Superman versus Batman. Captain America versus Iron Man. Zuckerberg versus Musk? 

The reported clash between the two technology titans is proof that not everyone sees the benefits and dangers of artificial intelligence in the same light. Yet from Facebook’s algorithms to Tesla’s self-driving cars, it’s clear that AI isn’t science fiction any longer—and that we’re already at the cusp of a new era, with AI poised to deliver transformational change in business and society. 

As we explain in our book Human + Machine: Reimagining Work in the Age of AI, which is based on research with 1,500 organizations, the fundamental rules by which organizations run are being rewritten daily. As businesses deploy AI systems—from machine learning to computer vision to deep learning—some will see modest short-term productivity gains. But others—by understanding and taking advantage of the true nature of AI’s impact—will attain breakthrough improvements in performance, often by developing game-changing innovations. 

More than just automating processes, AI systems are augmenting human capabilities and enabling people and machines to work collaboratively, changing the very nature of work and transforming businesses. To exploit AI’s potential, leading companies are embracing a new era of business processes that’s more fluid and adaptive, with organic teams comprising both humans and advanced AI systems. 

This emerging symbiosis between man and machine is unlocking what we call the third wave of business transformation. The first, ushered in by Henry Ford, involved standardized processes; the second, which peaked in the 1990s with business process reengineering, consisted of automated processes. Building on the first two, the third wave involves adaptive processes and will be more dramatic, ushering in entirely new, innovative ways of doing business. 

The third wave has created what we call “the missing middle”—a huge, dynamic and diverse space in which humans and machines collaborate to achieve exponential increases in business performance. Here humans and machines are symbiotic partners, exploiting what each party does best and pushing each other to higher levels of performance. Humans, for example, are needed to develop, train and manage various AI applications. In doing so, they’re enabling those systems to function as true collaborative partners. Machines, in turn, are augmenting human capabilities—providing people with superhuman capabilities, such as the ability to process and analyze copious amounts of data in real time. 

To exploit the full power of AI, companies must address the missing middle by considering new employee roles, establishing novel types of working relationships between humans and machines, changing traditional concepts of management and overhauling their very concept of work itself. In fact, we’ve we’ve identified three categories of human-machine interaction in the missing middle in which AI augmentation is already reshaping business processes:

Amplification, in which AI agents give people extraordinary data-driven insights, often using real-time data—such as using augmented reality glasses to overlay digital information or instructions on a worker’s field of view. It’s like your brain—but better.

Interaction, in which AI agents employ advanced interfaces such as voice-driven natural-language processing to facilitate interactions between or on behalf of people. Often used in personal-assistant and customer-services roles, these AI agents are often designed to have a personality and can function at scale, assisting many people at once.

Embodiment, in which AI agents work in combination with sensors, motors and actuators that enable robots to share workspace with humans and engage in physically collaborative work. These robots work with people on factory floors and in warehouses. They come in the form of robot appendages, package-carrying autonomous carts and aerial delivery drones. 

The AI revolution isn’t approaching —it’s already here. It’s about reimagining your processes, across all functions of the company, to leverage the technology’s power to augment human capability.

We’ve also identified three broad types of brand-new jobs in the missing middle that companies will need to ensure the successful implementation of AI: 

Trainers, who will teach AI systems how they should perform, helping natural-language processors and language translators make fewer errors and teaching AI algorithms how to mimic human behaviors. At the simple end of the spectrum, trainers help natural-language processors and language translators make fewer errors. At the complex end, AI algorithms must be trained to mimic human behaviors.

Explainers, who will bridge the gap between technologists and business leaders, explaining the inner workings of complex algorithms to nontechnical professionals. Within explainers are three subcategories: transparency analysts, who classify the reasons a particular AI algorithm acts as a black box; algorithm forensics analysts, who hold algorithms accountable for their results; and explainability strategists, who make important judgment calls about which AI technologies to deploy for specific applications.

Sustainers, who will ensure that AI systems are operating as designed—i.e., functioning properly as tools that exist to serve us, making our work and lives easier. We’ve identified three sustainer roles: context designers, who ensure that AI systems are designed right in the first place; AI safety engineers, who anticipate and address the unintended consequences of an AI system; and ethics compliance managers, who act as ombudsmen for upholding generally accepted human values and morals.

Fusion Skills To Ride The Third Wave 

Our research found that the leading companies in various industries are already riding the third wave, developing the next generation of processes and skills to capitalize on human-machine collaborations. To reimagine processes in the missing middle, they’ve developed new and distinct skills that draw on the fusion of human and machine talents to create better outcomes than can be achieved by either working independently. We’ve identified eight such “fusion skills”:

Rehumanizing Time: Few people do their best work when they operate relentlessly at the edge of their productivity threshold, so as AI changes the nature of human-machine interaction, rehumanizing time reminds us that we have an opportunity to increase worker effectiveness and well-being, along with productivity. It allows people to skillfully redirect their time toward more human activities, such as increasing customer satisfaction, performing more-complex machine repairs or conducting creative, blue-sky research.

Responsible Normalizing: Normalizing is about responsibly shaping the way people understand and perceive human-machine collaborations; it requires a subset of other skills, including an understanding of humanities, STEM skills, an entrepreneurial spirit, public relations acumen and an awareness of social and community issues. 

Judgment Integration: When a machine is uncertain about what to do or lacks necessary business or ethical context in its reasoning model, people must be smart about sensing where, how and when to step in. Human judgment and effectuation will always be a key component to any reimagined process.

Intelligent Interrogation: How do you probe a massively complex system or predict interactions among complex layers of data? People simply can’t do this on their own, so they must ask questions of their friendly AI to get the insights they need.

Bot-Based Empowerment: Through bot-based empowerment, people can punch above their weight using intelligent agents. Examples include scheduling agents such as Clara and x.ai; Textio and IBM’s Watson Tone Analyzer to improve writing; and even Doli.io, to post updates or pictures to social media to build your professional and personal brand.

Holistic Melding: Although robots are revolutionizing surgery, the keys to success remain the surgeons and their ability to learn the skills required to operate the robot—in essence, the ability to project their surgical skills into the body of a machine. In the age of human-machine fusion, holistic (physical and mental) melding will become increasingly important.

Reciprocal Apprenticing: Traditionally, technological education has gone one way: People learn how to use machines. But with AI, machines are learning from humans, and humans, in turn, learn from machines. Apprenticing means that customer service representatives or anyone working in conjunction with an AI agent will act as “role models” to their digital colleagues—requiring not only that the teacher have appropriate technical skills, but that the AI is built in a way that makes it easily trainable.

Relentless Reimagining: Perhaps the most important hybrid skill is the ability to reimagine how things currently are—a fundamental skill that lays the foundation for other skills like intelligent interrogating and bot-based empowerment. It’s this capability to reimagine that enables people to adapt more easily to a different world, in which advanced AI technologies continually transform organizational processes, business models and industries.

The third wave of business transformation involves adaptive processes, ushering in entirely new, innovative ways of doing business.

The Future Is Here 

The AI revolution isn’t approaching—it’s already here. It’s about reimagining your processes, across all functions of the company, to leverage the technology’s power to augment human capability. By giving people powerful tools to do more, AI can rehumanize work, giving us more time to be human, rather than using our time to work like machines. The difference between the winners and losers will be determined not by whether an organization has implemented AI, but on how it has.

CREDIT: SimonKR/iStock