Automation is becoming more capable, reliable and less expensive to deploy. Autonomous and semi-autonomous systems are doing things that were science fiction a few generations ago. These include: intricate surgeries, flying airplanes, driving cars, cooking hamburgers, cleaning homes and running industrial operations. Smart systems analyze economic performance, stock markets, legal strategies and the data at the heart of theoretical physics.
Technologists and economists have long asserted that technological progress is a net positive for employment. Empirical data supported this view. Innovative technologies generally created larger numbers of better paying more interesting jobs. Workers developed new, more demanding skills. Physical labor diminished relative to higher skill, more intellectually demanding work. We should expect, therefore, that smart technologies like automation and AI will do the same – Right? This time the impacts are more difficult to predict because many jobs created by these innovative technologies require fewer skills, smarts, education and experience. Smart systems are performing increasingly complicated, intellectually demanding work, and often de-skilling, not up-skilling the human workforce.
For example, people can’t compete with computers when it comes to processing and crunching large volumes of data. So, it’s not surprising that raw data analysis is usually done by databases and software. Higher end analysis has traditionally been done by trained analysts using software as tools to facilitate time consuming, technically demanding work. It’s another example of technology automating lower end functions to free up people for more demanding work. Smart technologies are challenging this calculus. AI and machine learning are taking data processing and analysis much further by identifying the implications of current trends and predicting future ones. They are replacing trained human analysts in these sophisticated, intellectually demanding jobs. In this context, there are few if any higher-level work for trained, intellectually gifted human analysts. They already represented the top echelon in the field. Unlike previous analytical support systems that served as tools to improve human performance, many smart systems are replacing knowledge workers altogether.
These trends are increasing concerns that automation and smart systems will create high rates of structural unemployment. After all – Why would companies rely on human labor when they can restructure jobs and let smart systems do most of the physical and intellectual work? It’s a simple concept that is not so simple in practice. Automating some jobs with high intellectual content may be unavoidable but relinquishing human analytical, creative and decision-making capabilities can be risky. The challenge for companies is to identify the best mix of human capabilities and emerging smart systems. In this context, technology is often an equalizer, not a differentiator because it is affordable and available to all competitors. Differentiation and competitive advantage emerge from synergies of people and technology that are more than the simple sum of their parts.
Smart technologies are challenging business leaders in ways few had anticipated. CEOs are leading organizations that must continuously adjust the balance between human and smart systems capabilities. It often involves restructuring organizations, and changing management and leadership styles. New thinking must be translated into budget and decision-making authority. These changes affect talent acquisition and employee retention, development and training[1]. The focus is on achieving human and technological leadership. It’s a strategy supported by experience and research across national and international markets. For example, a multi-year MIT led international study of companies with revenues greater than 50 million dollars found that the most profitable had developed technological capabilities and human leadership. Most conducted continuous, targeted experiments and supported creative entrepreneurship across the enterprise. For the best companies, human capital was as indispensable to competitive advantage as the most innovative technologies.
Summary and implications
Disruptive technological innovations are accelerating. The latest waves are driving automation, artificial intelligence and machine learning out of high tech and into general commerce. Smart technologies are transforming how business gets done and, in the process, the role of human beings in the enterprise. Established businesses are struggling to adapt. New businesses with innovative business models compatible with smart technologies are emerging. These changes will be as disruptive in the years ahead as the Internet was a generation ago. History suggests that spectacularly successful companies will emerge, along with many catastrophic failures. Interestingly, while disruptive technologies will be the drivers of change, it will be human capital that determines which companies succeed and which ones stumble into oblivion.
References
[1] Robotics and AI spark skill shortage scare for CEOs, February 19, 2018, Financial Review, http://www.afr.com/technology/robotics-and-ai-spark-skill-shortage-scare-for-ceos-20180212-h0vzsm