The Top Seven Uses of Cognitive AI Today
by Jim Sinur
The world is speeding up and accelerating even as you read this article. Big Data keeps piling up; new IoT devices are multiplying exponentially; new patterns of threats and opportunities are emerging by the second; decisions are lagging optimal conclusions; the goals keep changing; governance complexity is growing. Your actions had better be on the mark. Your processes can't hang with this pace, and you can't collaborate fast enough to get the brain power on the job. It's worse than the game called "Whack-A-Mole" where the mole heads pop up faster than you can hit them accurately.
How will you and your organization keep up? Cognitive AI will help organizations in at least seven areas of concern and can deal with the endless combinations and permutations facing us. If you want to master Digital, you need Cognitive AI.
1. Grocking Big Data
The number of data sources, even without the IoT generating more, is unknown. The depth of the data lakes is another unknown. Combine these unknowns with unstructured data, text, voice, images, and video and now you are out-flanked by the size and scope of data. Cognitive AI, with or without machine learning, can sort through this barrage of data to find patterns of interest and triggers for decisions and actions.
2. Managing the IoT Population Explosion
It's clear that the number of devices is exploding and that the signals they emit is creating an even bigger Big Data problem, but managing these devices without rigid or flexible chips will be an even greater challenge. These devices will be deciding and acting alone or in concert with other devices on the edge, driving toward changeable goals while not violating constraint boundaries. This means that these devices need to be smart so we can pass control to the edge to create smart and dynamic swarming agents that can be guided by AI.
3. Leveraging Opportunities & Risk
Signals and patterns need to be quickly sifted and aggregated into patterns of interests for managers to decide and take action to optimize an organization's opportunities or to protect organizations from emerging risks. This sifting, aggregating, and learning can be assisted and super charged by cognitive AI. For wise organizations that have anticipated key triggers and patterns and have planned responses on the shelf, cognitive AI can quickly be used to verify appropriate responses.
4. Divining Great Decisions
Today great decisions can be made by having the right set of algorithms, applied in the proper sequence to come up with optimal decisions. Analytics or poly-analytics can be further leverage by using cognitive assists to decide on new combinations and sequences, replacing the human trial-and-error application of filters and algorithms. Even predictive algorithms can be enhanced by machine learning and cognitive AI.
5. Delivering on Shifting Goals
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 role in setting these goals and constraints.
6. Complying with Growing Governance
The problem with governance standards is that they are standalone in nature. Organizations are usually barraged with multiple governance standards that have to be mixed with the desired outcomes of the organizations represented in goals and constraints. Cognitive AI can be leveraged in sorting out the complexities of overlapping governance standards while they change in flight.
7. Keeping Actions on Point
All of the above contribute to the right action, taken at the right time, but also all constituent desires need to be put into the mix. Cognitive AI can represent the customer, employee, partner, and vendor goals that need to be considered. This gives a dimension of satisfaction that can be baked in, just in time to keep the organization-desired outcomes in dynamic balance with constituent-desired outcomes.
There is no way we humans can keep up without a little help from our cognitive friends. It will start out with digital assistants, then super-charging the competence of every person and program through the use of COGs (cognitive services), and finally moving control to the edge through smart agile agents that may include robotics. Don't be late to the digital party that's coming your way.
Jim Sinur is an independent 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 (iBPMS), process collaboration for knowledge workers, process intelligence/optimization, business policy/rule management (BRMS), and leveraging business applications in processes.
When with Gartner, Jim 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 vertical industry experience on the investment and operational sides of the insurance and financial services. Jim has long been active in the rules, data, and computing communities, helping shape direction based on practical experience.