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  1. Nathaniel Palmer
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  3. Thursday, 13 June 2019
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Just a few years ago, we embarked on the ambitious redefining What is BPM?

Today we have reached another crossroads in the market for BPM and Process Automation. At our recent bpmNEXT event in Santa Barbara, we had many meaningful discussions about this, and specifically about the arrival of “Intelligent Automation” as a definitive market and software category. It has arrived and is now truly a thing.

Yet we (both as a conference delegation and the broader community in subsequent conversations) are split what it means. Recently I wrote an article about this, yet there is more to the definition, which is still evolving. Just as we did with the definition, having a collective voice and common understanding of Intelligent Automation will be invaluable to sustaining its current momentum, and ultimately necessary for it stick.

Some questions which need answers:

  • What is the differentiation you see/promote for that which truly separates "Intelligent Automation" from traditional workflow automation or BPM?
  • How do/should we as a community drive a common understanding/definition of Intelligent Automation?
  • How important is the analyst world and similar channels to driving collective voice and common understanding of "Intelligent Automation"?
  • How should "Intelligent Automation" and "BPM" be juxtaposed?
Accepted Answer Pending Moderation
What is the differentiation you see/promote for that which truly separates "Intelligent Automation" from traditional workflow automation or BPM?

When it comes to coining terms that make distinctions in this space, we've been down the "intelligent" path before. Advanced BPM/DPA platforms might reasonably be called "intelligent" even if they lack some of the features discussed in Nathaniel's article (which I very much enjoyed). In this case, though, the "intelligent" designation seems to have arisen from the advent of machine learning capabilities within those platforms. Fair enough, although "predictive" or "self-improving" or even "learning" might be better at making this particular distinction.

How do/should we as a community drive a common understanding/definition of Intelligent Automation?

First and foremost, let us distinguish Predictive Automation (see? sounds good, right? I also like "Autodidactic Automation") from RPA. RPA is not "intelligent", and it doesn't "learn" in any meaningful sense (despite the claims on every website of every RPA vendor on Earth). Sure, BPM applications assign tasks, and RPA agents (I refuse to call those things "bots";) can be useful as doers of tasks. The whole reason for RPA to perform such tasks instead of humans is that the intelligence that humans (presumably) bring to those tasks is simply not required.

Then, let's exclude all those platforms claiming to have machine learning that in reality only have connectors to other applications/services that do the actual learning. A connector doesn't make you intelligent; it merely allows you to chat with somebody who is.

When we talk about Intelligent Automation, therefore, let's then limit the discussion to platforms that offer native, fully integrated, no-code machine learning functionality.

How important is the analyst world and similar channels to driving collective voice and common understanding of "Intelligent Automation"?

Frankly, the analysts will ultimately control the nomenclature — particularly as far as customers are concerned.

How should "Intelligent Automation" and "BPM" be juxtaposed?

In Nathaniel's article, he suggests that BPM is a major part — but not all — of what comprises Intelligent Automation. He also notes that RPA can be (but is not required to be) a part of an Intelligent Automation strategy (though RPA per se is not intelligent). Certainly, machine learning is a critical component.

One is tempted to say that Intelligent Automation = BPM + ML + ... but, then again, "BPM" has never quite been fully defined. We're forever doomed to be muddling around with nomenclature anyway.
Scott
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