How does AI fit with automation?


By Neil Kinson, Chief of Staff, Redwood Software

AI, most regularly associated with Artificial Intelligence, has become a bit of a stand-in term for what is really a broad selection of technologies that encompasses machine learning, predictive analytics, natural language processing, object recognition and more. To the uninitiated, it can be a bit confusing, and so everything ends up under the umbrella term ‘AI’.

It’s a bit like that family member who refers to all tablets as an ‘iPad’, regardless of the actual device they’re holding or referring to. It’s the set of capabilities that’s important to the user, not the device itself.

As a result of this bunching together of terms, the exact capabilities of ‘AI’ and how it fits with existing automation solutions hasn’t been clear for many IT and business professionals. And that in itself has led to a period of exploration and, in many cases, disappointment at current capabilities and use cases, versus the myths perpetuated by vendors jumping on the bandwagon.

But hype only lasts so long and what takes its place is a calm assessment of efficacy and return on investment. And it’s there that current thoughts around ‘AI’ tend to go astray.  

At Redwood, everything we do is focused around delivering measurable value, so we prefer to think of the overarching collection of ‘AI’ technologies as Augmented Intelligence, rather than Artificial Intelligence.

What this accumulated Augmented Intelligence has meant for automation so far is the rise of ‘self-service’ applications and solutions, for both customer-facing and back-office operations, and that trend will continue through technologies that are themselves an amalgam of techniques.

Take predictive analytics as an example. The process of combining and assessing data in various ways to determine potential future patterns might well be called predictive analytics for ease, but it’s really a combination of data mining, statistical analysis, machine learning, and in some cases Artificial Intelligence, to make predictions about the future.

It’s there – in augmenting existing technological capabilities in a variety of ways to improve operations – that the future of AI and automation are intertwined, it’s just that the ‘A’ stands for augmented, not artificial.

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