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Companies that encourage teams to move fast and experiment must take care that new initiatives get sufficient oversight and remain aligned with the overall corporate strategy. Some have established a portfolio team made up of top executives to monitor and adjust the mix of fledgling projects that might fall outside of existing corporate structures like R&D or business lines.

Generative AI applications like ChatGPT demonstrate how large language models can quickly and cheaply perform some tasks that only humans could do before. Organizations might see an opportunity to use this technology to automate knowledge work, but implementing it comes with practical challenges that still require skilled employees involvement. This suggests that while newer AI tools might be better equipped to handle some tasks, they are unlikely to reshape organizations reliance on humans.

This case focuses on the challenges of the public provision of high-quality water in Hungary, a high-income, former Eastern Bloc country that has been a member of the European Union since 2004. It struggles with chronic groundwater arsenic contamination. At the Darden School of Business, this case is taught in the second-year elective, "Global Economics of Water," in a public policy module that covers two topics: supplying water for the public and water markets. It is taught alongside "Deadly Wells in Bangladesh" (UVA-GEM-0158), to compare and contrast Hungary's arsenic contamination issues and solutions to those of Bangladesh, a lower-middle-income country and one of the most populated in the world.

This case focuses on the efforts of Bavarian Nordic A/S, a Danish pharmaceutical company, to create a new COVID-19 vaccine. Their vaccine is based on a newer technology and has the potential to provide longer-lasting protection than the currently dominant BioNTech/Pfizer and Moderna vaccines. However, the project also faces obstacles related to uncertainty of vaccine efficacy, financing, product positioning, distribution, and access to production infrastructure. Indeed, given the head start of the incumbents' vaccines, the dominance in this business of large pharmaceutical companies, and the multitude of other COVID-19 vaccines, some wonder whether the company should be going down this path at all.

The author, Honeywell's CEO until June 2023, writes: "There's zero chance that we would have made it through Covid, inflation, the upswing in geopolitical risk-all the challenges we faced over the past several years-had we not developed a transparent and coherent digital strategy." In this article he describes the company's multifaceted transformation from a diversified industrial conglomerate into an integrated company. Internally, the goal was to improve productivity, transparency, and agility with centralized data to guide business decisions. Externally, it was to harness all the information generated by systems Honeywell sold in order to offer clients a whole new kind of value: a means to track emissions, save energy, improve safety, and more. First the company had to simplify and reorganize its infrastructure, going from 150-plus enterprise resource planning systems (ERPs) to 10, from 1,700 websites to fewer than 100, and from 2,700 applications to fewer than 1,000. Next it had to define master data for products, employees, customers, and many other things. Then it developed a strategy for putting all that data to work. By running the monthly meetings and the operating reviews himself, Adamczyk sent a message to everyone: "I care about this transformation personally, and we're committed to this path."

When it launched GPT-4, in March 2023, OpenAI touted its superiority to its already impressive predecessor, saying the new version was better in terms of accuracy, reasoning ability, and test scores-all of which are AI-performance metrics that have been used for some time. However, most striking was OpenAI's characterization of GPT-4 as "more aligned"-perhaps the first time that an AI product or service has been marketed in terms of its alignment with human values. In this article a team of five experts offer a framework for thinking through the development challenges of creating AI-enabled products and services that are safe to use and robustly aligned with generally accepted and company-specific values. The challenges fall into five categories, corresponding to the key stages in a typical innovation process from design to development, deployment, and usage monitoring. For each set of challenges, the authors present an overview of the frameworks, practices, and tools that executives can leverage to face those challenges.

Businesses today face serious talent gaps. The share of companies reporting staffing shortages is at an all-time high: 77%. Last fall the United States had 9.5 million unfilled jobs but only 6.5 million unemployed workers. Many open positions demand sophisticated know-how that cannot be supplied by AI or by training new hires. Every day 10,000 Americans reach the traditional retirement age of 65, which exacerbates the problem. Critical skills, experience, and connections can walk out the door with each retirement. The good news is that many older employees want to keep working; in fact, nearly 60% say they're receptive to the idea of working during retirement. It's time for companies to stop overlooking this large, valuable labor pool. Employers need to shed their misconceptions about older workers and take measures to make the most of their experience, creating phased retirement programs, offering refresher courses, and recruiting through retiree networks, among other strategies. Older employees' knowledge can be leveraged through coaching roles, on multigenerational teams, and in institutional systems. But companies will have to work to engage their seasoned staffers, offering them flexibility, the right benefits, and opportunities for connection.

