It’s hard to overstate how big of an impact AI will have on society over the next 20 years. ~ Jeff Bezos (1)

The world of computing has never been more complex than it is today. The rapid rise of the Internet and digital transformation has disrupted many aspects of how we get work done. Despite this historic pace of change, we are still in the infancy of this transformation. Business leaders face a mountain of uncertainty as they navigate the impact of the digitization of work practices and begin to modify strategies to leverage its advantages. A key area of the digital transformation includes artificial intelligence (AI) and its underlying technology of machine learning. AI has captured our imagination because of its promise to automate work processes and improve efficiencies. Although recent advances in AI have primarily been focused on speech recognition, image recognition, and game playing, we’ve all heard about how AI will eventually affect jobs, especially those that include rote and/or manual tasks. In fact, prominent machine learning expert, Andrew Ng, states that “If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.” (2) Business has begun to digitize everything it can, and the result is massive amounts of data. The data is analyzed and used to train neural networks so they can learn faster and perform more detailed tasks.

The idea that AI will potentially eliminate millions of jobs is causing anxiety about the coming “automation apocalypse” that threatens to unleash a massive wave of unemployment. A survey by the Pew Research Center found that 72% of Americans are worried about a future in which workplace automation replaces human workers. (3) As AI advances, experts are certain that it will fuel a diverse array of devices and services. So many, in fact, that the lines between machines and humans will blur to the point of it being difficult for us to recognize who or what is behind them. For now, the primary economic value created by AI is its ability to learn simple input/output operations and act on them. For example, AI is capable of identifying specific people or objects within a image. Apple’s new iPhone X is an example of this type of AI. The iPhone X’s face detection AI unlocks the phone if it determines the face is yours. Another common example is AI used to scan online loan applications to determine if the applicant will repay the loan, providing instant decisions. AI’s most prevalent usage today, however, is in online display advertising. Ads on Google, Facebook, Twitter, and other social media and news sites customize themselves to your interests to encourage clicks.

With the knowledge that AI will infuse itself into the workplace, what do Learning Leaders need to do to prepare the modern worker? It’s a natural human instinct to respond with fear and anxiety. Researchers are studying the effects of automation on jobs, and a 2016 study by the World Economic Forum surveyed 15 major economies that consist of ⅔ of the global workforce — almost 2 billion workers — and concluded that the rise of AI will eliminate a net 5.1 million jobs by 2020. (4) This apocalyptic view is countered with research that shows AI is not as advanced as we think, and its ability to eliminate massive numbers of jobs may not occur as fast as we anticipate. (5) AI requires massive amounts of data and computational power. Humans learn abstract relationships much quicker than a machine, and can process relationships and make correlations with intuition very quickly. It takes a large dataset for a computer to do this. Humans and robots collaborating during work is most likely the outcome we will see as AI leverages data to learn and humans ensure the right data is gathered and analyzed.

It’s certain that technology will replace many jobs, which is what we should want. Humans can then focus on our strengths, and we can strike a balance between intelligent machines and people. Jobs that are better suited will shift to machines, especially in manufacturing and data processing. Jobs better suited to people, such as engineering, design, and management, will expand. In addition, we will invent entirely new occupations in response to the demands of automation. For L&D, this is an opportunity to identify and build the digital capabilities the modern workforce requires. Caroline Brant, an AI expert and L&D advisor for Zoomi, Inc., a company focused on AI technology for learning, has seen a spike in learning analytics positions across many companies. Brant says that, “several organizations now see the value in adding learning experts on their workforce analytics teams, or data scientists on their learning teams to evaluate the true value of learning initiatives, investigate how predictive analytics correlate to workforce performance, and help determine how to derive business value from performance-related data.” As business strategies shift to increase productivity and improve quality through automation, people will still be needed to run the business and execute the strategy. As a result, a dynamic and transformative learning strategy is a key differentiator. Technologies such as virtual reality (VR) and augmented reality (AR) will help safely train humans to operate and maintain complex software and machinery. Mobile technologies will provide workers information at their moment of need. Action-based learning will help develop new behaviors and mindsets for leaders and managers to continually improve their teams abilities to execute. Additionally, we will train robots how to perform dangerous and/or rigorous tasks. The promise of computational power, ubiquitous connectivity, and large datasets provide richer tools to develop adaptable learning experiences for both humans and intelligent machinery.

Next, L&D needs to foster deeper innovation in learning methods and leverage the right technology to facilitate learning experiences that accelerate skill transitions. These learning methods need to focus on critical thinking, problem solving, adaptability, emotional intelligence, and creativity. These are the human skills required to successfully navigate the future workplace. This connects L&D strategically to a dynamic workforce that can quickly learn and connect disparate concepts and ideas to create business value. The future viability of many companies will not rest on how many machines they implement or how much automation in which they invest. Instead, their advantage will come from a workforce that can shift to changing demands, solve new problems, and continually create value. For the rest of time, workers at all levels will interact with technology to perform their jobs. All workers are now knowledge workers.

AI will have some level of impact on every job, which means that L&D must place emphasis on how to train workers to be more flexible. We must develop managers and leaders so that they gain a broader understanding of how intelligent machinery and humans work together. People will also need to understand how AI makes decisions and be able to intervene when its decisions are flawed, biased, or dangerous. This will potentially create an entirely new specialty in many areas of business as AI becomes more central to decision-making and infused into areas such as filtering job applications, assisting with performance evaluations and feedback, and assessing on-the-job performance against expected metrics. Consider this new job description for L&D:

Job: Cognitive Capability Lead for Learning

The Cognitive Capability Lead for Learning (CCLL) guides the implementation of cognitive learning solutions to address performance-based business process improvement.


  • Centrally coordinates all technical activities in the design and development of cognitive learning solutions and is a main point-of-contact between IT, learning, and the lines of business
  • Leads content and technology configuration and integration streams for the business and IT
  • Creates and communicates the business case for cognitive learning solutions
  • Prepares training materials for the cognitive learning solutions and monitors and directs the continuous machine learning systems

Skills Required

  • Advanced understanding of human and machine learning
  • Experience with content development
  • Advanced degree in computer science
  • Familiarity with cognitive technologies

Automation is on a march that will result in transition, not devastation. Yes, there will be jobs that are eliminated, such as those that involve rote tasks. But that’s been the case for decades. Part of the progress we have made has been to move away from rote, dangerous activities towards safer and higher value work for humans. As the past has shown us, occupations change and new ones are created. Humans have a tremendous propensity for growth, which fuels new industries and creates new jobs. As the study from McKinsey Global Institute suggests, global full employment worldwide is predicted with continued innovation and economic growth.

Does AI take away jobs or does it create new areas of work that require new skills? The answer is not easy, and it will rely on humans determining what AI really is and what its limitations will or should be. Humans still are able to shape the future we desire through the decisions we make today. We should remember that technology is just a tool. People are behind the decisions for how it is used.


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