In February 2022, the MIT Sloan School of Management issued a report that glowingly stated that many companies were starting to make "serious money" with AI. This was welcome news, since MIT Sloan's 2019 report had shown that seven out of 10 companies investing in AI at that time were seeing minimal or no benefit from AI. One factor the 2022 Sloan report mentioned was that in the 2019 survey, there were very few organizations that had artificial intelligence in production. In 2022, according to MIT Sloan, 26% of companies had AI in production. This usage increase was substantial.

AI has been a buzzword and businesses are all at different stages of implementing it. But is it actually solving anything? AI tools help individuals excel in their independence by helping them learn from past actions, projecting outcomes of current actions, and even offering feedback on your past actions in order to improve work performance. If using AI would make your customer service interactions improve, why wouldn't you use it? For example, Walgreens found that if they can better predict when a customer's pharmacy order will be ready, it improves both customer satisfaction and worker satisfaction. In this new study from MIT Sloan and BCG, it was noted that AI is making worker's lives easier, in simple ways that we may not always be aware of.

Companies around the world are adapting to new ways of doing business, with automation and artificial intelligence playing an important role amid the ongoing pandemic. These insights from MIT Sloan Management Review can help ensure digital transformation initiatives are successful while also resilient in the face of new disruption. As enterprises consider what digital transformation will look like after the pandemic, MIT Sloan senior lecturerGeorge Westermanencourages business leaders to leave behind their pre-pandemic assumptions about innovation. Instead, he said in a recent webinar, lean into how COVID-19 forced enterprises to change for the better. The collective response to the pandemic challenged longstanding notions about the efficiency of remote work, the agility of corporate IT departments, the rigidity of government regulators, and the willingness of customers to embrace (and pay for) digital interactions.

Should your Roomba need a W-2? Probably not, but it's an amusing thought when debating the more serious topic of whether or not a robot should have to pay taxes -- and how to do it. During the June MIT Technology Review EmTech Next event, two experts argued both sides of the question before an audience at the MIT Media Lab in Cambridge, Massachusetts. Ryan Abbott, professor of law and health sciences at the University of Surrey, argued in favor of taxing robots, while Ryan Avent, economics columnist for The Economist, argued against the idea. Both agreed there needs to be a shift in tax burden from labor to capital. Avent, however, carried the most audience votes by the end of the debate. Here are some highlights from each of the men's arguments.

What did you think of the last commercial you watched? Would you buy the product? You might not remember or know for certain how you felt, but increasingly, machines do. New artificial intelligence technologies are learning and recognizing human emotions, and using that knowledge to improve everything from marketing campaigns to health care. These technologies are referred to as "emotion AI." Emotion AI is a subset of artificial intelligence (the broad term for machines replicating the way humans think) that measures, understands, simulates, and reacts to human emotions.

As with most iterations or applications of artificial intelligence, machine learning can either catapult the imagination to utopian climbs or conjure deeply dystopian anxieties. And while neither the stuff of Star Trek nor Terminator will come to pass anytime soon, machine learning will likely be to the post-industrial era what automation was once for the industrial, announcing both promise and perils across nearly every sector of business and society. Are business schools-- or more importantly, their graduates-- prepared for the changes ahead? Many schools are already integrating a deeper technical understanding of machine learning into their MBA curricula. In a world where computers perform more and more of the cognitive labors once reserved for humans, it makes sense that MBAs would tack closer to the role of engineers.

Each day we read about amazing technology breakthroughs, particularly when it comes to artificial intelligence (AI). But if AI is so great, why are these breathtaking technological achievements not matched with soaring productivity and economic growth? Or, to paraphrase an old jibe: If the economy is so smart, why aren't we all rich? After all, we live among astonishing examples of potentially transformative new technologies that could greatly increase productivity and economic welfare. As noted in the 2014 book, "The Second Machine Age," leaps in AI, machine learning and, more recently in areas such as image recognition, abound.

Each day we read about amazing technology breakthroughs, particularly when it comes to artificial intelligence (AI). But if AI is so great, why are these breathtaking technological achievements not matched with soaring productivity and economic growth? Or, to paraphrase an old jibe: If the economy is so smart, why aren't we all rich? After all, we live among astonishing examples of potentially transformative new technologies that could greatly increase productivity and economic welfare. As noted in the 2014 book, "The Second Machine Age," leaps in AI, machine learning and, more recently in areas such as image recognition, abound.

On May 23, 2017, the MIT Sloan School of Management hosted the 14th annual CIO Symposium: "The CIO Adventure: Now, Next and… Beyond." The one-day event brought senior IT executives together to discuss key technologies, including IoT, AI, blockchain, big data, DevOps, cloud computing, and cybersecurity. The main idea was to help prepare these tech leaders for challenges they face, including shepherding ongoing digital transformations, building a digital organization, and managing IT talent. With these concerns top-of-mind for CIOs and IT leaders, MIT Media Lab's Joi Ito moderated the session "Putting AI to Work," which featured Josh Tenenbaum, a professor in the Department of Brain and Cognitive Sciences at MIT; Ali Azarbayejani, CTO of Cogito Corporation; Seth Earley, CEO of Earley Information Science; and Ryan Gariepy, CTO and co-founder of Clearpath Robotics and OTTO Motors.

In 2008, four students at the MIT Sloan School of Management developed a system for captioning online video that was far more efficient than traditional methods, which involve pausing a video frequently to write text and mark time codes. The system used automated speech-recognition software to produce "rough-draft" transcripts, displayed on a simple interface, that could easily be edited. Landing a gig to caption videos from five MIT OpenCourseWare (OCW) classes, the students were able to caption 100 hours of content in a fraction the time of manual captioning. This marked the beginning of captioning-service company 3Play Media, which now boasts more than 1,000 clients and an equal number of contracted editors processing hundreds of hours of content per day. Clients include academic institutions, government agencies, and big-name companies -- such as Netflix, Viacom, and Time Warner Cable -- as well as many users of video-sharing websites.