Artificial Intelligence

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Unpacking the AI-Productivity Paradox

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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 20 Most Popular MIT Sloan Management Review Articles of 2017

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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.

The New Economic Benefits of Older Workers

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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.

Could AI Be the Cure for Workplace Gender Inequality?

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.

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AI in the Boardroom: The Next Realm of Corporate Governance

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.

Five Management Strategies for Getting the Most From AI

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.

Sponsor's Content | Journey to AI: Building a Foundation in Big Data Analytics

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AI is making headlines — and not just in futuristic technologies like self-driving cars. It’s transforming business processes in established industries, from retail to financial services to manufacturing. But what’s the best way to adopt AI for your organization?

Reshaping Business With Artificial Intelligence

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.

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Accelerate Access to Data and Analytics With AI

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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.

When Jobs Become Commodities

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.

The Fundamental Flaw in AI Implementation

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.

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The 10 Most Popular New MIT SMR Articles

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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.

Video: Preparing for the Changes AI Will Bring to Tomorrow’s Jobs

At the MIT Sloan School of Management’s 14th annual CIO Symposium, “The CIO Adventure: Now, Next and… Beyond,” senior IT executives came together to discuss key technologies, including how AI will transform the workplace. The goal: to help prepare these tech leaders for challenges they face, including shepherding ongoing digital transformations, building a digital organization, and managing IT talent.

Romantic and Rational Approaches to Artificial Intelligence

Organizations have made rapid gains in their ability to generate big data sets, but the ability of managers and executives to develop insights from that data has lagged behind. Data processing by artificial intelligence offers the prospect of speeding things up — but it also risks expanding the gap, as managers lack understanding of how AI reaches its data-based conclusions.

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