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.

The impact of artificial intelligence on the future of work and organizations was an especially popular topic on MIT Sloan Management Review’s website in 2017. But AI wasn’t the only subject on readers’ minds. Other widely read pieces of new content addressed timely issues like digital transformation and design thinking — as well as perennially important topics such as innovation, strategy execution, problem formulation, and negative emotions in the workplace.

Many countries experiencing fast growth in the aging of their populations, including Germany, Japan, and South Korea, are also experiencing growth in their gross domestic product. The most plausible explanation for this counterintuitive finding is that there has been a rapid adoption of automation technologies in countries with more pronounced demographic changes. In other words, technology isn’t just capable of offsetting potential negative effects of aging populations — it’s already doing so.

Artificial intelligence is beginning to replace many of the workplace roles that men dominate. The parts of those jobs that will have staying power are those that rely more heavily on emotional intelligence, abilities such as empathy, persuasion, and inspiration — skills in which women typically excel. In the AI economy, men won’t be as successful as women unless they embrace these differentiator skills.

As organizations explore how software robots — or bots — can help automate administrative tasks and decisions, it pays to keep in mind some of the risks that come with the territory.

Business has become too complex for boards and CEOs to make good decisions without intelligent systems. Just as artificial intelligence helps doctors use patient data to make better diagnoses and create individualized medical solutions, AI can help business leaders know more precisely which strategy and investments will provide exponential growth and value in an increasingly competitive marketplace.

A global survey by the McKinsey Global Institute finds that AI is delivering real value to companies that use it across operations. C-level executives report that when they adopt AI at scale — meaning they deploy AI across technology groups, use AI in the most core parts of their value chains, and have the full support of their executive leadership — they are finding not just cost-cutting opportunities, but new potential for business growth, too.

Disruption from artificial intelligence (AI) is here, but many company leaders aren’t sure what to expect from AI or how it fits into their business model. Yet with change coming at breakneck speed, the time to identify your company’s AI strategy is now. MIT Sloan Management Review has partnered with The Boston Consulting Group to provide baseline information on the strategies used by companies leading in AI, the prospects for its growth, and the steps executives need to take to develop a strategy for their business.

Detailed and data-rich insights won’t help your company if your employees don’t know where to find them — but that’s a problem AI can solve. Machine learning can enable faster organizational learning by helping each employee quickly understand what others in the organization understand — forming a knowledge distribution network.

Tom Davenport speaks at the 2017 MIT CIO Symposium, sharing the three ways businesses use artificial intelligence.

Most of us view our jobs as specialized or somehow differentiated, but the world of business and management increasingly feels otherwise. For many organizations today, the next big driver of job commoditization is automation driven by smart machines. Simply put, if a job is viewed as a commodity, it won’t be long before it’s automated. The key for workers whose jobs have traditionally seemed safe: Highlight the tasks that require a human touch.

Andrew McAfee and Erik Brynjolfsson discuss the future of work and the global economy at the 2017 MIT CIO Symposium.

Many managers are excited about smart machines but are struggling to apply machines’ limited intelligence. Indeed, computers can process data just fine, but to generate competitive advantage from machine learning applications, organizations must upgrade their employees’ skills. Companies will also need to redesign employee accountabilities to empower and motivate them to deploy smart machines when doing so will enhance outcomes.

In the first half of 2017, MIT SMR website visitors showed high interest in articles about how artificial intelligence will affect the job market and organizations. In fact, three of the 10 most-read pieces of new MIT SMR editorial content during that period address some aspect of that question. But the other seven most popular new articles cover a wide range of topics — from dealing with negative emotions in the workplace to exploring the organizational implications of blockchain technology.