the very data they already have stored within their own systems.

One such technology is process mining, a new category of big data analytics that helps businesses get a clear view of all the activity that’s currently happening within their organisation. It uses the digital traces left behind by every IT-driven operation to reconstruct the as-is scenario and provide complete transparency into how business processes are operating in real life.

Using this insight, organisations can easily identify which of their processes are ready for automation, and whether these adjustments are justifiable with ROI. Getting a complete picture of business processes is critical to helping companies develop a more targeted approach to automation, and process mining can help here. Combined with machine learning, the technology becomes a powerful tool for businesses, by providing prescriptive recommendations for process improvement, and alerting users to previously undiscovered opportunities for greater efficiency.

It is no surprise that businesses and world leaders alike are starting to sit up and take notice of AI and the potential impact it could have. The benefits are set to be enormous, with the promise of new jobs and a significant boost to the economy, in turn, enabling businesses to remain competitive on the global stage.

Of course, the power of AI stems from the capability to understand a business’ challenges more completely and to make changes as a result. It is unwise to dive headfirst into an automation initiative without having an objective, so any organisation considering rolling out AI must first identify its intended purpose. If enterprises are unprepared or unwilling to make changes based on the potential that AI can unlock, then the whole initiative is wasted.