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Lying in wait is the thought that learning is a skill to be taught, not just to learn a subject, but rather to analyze the environment we live in and find the problems needing solutions.  This stretches the learning practice to make us better problem solvers and innovators, not just experts in a discipline.  With this comes a need to start training our newest generations in this lifelong learning experience and provide transition to the existing generations to “come up to speed”.

It is a closed loop process at its most basic roots; viewing, analyzing, changing, monitoring, and looping back to viewing, continually.  We must intersect technology, like AI, into our process to assist in creating a closed loop system that is changing and moving us and our businesses forward, lest it stagnate.


AI Enhanced Workplace Training

It is highly likely that the populace will need new environments for learning, with outcomes that are not geared to a degree or singular mastery of tasks, but rather reshaping what we need to know and how/where to apply that knowledge.

Current educational thinking is putting soft skill learning into courses in preparation for the work environment as organizations are recognizing that their senior and high potential employees may not possess the leadership skills needed to move the organization forward.  Skills to mentor teams, presentation and business case skills, communication in various media, interpersonal relationship and team building, and innovation/design thinking are examples of what senior executives as finding lacking in the workforce.

But as stated, the introduction of educational information will be enhanced when AI monitors processes and people and can make recommended changes to the environment to produce a more efficient or valuable outcome.  AI will be collecting information from individuals to help recognize the learning styles that produce results (Wang, 2018).  And AI will find a home in the recruitment of staff based on assessments and analysis to hire the most adaptable individuals to fit the new workplace. AI’s ability to amass information for the purpose of recognizing patterns and their potential for being successful or harmful provides organizations the ability to let training become self-directed so that organizations can rely that AI will monitor and assess the readiness of individuals, teams, and the workforce in general for change.

We are already seeing AI value in embedded processes in transactional systems that look to a human initiated action and compare it with data of previous human actions and their outcomes.  AI can help to make the actions support success or temper the decisions by presenting additional information to refine the knowledge supporting the action/decision. (Bennetts, 2018)

And with mobile apps combined with better voice recognition, workers can now access information that is highly pertinent to when and where they are needing “problem solving” education, be it on the “shop floor”, in the field, or even at home.  And with the myriad of remote collaboration suites available, bringing the team together through mobile and introducing the AI team member into the mix will result in faster problem resolutions. But the future value of AI and ML will be to propose new “problems” or scenarios that can be taken by humans as “things to think about” and measure the outcomes.  Those new scenarios will also be “crowd-sourced” to allow collaboration and innovation to be brought to the problem from all areas of the enterprise.  And amassing the solutions and outcomes of those problems to use as benchmarks for future problem solving again will be the domain of AI.


What our Future May Hold

  • Introduction of AI, ML, and Augmented/Virtual Reality (XR) will enhance the education process, being very adaptive, faster knowledge dissemination through visualization and more entertaining to future generation of learners. Walmart is using VR for training from on how to stock the produce section to handling the Black Friday crowds. (Thibodeau, 2018)
  • Voice technology will morph into being highly adaptive in recognizing different languages, dialects, and speech patterns. AI can access massive amounts of information to understand better what is being asked and can couple that with individual information gathered from the device to know who they are addressing.  As the speech recognition improves, it must also be accompanied by devices that can provide privacy to an individual speaking to and hearing the output of an AI assisted learning situation.  Unless this is mastered well, we will only raise the “noise level” of our surroundings and make this a less conducive method of communicating with AI.  But the “hands-free” nature of speaking to our devices is a very natural and comforting manner to introduce AI improvements to our lives.  We already see the usefulness of such devices as Amazon Echo or Google Home.  Many new extensions of these devices, coupled with the IOT capabilities allows us to talk to and gain insights from our devices, with AI sitting behind the scenes (Kanungo, 2018) (Sumser, 2018)
  • AI can benefit our current processes immensely in areas of data integrity. Over the many years, we have progressively converted our information from one platform and technology to newer platforms and technology that requires us to sometimes GUESS what the converted information really means.  As a result, our business intelligence is tainted with erroneous or useless data, not because the need for that information is useless, but the integrity of that information is highly suspect.  AI can help to reduce or even eliminate the problem as automation moves input of information into the hands of those MOST directly involved with the transaction.  It can ensure that the data is more reliable in comparing in the context it is entered, make or suggest corrections instantly, and create better analysis of interrelated information to make the enterprise data highly accurate (Sutter, 2018).
  • AI to be at the center of global communities generating ideas that are business, economic and life altering. The crowd-sourcing aspects of multiple sources of information being aggregated into thoughts and shared into the community to stimulate additional innovation put us on a scale well outside of what we envision just for the business uses of AI.  And these communities will more than likely exhibit cross thinking in such a way that newer thinking will be borne out of the AI process and broader problem solving with become inherent through cross-pollination.  And AI will be at the center of this, making us perhaps better humans.  It may leverage mankind to be more holistic in its approaches to solving global problems and provide a stronger approach to the longevity of the entire human race.