Most companies are struggling to realize artificial intelligence's potential to completely transform the way they do business. The problem is, they typically apply AI in a long list of discrete uses, an approach that doesn't produce consequential change. Yet trying to overhaul the whole organization with AI all at once is simply too complicated to be practical. What's the solution? Using AI to reimagine one entire core business process, journey, or function end to end, say three McKinsey consultants. That allows each AI effort to build off the previous one by, say, reusing data or enhancing capabilities for a common set of stakeholders. An airline, for example, focused on its cargo function, and a telecom provider on its process for managing customer value. Scaling up AI involves four steps: (1) Identify an area where AI will make a big difference reasonably quickly and there are multiple interconnected activities and opportunities to share technology. (2) Staff the team with the right people and remove the obstacles to their success. (3) Reimagine business as usual, working back from a key goal and then exploring in detail how to achieve it. (4) Support new AI-based processes with organizational changes, such as interdisciplinary collaboration and agile mindsets.

Many organizations are drowning in a flood of corporate bullshit, and this is particularly true of organizations in trouble, whose managers tend to make up stuff on the fly and with little regard for future consequences. Bullshitting and lying are not synonymous. While the liar knows the truth and wittingly bends it to suit their purpose, the bullshitter simply does not care about the truth. Managers can actually do something about organizational bullshit, and this Executive Digest provides a sequential framework that enables them to do so. They can comprehend it, they can recognize it for what it is, they can act against it, and they can take steps to prevent it from happening in the future. While it is unlikely that any organization will ever be able to rid itself of bullshit entirely, this article argues that by taking these steps, astute managers can work toward stemming its flood.

Although manipulations of visual and auditory media are as old as the media themselves, the recent entrance of deepfakes has marked a turning point in the creation of fake content. Powered by the latest technological advances in artificial intelligence and machine learning, deepfakes offer automated procedures to create fake content that is harder and harder for human observers to detect. The possibilities to deceive are endless-including manipulated pictures, videos, and audio-and organizations must be prepared as this will undoubtedly have a large societal impact. In this article, we provide a working definition of deepfake together with an overview of its underlying technology. We classify different deepfake types and identify risks and opportunities to help organizations think about the future of deepfakes. Finally, we propose the R.E.A.L. framework to manage deepfake risks: Record original content to assure deniability, expose deepfakes early, advocate for legal protection, and leverage trust to counter credulity. Following these principles, we hope that our society can be more prepared to counter deepfake tricks as we appreciate its treats.

Artificial intelligence seems to be on the brink of a boom. It's now guiding decisions on everything from crop harvests to bank loans, and uses like totally automated customer service are on the horizon. Indeed, McKinsey estimates that AI will add $13 trillion to the global economy in the next decade. Yet companies are struggling to scale up their AI efforts. Most have run only ad hoc projects or applied AI in just a single business process. In surveys of thousands of executives and work with hundreds of clients, McKinsey has identified how firms can capture the full AI opportunity. The key is to understand the organizational and cultural barriers AI initiatives face and work to lower them. That means shifting workers away from traditional mindsets, like relying on top-down decision making, which often run counter to those needed for AI. Leaders can also set up AI projects for success by conveying their urgency and benefits; investing heavily in AI education and adoption; and accounting for the company's AI maturity, business complexity, and innovation pace when deciding how work should be organized.

Tapping into the creativity of a crowd can provide a highly efficient and effective means of acquiring ideas, work, and content to solve problems. But crowdsourcing solutions can also come with risks, including the legal risks associated with intellectual property. Therefore, we raise and address a two-part question: Why-and how-should organizations deal with intellectual property issues when engaging in the crowdsourcing of solutions? The answers lie in understanding the approaches for acquiring sufficient intellectual property from a crowd and limiting the risks of using that intellectual property. Herein, we discuss the hazards of not considering these legal issues and explain how managers can use appropriate terms and conditions to balance and mitigate the risks associated with soliciting solutions from a crowd. Based on differences in how organizations acquire intellectual property and limit associated risks, we identify and illustrate with examples four approaches for managing intellectual property (passive, possessive, persuasive, and prudent) when crowdsourcing solutions. We conclude with recommendations for how organizations should use and tailor the approaches in our framework to source intellectual property from a crowd.

