The scale of impending technological change brought about by artificial intelligence (AI) and machine learning has been likened to the transition from the steam engine to the electric motor by Andrew McAfee and Erik Brynjolfsson in their book ‘Machine, Platform, Crowd’. They argue that those who simply thought that an electric motor would replace a steam engine were left behind in an industrial revolution that saw the new technology enable ideas like conveyor belts, overhead cranes, and machine shops that changed the face of manufacturing and ushered in a new era of innovation, touching virtually every aspect of our lives. 

In the same way that electrification required businesses to change their model, artificial intelligence requires fundamental shifts in thinking and approach to adapt to a new landscape. Successful companies will embrace artificial intelligence from a technological innovation perspective, while making equally fundamental shifts in their leadership capacity to adapt to a new business reality. 

Understanding the evolution in the application of machine learning, how to harness its potential, and the implications on the conduct of leadership is already differentiating some leaders from the pack. Being able to see beyond the continuous improvement cycle of digitization of existing processes to true digital innovation will offer unique competitive advantage. 

According to Gartner, digital dexterity is the “ability and desire to use existing and emerging technology to drive better business outcomes” and their Annual Chief Data Officer Survey indicates that “by 2020, 50% of organizations will lack sufficient AI and data literacy skills to achieve business value.”

Digital dexterity, agility, and the ability to harness the creativity of a Gen Z workforce will be hallmarks of the emerging leadership toolkit, together with the ability to strategically govern data and navigate an evolving legal and ethical framework in a hyper connected  real-time world where machines increasingly take on decisions previously reserved for humans. 

This presents unique challenges for existing mid career and senior leaders to remain relevant, develop the knowledge to evaluate opportunities in emerging technologies, and consider the potential unintended consequences of their decisions to manage organizational risk. 

Long the domain of the specialist, machine learning applications are becoming ubiquitous, and transitioning from a decision support tool with well understood heuristics to an autonomous decision making tool where large volumes of data are processed from a computer application which ‘learns’ within seconds and makes decisions in ways that are not fully understood or transparent; this can raise issues of data bias, safety, and liability when things go wrong. In high reliability industries, where the complexity of human and technology interaction can have material safety impacts, the impetus for leaders of utilities, suppliers and regulators to have a sufficient digital dexterity about machine learning and artificial intelligence is critical.  According to Ronald M. Baecker in his highly relevant book ‘Computers and Society: Modern Perspectives’, “Machine learning systems do not have self knowledge and common sense. They cannot explain the logic behind their decisions. We do not know what a machine learning system knows and does not know, and we cannot understand its decisions.”  Despite this, organizations, and their leaders, remain accountable for decisions and must maintain the trust of their employees, investors, neighbours and customers. 

Experts are finding ways to establish ethical frameworks for designers and developers, but it is up to senior leaders to adopt these standards and embed them in the organizational culture, governance, and systems. One practical framework, Ethical by Design, is being developed by Jennifer Boger, director of the University of Waterloo’s Intelligent Technologies for Wellness and Independent Living lab. According to the University, “Boger and her collaborators want to empower creators of technologies and systems to better-consider the ethics of what they are building, at every stage of the development process. The [framework] proposes a set of principles acting as signposts for developers to consider, discuss and support in the technology they are designing.” Having such principles in place can help avoid unintended consequences of the application of artificial intelligence. 

To broadly engage society for the future will also require the leaders of today to equip our youth to discern about the implications of artificial intelligence, in addition to having the technical skills and data literacy to thrive in the new reality. Leaders should proactively find ways to connect with youth through events and initiatives like hackathons, design challenges, and maker spaces, creating mutually beneficial opportunities to learn.

The coming tsunami of changes to society and all aspects of business from artificial intelligence is difficult to imagine. Navigating the changes will require both digital dexterity and data literacy by business leaders, as well as citizens and government policy makers. In the absence of a crystal ball, engagement around effective digital governance and a systematic effort to improve awareness of critical issues related to artificial intelligence penetration into all aspects of our lives will mitigate some of the unintended consequences of the transition through the digital revolution.