- Read Time: 7 min
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.
Showing 1-20 of 45
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.
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?
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.
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.
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.
The MIT Sloan School of Management 14th annual CIO Symposium discusses the impact artificial intelligence will have on the jobs of the future.
AI will augment jobs, much as electric ignition, cruise control, and back-up cameras incrementally improved the automobile. So the question is not “Which jobs will be replaced?” but rather, “How will jobs be increasingly assisted by AI?”
Big Data is moving to a new stage of maturity — one that promises even greater business impact and industry disruption over the course of the coming decade. Organizations are now combining the agility of Big Data processes with the scale of AI capabilities to accelerate the delivery of business value.
A new global study finds several new categories of human jobs emerging. These roles are not replacing old ones. They are brand-new positions that complement the tasks performed by AI machines and will require skills and training that have never before been needed.
The growth of AI in business is likely to defy smooth, linear progression. It is difficult to build off of what has already happened to reliably determine what is likely to develop — and sooner or later, there’s a point of diminishing returns.
Showing 1-20 of 45