Many companies overestimate customers' appetite for sustainable products, flooding the market with offerings that don't sell. The reality is, social and environmental benefits have less impact on purchasing decisions than basic product attributes do. Consumers buy products to get specific jobs done, and only after they find something that will do that will they look for a product that provides some social or environmental advantage. Of course, that's only if they value sustainability. Not everyone does, and marketers need to recognize that. Some customers (greens) place a premium on it, some (blues) value it only moderately, and some (grays) don't care about it and view it skeptically. The three segments cannot all be approached in the same way. How sustainable product benefits interact with traditional benefits is also critical: They can have no impact on a product's performance (independence), diminish it (dissonance), or enhance it (resonance). Marketers need to follow different playbooks for independent, dissonant, and resonant products, tailoring their approaches to green, blue, and gray customers with each.

Despite a multitude of initiatives in cross-sector collaboration and open innovation, businesses still struggle to support the development of game-changing ideas. The authors argue that the solution to this problem starts by recognizing an important truth: Innovation is about more than an idea-it is a long, collaborative journey. Innovation is more likely to succeed when it is a curated process in which an intermediary takes responsibility for sparking and sustaining collaboration among the people involved. In this article, the authors demonstrate how intermediaries can support collaboration throughout the entire innovation journey. First, they provide opportunities for innovators to make connections. They don't simply bring people together; they carefully select participants and curate the experience to generate the best results. Second, they help innovators develop relationships, using structured follow-ups and offering holistic mentoring. And third, they help entrepreneurs sustain their relationships and manage the team over time as the collaborations evolve and team members change.

Until recently most incumbent industrial companies didn't use highly advanced software in their products. But now the sector's leaders have begun applying generative AI and machine learning to all kinds of data-including text, 3D images, video, and sound-to create complex, innovative designs and solve customer problems with unprecedented speed. Success involves much more than installing computers in products, however. It requires fusion strategies, which join what manufacturers do best-creating physical products-with what digital firms do best: mining giant data sets for critical insights. There are four kinds of fusion strategies: Fusion products, like smart glass, are designed from scratch to collect and leverage information on product use in real time. Fusion services, like Rolls-Royce's service for increasing the fuel efficiency of aircraft, deliver immediate customized recommendations from AI. Fusion systems, like Honeywell's for building management, integrate machines from multiple suppliers in ways that enhance them all. And fusion solutions, such as Deere's for increasing yields for farmers, combine products, services, and systems with partner companies' innovations in ways that greatly improve customers' performance.

Executives need guidance about managing their organizations' engagement with societal issues-including hot-button topics such as gender, climate, and racial discrimination. Success in this realm does not mean avoiding public controversy or achieving unanimous support among key stakeholders, the authors write. Rather, it results from adhering to certain processes and strategies, which they have derived from recent global survey research along with examples from managerial best practice. They offer an approach that is anchored in data but sensitive to values and context. It can be helpful in figuring out which issues to address and how; in ameliorating disappointment among stakeholders; and in managing any potential blowback. Data can tell you what your various stakeholders care about, they write, but judgment is necessary to act in careful consideration of conflicting preferences while being consistent with your company's values.

Health systems are struggling to address the many shortcomings of health care delivery: rapidly growing costs, inconsistent quality, and inadequate and unequal access to primary and other types of care. However, if retailers and health systems were to form strong partnerships, they could play a major role in addressing these megachallenges. While some partnerships do exist, they are rare and have only scratched the surface of their potential. Rather than focusing on the direct-to-consumer model that retailers have largely employed, the partnerships should offer much broader care. Drawing on real-world examples, the authors outline four key actions that retailers and health systems should take: (1) They must move beyond convenience to offer comprehensive care. (2) They should move care from clinics into the home. (3) They should leverage data to improve clinical care and the customer experience. And (4) they should change how-and by whom-health care work is done. Implementing these four actions would generate improvements that would benefit not just patients but also the organizations that pay for their health care.

