By | Bernard Marr
Some of the biggest challenges for organizations looking to roll out digitally transformative initiatives are around platforms and skills. For enterprise workloads, Artificial intelligence (AI), Internet of Things, and other data-driven technologies generally require numerous technologies and platforms to be deployed simultaneously, and you’ll often find you’ll need people with a particular skillset – one that’s in high demand – to get it done.
This is changing – due to a process that’s often referred to as the “democratization of data,” there’s been a strong trend towards creating simplified processes, as well as widening access to these processes among employees who may never have worked with data before, let alone studied for a Ph.D. in data science. It’s a widely held belief – bourn out by some serious research by the likes of Gartner – that for AI to achieve its truly transformative potential, it has to be possible for anyone to use it, and not just a highly educated elite.
One way that companies are making this a reality is by deploying what is known as analytics process automation (APA). At its core, this is all about bringing together advanced analytic capabilities, automation of business processes, and workforce upskilling under one umbrella. These are three essential areas that businesses have to tackle if they want to make the most of the opportunities of digital transformation. Therefore, managing them together in a synchronized and integrated way on a unified platform makes a lot of sense.