From the seclusion of monastic life to the noise of Silicon Valley, the ancient practice of mindfulness has 'come out of the cloister.' As an antidote to mindless cognition and behavior, the practice of mindfulness-with its principle of grounding attention in the present moment-has been shown to have powerful and positive effects at both the individual and the collective level and in fields as wide-ranging as medicine, schooling, prison programs, law and negotiation, business, and even the army. This installment of Marketing & Technology introduces mindfulness to managers and explores its potential for enhancing the service encounter. We begin by reviewing the two main conceptualizations of mindfulness: the cognitive and the contemplative. We then explore the service encounter from the perspective of emotional labor and show how mindfulness can change surface acting into deep acting, thereby significantly improving the service encounter for both the consumer and provider. We also explore the other benefits of mindfulness and their application to the service encounter: adaptability, flexibility and creativity. We conclude by sharing resources for managers interested in implementing mindfulness training.

Managers are frequently tasked with increasing the engagement levels of key stakeholders, such as customers and employees. Gamification--defined as the application of game design principles to change behavior in non-gaming contexts--is a tool that, if crafted and implemented properly, can increase engagement. In this article we discuss how gamification can aid customer and employee engagement, and delineate between four different types of customers and employees who act as 'players' in gamified experiences. We include illustrative examples of gamification and conclude by presenting five lessons for managers who wish to utilize gamification.

Although the protection of secrets is often vital to the survival of organizations, at other times organizations can benefit by deliberately leaking secrets to outsiders. We explore how and why this is the case. We identify two dimensions of leaks: (1) whether the information in the leak is factual or concocted and (2) whether leaks are conducted overtly or covertly. Using these two dimensions, we identify four types of leaks: informing, dissembling, misdirecting, and provoking. We also provide a framework to help managers decide whether or not they should leak secrets.

Two related trends characterize the recent past: value propositions are migrating from the physical to the informational, and value creation is shifting from firms to consumers. These two trends meet in the phenomenon of " consumer generated intellectual property" (CGIP). This article addresses the question: " How should firms manage the intellectual property that their customers create?" It explores how CGIP presents important dilemmas for managers and argues that consumers' intellectual property should not be leveraged at the expense of their emotional property. It integrates these perspectives into a diagnostic framework and discusses eight strategies for firms to manage CGIP.

There is growing interest in how gamification--defined as the application of game design principles in non-gaming contexts--can be used in business. However, academic research and management practice have paid little attention to the challenges of how best to design, implement, manage, and optimize gamification strategies. To advance understanding of gamification, this article defines what it is and explains how it prompts managers to think about business practice in new and innovative ways. Drawing upon the game design literature, we present a framework of three gamification principles--mechanics, dynamics, and emotions (MDE)--to explain how gamified experiences can be created. We then provide an extended illustration of gamification and conclude with ideas for future research and application opportunities.

Traditionally, consumers used the Internet to simply expend content: they read it, they watched it, and they used it to buy products and services. Increasingly, however, consumers are utilizing platforms-such as content sharing sites, blogs, social networking, and wikis-to create, modify, share, and discuss Internet content. This represents the social media phenomenon, which can now significantly impact a firm's reputation, sales, and even survival. Yet, many executives eschew or ignore this form of media because they don't understand what it is, the various forms it can take, and how to engage with it and learn. In response, we present a framework that defines social media by using seven functional building blocks: identity, presence, relationships, conversations, groups, reputations, and sharing. As different social media activities are defined by the extent to which they focus on some or all of these blocks, we explain the implications that each block can have for how firms should engage with social media. To conclude, we present a number of recommendations regarding how firms should develop strategies for monitoring, understanding, and responding to different social media activities.