The fear of robots eclipsing human power in society, in particular the workforce, has persisted for decades despite the moderate progress of artificial intelligence systems. For professor and robotics researcher Ken Goldberg, a hybrid human-machine workforce is much more likely to take shape, and in many industries, it has already begun.

Not many companies are there yet, but there’s a developing framework for what it takes to lead an AI-driven company. Leaders at the forefront of AI have seven key attributes: They learn the technologies; establish clear business objectives; set an appropriate level of ambition; look beyond pilots and proofs of concept; prepare people for the journey; get the necessary data; and orchestrate collaborative organizations.

To deliver ROI and productivity, firms must overcome the barriers to implementing AI technology.

AI provides access to unstructured information and enables organizations to learn faster and offer new services.

AI’s largest and most enduring contributions will be in non-technology sectors, and many of them will come from China. Buoyed by the country’s latest five-year plan and enabled by centralized data, Chinese companies are investing aggressively in AI and adapting their business models to make the most of AI’s potential, but unclear business cases and bottlenecks due to lacking technical capabilities hinder adoption.

Software continues to “eat the world,” but often at the cost of user privacy and trust. In order to grow responsibly, companies must move from a “can we” to a “should we” framework when bringing products to market.

Less than 5% of companies are using AI to reinvent how they do business, but the competitive intensity surrounding the technology suggests that a wait-and-see strategy could be a costly mistake. To get a share of the global profit pool of $1 trillion that AI will produce by 2030, the McKinsey Global Institute says companies should begin adopting it at scale within the next three years.

When pundits talk about the impact that artificial intelligence will have on the labor market, the outlook is usually bleak, with the loss of many jobs to machines as the dominant theme. But that’s just part of the story — a probable outcome for companies that use AI only to increase efficiency. As it turns out, companies using AI to also drive innovation are more likely to increase headcount than reduce it.

Virtually all human achievements have been made by groups of people, not lone individuals. As we incorporate smart technologies further into traditionally human processes, an even more powerful form of collaboration is emerging.

Businesses should use AI technology as a tool to improve customer service and processes, not just to imitate humans.

AI can do much more than augment human performance in the workplace.

Using industry examples and findings from the McKinsey Global Institute’s research, presenter Jacques Bughin describes the current state of AI and offers strategies for maximizing its potential.

Companies are adopting artificial intelligence at an accelerated pace — and learning that developing and deploying AI is not like implementing a standard software program. Before diving into AI systems, companies should consider three principles that can greatly improve the chances for a successful outcome. First, they need to recognize that humans and machines are in this together. Second, they need to teach the AI systems with a lot of data. And third, they need to continually test what the systems have learned.

As companies rely more and more on AI-driven chatbots to communicate with customers, they need to consider ways to make computers’ communication and understanding better and more natural.

Digital technologies will increase the high levels of ambiguity that executives must navigate. Aspiring leaders may respond by ignoring the challenge, which isn’t sustainable. A better response is to harbor healthy skepticism of the digital technologies they champion, develop values that will lead to better decisions, and work to institutionalize those values at the organizational level.

For more than a century, economies of scale made the corporation an ideal engine of business. But now, a flurry of important new technologies, accelerated by artificial intelligence (AI), is turning economies of scale inside out. Business in the century ahead will be driven by economies of unscale, in which the traditional competitive advantages of size are turned on their head.

Researchers are exploring how to create intelligent machines that work with us better as opposed to taking our place. Robots that can express human body language can have a positive effect on their human colleagues, enabling them to be more effective at their jobs, take on higher-level tasks, and realize psychological benefits. The overall result is a more productive human-robot team.

It’s possible that humankind has created complex, systemic problems that exceed our human capacity to solve them. Some companies, particularly the tech giants, are recognizing this possibility and looking to AI as a tool for solving environmental and social problems. One of these companies is Microsoft. In December 2017, it committed $50 million to its new “AI for Earth” program to fund innovators who are making progress in four critical areas — climate change, water, agriculture, and biodiversity.

AI’s most potent, long-term economic value may lie not in the thousands of new startups, but in the ability of AI to augment the discovery and pursuit of basic scientific advances that could be the foundations of new industry.

Systems using artificial intelligence increasingly match or surpass human-level performance, driving great expectations and soaring stock prices. Yet measured productivity growth has declined by half over the past decade.