Industry 5.0 will be fueled by minds, not just machines
Deloitte’s Global Generative AI Innovation Leader Nitin Mittal and Tomorrow CEO Mike Walsh explore the Fifth Industrial Revolution in which the catalyst for societal transformation is the augmentation and expansion of human intelligence.
Given the recency of the Fourth Industrial Revolution, it might be a surprise that we are on the verge of an entirely new one. Rapid progress in computation, connectivity, and artificial intelligence (AI)—accelerated by the COVID-19 pandemic—has brought forward the timeline for transformation. While prior industrial revolutions were premised on gains in operational efficiency, the next revolution will be powered by minds, not just machines—where the catalyst for societal transformation is the augmentation and expansion of human intelligence.
The Fifth Industrial Revolution is more than a marketing slogan. Imagine if we could find a way to align the capabilities of humans and machines while considering broader factors such as employee welfare, the environment, and community stakeholders. The stakes for such a balance will be more than social stability; it would be a potent platform for sustainable growth. The pressure for new drivers of productivity and creativity is growing. Over the past 20 years, productivity growth has slowed in most industrialized economies. In the U.S., for example, output per hour worked has grown at just 1.4% since 2004, half the growth rate experienced in the three decades following World War II.
So, what does it take to start a new revolution? Technology alone is rarely sufficient. Enabling technologies typically define industrial revolutions—steam, electricity, computing, digital connectivity, and AI. Yet, in each of these five technological breakthroughs, there was a lag between technical innovation and societal change. One of the reasons for that is ‘absorptive capacity,’ or an organization’s ability to recognize the value of new technology and apply it effectively.
A brilliant invention only changes things once people start experimenting with new production techniques, business models, and ways of working. For example, consider the 82-year gap between the invention of the electric dynamo by British physicist Michael Faraday in 1831 and the sophisticated application of electric power to mass manufacturing by Henry Ford at his Highland Park facility. Ford’s genius was not so much his adoption of a disruptive new technology but rather his realization that achieving radical productivity gains requires a complete rethink of the system of work.
Changing how we work has the potential to change who we are. A better-trained, more adaptable, and AI-augmented workforce is not only equipped to solve more complex problems but may also be better prepared to weather the inevitable economic upheavals from industrial transformation. Ford had to double wages to reduce turnover at his facility, but in today’s Fifth Industrial Revolution, the catalyst for more fulfilling work could be the creation of a digital workforce that eliminates the need for repetitive activities. Process automation is only half the story. What if the greatest underutilized resource is not idle factories or surplus capital but rather the untapped power of human intelligence?
Given AI’s impressive feats of insight and creativity in the last few years, it might seem counterintuitive to consider enhanced human cognition as a driver of economic productivity, let alone the basis of an entirely new Industrial Revolution. However, one way of thinking about the patterns of progress over the past few hundred years is from the perspective of efficiency.
The first two Industrial Revolutions focused on improvements in mechanical efficiency: We systemized manual production and relocated work from fields and artisanal crafts to standardized factories and mass production. Then, computational efficiency drove the following two revolutions, taking us from expensive standalone computers to scalable digital platforms connected in a global cloud of servers orchestrating smart systems and sophisticated supply chains. Arguably the next frontier is cognitive efficiency.
Cognitive efficiency can be defined as the ability to learn, solve problems, or create new concepts through the optimal use of the resources available to us. In the 21st century, those resources include the mental ones that we are born with, the enhanced capabilities we gain through education and training, and, of course, the artificial augmentations we can harness through technology. Not surprisingly, there is a vast gulf between merely having access to tools such as Bard and ChatGPT and designing a human-machine workflow that provides a competitive advantage.
The quest to unlock the collective cognitive resources of organizations will drive us to reconsider the nature of work. To be a successful knowledge worker today is no longer based on what you know but rather on how well you can learn. In an era of generative AI and large language models, valuable work is asking the right questions, assessing the generated outputs, and fine-tuning your model for better performance. Work, in this context, is not merely repeating known tasks—but being able to think more broadly about the nature of the work itself. We used to focus on doing, executing, and interacting. Work is now about exploring, connecting, and elevating the human experience. In other words—metacognition—the ability to think about how we think.
While redesigning work will free humans from mundane, repetitive decision-making—that will not be enough to kickstart a new age of exponential change. To do that, we must find ways to use AI to create net-new knowledge and breakthroughs beyond normal operations. How might this happen? Consider the discovery of penicillin or transistors, graphene, or microwaves. The history of breakthroughs is one of serendipity combined with the expertise of someone capable of recognizing the happy accident for what it truly is. Fortunately, generative AI with its ability to surface knowledge in unexpected ways and at scale may prove to be the tool organizations need to increase the probability of profitable discoveries.
Most leaders are now familiar with using AI chatbots, such as ChatGPT and Google Bard. However, the true disruptive potential of generative AI will arrive with the proliferation of virtual agents. The Fourth Industrial Revolution demonstrated the usefulness of digital twins of factories and machines in optimizing performance; in the era of Industry 5.0, we will likely have digital twins of people who can undertake autonomous action, insights, conversation, and execution.
AI-fueled organizations will be as unrecognizable from today’s enterprises as firms from a century ago are for us. The secret ingredient to successful transformation will be culture, not just technology. Culture is an operating system of interactions, and while the next revolution may be premised on the successful synthesis of human and machine, only those organizations who undertake a radical change in mindset will successfully make that transition.
The next decade has the potential to be extraordinary: We anticipate radical breakthroughs from amplified intelligence in every field, from health care to materials science. Yet, deploying AI to optimize business processes will not in itself unleash a new industrial age. Being incrementally better is not enough. To thrive in the world of tomorrow, we need to be different.
Note: This article was supplied by Deloitte.
Mike Walsh is the author of The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You. Walsh is the CEO of Tomorrow, a global consultancy on designing companies for the 21st century.
Nitin Mittal is the co-author of All in on AI: How Smart Companies Win Big with Artificial Intelligence, a Wall Street Journal bestseller. Mittal is Deloitte’s Global Generative AI Innovation leader and Consulting Emerging Markets leader, advising organizations on the application of AI and the implications of emerging technologies on the strategy and competitive positioning of businesses.