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The Five Ts of Human-Machine Collaboration

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The Five Ts of Human-Machine Collaboration

It’s a no-brainer that artificial intelligence (AI) will be the number one driver of business change in the next five years....

5 Minutes Read

It’s a no-brainer that artificial intelligence (AI) will be the number one driver of business change in the next five years. It seems that every company today is interested in becoming an AI-first company. And why not? AI promises to provide huge economic benefits including boosting revenue growth, increasing productivity levels, and acquiring and retaining customers. Even conservative estimates project at least $1.49 trillion in growth due to AI over the next ten years. AI has become a potential panacea for many of our existing real-world problems and for the future growth. But before jumping in ‘gung ho,’ leaders must realize that there’s a lot of playing field between the realities of today and what lies ahead. Just over one-third of organizations feel fully prepared to handle future work with intelligent machines. There’s a lot of groundwork and preparation involved in terms of skills, culture, processes, and technology.

The transition to the new machine age will not be easy. In fact, the process will be overwhelming for many leaders. To help them adjust, leaders will need greater clarity on how work will shift, what the new and valuable work will be, and how they will be supported when transitioning to a human-intelligent machine workforce. In my new report on humans + machines, I offer a framework to help organizations align five elements (5Ts)—tasks, teams, talent, technology, and trust—to successfully transition into the new machine age:

  • Teams: Small, flexible and hybrid. The transition to the intelligent machine age won’t happen without an acute focus on the relationship between humans and machines, how the two will collaborate, and how the current workforce and the business itself will adapt to AI. We will witness a shift from larger hierarchical team structures to smaller teams in the future. These changes will allow individuals and teams to become more fluid and flexible across roles and functions.
  • Tasks: Learning to assign and share. No one task will be 100% driven by a machine or a human by themselves; instead, every task will have some degree of shared involvement. Businesses will need to create a task allocation framework to define roles and responsibilities and set the rules for AI systems and workers to coordinate to accomplish a task. Augmented reality/virtual reality (AR/VR) will be a driving force for enabling workers to collaborate meaningfully with machines through a simple and intuitive interface (translating consumer behavior to business users, as well as to machines, for instance).
  • Talent: The fusion of human and technical skills. Technical skills will continue to be in demand, but need to be blended with human-centric skills of creativity, problem-solving, adaptability, organization and communication among others. Doubling down on human skills will not be sufficient, though. Human skills will need to be tweaked for optimal human-machine collaboration. Workers will need to think in terms of the systems, tools and processes required to make the best use of AI-driven insights and capabilities.
  • Technology: IT matters more than ever. For decades, IT has followed the theory of “Why fix what’s not broken?” This approach has led to the massive accumulation of outdated legacy infrastructure, which is not only expensive to upgrade but also slow to meet the demands of intelligent machines. Whether your organization is recreating a business process from scratch or injecting AI into front-, middle- or back-office processes, success will depend on how well the IT infrastructure is integrated with AI systems. Our advice is, don’t jump the AI gun unless you have addressed your IT infrastructure woes.
  • Trust: The new battleground for success. The threat to workers’ current jobs is an inescapable topic when it comes to AI and this will alter employee-employer trust levels in the future and not many leaders have a clear understanding of how to handle this disruption. Also, from unexpected or biased results, to perpetuation of dangerous errors, many people fear “what can go wrong” with intelligent machines. What if an AI-powered medical system makes a recommendation that leads to serious injury or even death? This could have a catastrophic impact on companies’ brand and finances. For more information on this important topic, check out my recent post on how to elevate employee-employer trust levels and instill trust in machines.

Preparing for the future of work will be full of change, disruption, opportunity, and risk. To win in this age of intelligent machines, businesses should embrace the five Ts to reimagine tasks, restructure teams, remix talent, reinvent IT infrastructure, and reestablish trust among workers and with intelligent machines. Ultimately, as the adoption of intelligent machines increases, the process of ensuring a successful partnership between humans and machines will be the biggest opportunity and challenge for organizations.


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