Businesses need better planning to make their supply chains more agile and resilient. After explaining the shortcomings of traditional planning systems, the authors describe their new approach, optimal machine learning (OML), which has proved effective in a range of industries. A central feature is its decision-support engine that can process a vast amount of historical and current supply-and-demand data, take into account a company's priorities, and rapidly produce recommendations for ideal production quantities, shipping arrangements, and so on. The authors explain the underpinnings of OML and provide concrete examples of how two large companies implemented it and improved their supply chains' performance.

During his former career as a kidnapping and extortion negotiator, the author handled sensitive cases all over the world. Through his experiences, observations, and conversations with other experts in the field, he developed a deep understanding of what works and what doesn't in high-stakes negotiations. Now he advises executives and corporations about what he calls the level-five mindset, which involves deep listening to better understand and interpret a counterpart's self-perception and perspective. He offers eight tools to both ensure and demonstrate that mindset: minimal encouragers, open questions, reflecting back, emotional labeling, paraphrasing, "I" statements, effective pauses, and summarizing. Using them, he writes, will "boost your capacity for empathy, your ability to find common ground, and your chances of gaining your counterpart's cooperation."

Paulo Ferreira, the president of Luna Brazil, has an ambitious plan to turn around the dismal performance of the plant he oversees in Campinas. The wrinkle is, he needs the buy-in of the powerful local union, which is still smarting from a 10-year-old labor conflict and lately has begun to step up its demands and picket outside the factory. Headquarters, running out of patience with the dispute, wants Paulo to consider converting the plant to a distribution center. But that would mean hundreds of layoffs, which would decimate the local community that Paolo loves.

Six new books come down on both sides of the debate: The Alternative, by Nick Romeo; The Road to Freedom, by Joseph E. Stiglitz; Capitalism and Crises, by Colin Mayer; Climate Capitalism, by Akshat Rathi; Venture Meets Mission, by Arun Gupta, Gerard George, and Thomas J. Fewer; and Slow Down, by Kōhei Saitō.

The renowned soprano talks about developing confidence, overcoming stage fright, and juggling five jobs at once.

Paulo Ferreira, the president of Luna Brazil, has an ambitious plan to turn around the dismal performance of the plant he oversees in Campinas. The wrinkle is, he needs the buy-in of the powerful local union, which is still smarting from a 10-year-old labor conflict and lately has begun to step up its demands and picket outside the factory. Headquarters, running out of patience with the dispute, wants Paulo to consider converting the plant to a distribution center. But that would mean hundreds of layoffs, which would decimate the local community that Paolo loves.

Paulo Ferreira, the president of Luna Brazil, has an ambitious plan to turn around the dismal performance of the plant he oversees in Campinas. The wrinkle is, he needs the buy-in of the powerful local union, which is still smarting from a 10-year-old labor conflict and lately has begun to step up its demands and picket outside the factory. Headquarters, running out of patience with the dispute, wants Paulo to consider converting the plant to a distribution center. But that would mean hundreds of layoffs, which would decimate the local community that Paolo loves.

In 2023, Darktrace CEO Poppy Gustafsson was contemplating her growth strategy at a leading U.K.-based cybersecurity venture, launched in 2013 by a group of anti-terror cyber specialists, University of Cambridge mathematicians, and artificial intelligence (AI) experts. Darktrace was also one of the few technology companies built around AI from the start prior to Generative AI, and it offered AI-powered solutions to protect customers from a variety of complex online threats. Two years earlier, Darktrace had gone public on the London Stock Exchange with a market capitalization of $2.4 billion. In the wake of the IPO, in 2022, both the chief marketing officer and chief revenue officer had approached Gustafsson to tell her they wanted to step down from their roles. They were cofounders, and Gustafsson had worked with them from the start. Gustafsson and her team were weighing the decision of whether to bring on external hires or to promote from within for the CRO and CMO roles. The goal was to scale Darktrace from $500 million in revenues to $1 billion. The decision to recruit externally had significant investment implications, given fears of recession, high inflation, and layoffs faced by many companies in the second half of 2022. Recruiting talent from the outside would change the organization's hiring model, compensation structure, and incentives. But there were other concerns. Would newly recruited talent from the outside mesh with the culture and organization that Gustafsson and her cofounders had built at the company's U.K. headquarters? She knew she would have to manage sensitivities on both sides. What was the best way to ensure a smooth transition, and what qualities should she be looking for in the two new C-level executives? Was this a necessary step to realize her ambitions for growth?