AI to Manage Agility

Jim   Sinur
Jim Sinur VP and Research Fellow, Aragon Research Read Author Bio || Read All Articles by Jim Sinur

If you watched last year's Superbowl, you saw an example of agility in action with the swarming, lighted drones creating backgrounds in the sky behind Lady Gaga.  By giving the drones goals of flying into the right position to participate in creating an image with the right color, images were created in the sky.  Not only were they wondrous as paintings in the sky, with each drone being a dynamic pixel in a dynamic piece of art, they were used for ads for sponsors.  Imagine if organizations would paint a customer experience dynamically or respond to a competitor dynamically or intercept a market trend?  It's going to take AI to do this, not a bunch of hand-/human-controlled responses or computer programming alone.

Dealing With Goals

As organizations move from fixed process and applications to more dynamic processes, they will change to be goal driven.  This means that all resources will swarm to the established goals and adjust when the goals are changed.  AI combined with analytics will help to initially noodle out what are the best goals.

Dealing With Constraints

Besides goals, these dynamic processes and applications need boundaries to stay helpful — and sometimes even legal.  This is particularly true when there are multiple constraints.  AI and analytics can be helpful in initially establishing these boundaries/constraints.

Dynamically Setting the Goals and Constraints

Add dynamism to the mix and now you have a new set of problems that AI is quite adept at today.  AI can learn from situations collected over time, select the right set of prediction algorithms, and project the potential outcomes.  All of this can be done within scenarios and policies that have been selected for in-force or alternative scenarios.

Net; Net

Goals not only conflict and compete, they are shifting.  As this shifting takes on a new speed of change, Cognitive AI can create the right balance for emerging situations.  As processes and swarming agents become more goal directed than flow directed, organizations can act on shifting goals that leverage constraints.  Cognitive AI can play a big role in setting these goals and constraints.

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Standard citation for this article:


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Jim Sinur , "AI to Manage Agility " Business Rules Journal Vol. 19, No. 1, (Jan. 2018)
URL: http://www.brcommunity.com/a2018/b939.html

About our Contributor:


Jim   Sinur
Jim Sinur VP and Research Fellow, Aragon Research

Jim Sinur is an independent consultant and thought leader in applying business process management (BPM) to innovative and intelligent business operations (IBO). His research and areas of personal experience focus on business process innovation, business modeling, business process management technology (BPMT), processes collaboration for knowledge workers, process intelligence/optimization, business policy/rule management (BRMS), and leveraging business applications in processes. Mr. Sinur was critical in creating the first Hype Cycle and Maturity Model, which have become a hallmark of Gartner analysis, along with the Magic Quadrant. He has been active in the rules, data and computing communities, helping shape direction based on practical experience. Mr. Sinur has vertical industry experience on the investment and operational sides of the insurance and financial services.

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