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2024 Was a Bad Year for Sustainability
The year 2024 was a challenging year for sustainability, from climate issues to inequality. Three top concerns include elections and political turmoil that threaten progress, companies retreating or staying silent on DEI and ESG goals, and the rise of sustainability reporting that’s (temporarily) taking up companies’ time. Other issues from the past year include the clean economy hitting tipping points, AI’s growth threatening decarbonization, heavy industry making some progress, and the beginning of a crackdown on “greenwashing.”
Research: Why Forming Diverse Teams Is Harder in Uncertain Times
Widespread global uncertainty in the form of the COVID-19 pandemic, ongoing wars, social uprisings, and rising inflation have led individuals to feel less of a sense of personal control. New research finds that this lack of control can drive employees to seek similarity in coworkers, forming homogenous teams that stifle diversity and innovation. Research involving over 90,000 participants across multiple studies revealed that individuals with reduced control gravitate toward those similar in race, religion, or values, reinforcing predictability but fostering segregation and limiting collaboration. Leaders can mitigate this effect by taking the following steps: 1) Foster psychological safety, 2) establish predictable work routines, 3) encourage cross-functional teams, 4) develop responsive feedback systems, and 5) cultivate individual autonomy.
HBR’s Most Popular Podcast Episodes of 2024
All of us are on a continuous journey of learning and growth, and the change of the calendar year offers a chance to reflect. Some of the HBR podcast episodes that have resonated most with listeners in 2024 can help you gear up and get excited for whatever next step may be. They cover topics such as artificial intelligence skills, assertiveness and warmth in the workplace, balancing privacy and public safety, setting boundaries, capturing value, effective communication, and rising from middle to senior management.
Digital Twins Aren’t Just for Big Businesses
Digital twins enable businesses to repeatedly simulate and optimize complex multivariable problems, cutting the learning costs that come with experimenting in the physical world. Once the exclusive province of big business, small and medium enterprises (SMEs) can now use AI to advanced digital twins that enable them to repeatedly simulate and optimize complex multivariable problems. Creating these twins is a five-step process that involves: Setting a clear business objective; drawing up a clear flowchart of the process you’re twinning; identifying and structuring the data you’ll need; building the digital model of that flowchart; then testing, implementing, and iterating the model.
Why Your Finance Team Should Help Make Big AI Decisions
The companies that succeed with AI aren’t necessarily those with the most advanced models or the largest data sets — they’re the ones that bring together diverse expertise to make the smartest decisions. Finance, with its ability to ascertain value, ensure accountability, and provide an objective perspective, plays an indispensable role in making AI investments truly pay off. By involving finance teams early and often, companies can transform AI from an exciting possibility into a reliable growth engine — one that delivers both top-line expansion and operational excellence.
Is AI the Right Tool to Solve That Problem?
While AI has the potential to solve major problems, organizations embarking on such journeys of often encounter obstacles. They include a dearth of high-quality data; too many possible solutions; the lack of a clear, measurable objective; and difficulty in identifying whether a proposed solutions is “good.” In tackling these issues, Google DeepMind, Alphabet’s AI lab that is striving to solve extremely challenging real-world problems, has come up with solutions that can benefit others. And it also offers guidance in choosing which opportunities to pursue after potential projects have overcome those hurdles.
Contract Negotiations Should Be Collaborative, Not Adversarial
Traditional approaches to contract negotiation, heavily focused on risk mitigation, are increasingly misaligned with business needs. New research shows that while companies spend considerable time haggling over legal protections, the most common sources of disagreement during contract execution are practical issues like pricing, scope, and delivery. The path forward requires a fundamental shift in how we approach negotiations. This isn’t about abandoning risk management — it’s about recognizing that the best risk management strategy is often creating clear, practical agreements focused on mutual success. Organizations that make this shift are seeing tangible benefits: faster negotiations, better acceptance rates, and most importantly, more successful business relationships.
How to Create Products That Grow with Their Users
Planned obsolescence has generated reliable revenue streams, but at a devastating cost: mounting environmental waste, eroding customer trust, and missed opportunities for deeper customer relationships. As sustainability concerns grow and customer loyalty becomes increasingly vital, many executives are asking: How do we break free from planned obsolescence and design products that grow? The answer lies in understanding how innovative companies are already making this transition. Adobe’s Project Primrose offers a masterclass in PTG development, showing how organizations can evolve from disposable products to adaptive solutions that grow with customer needs.
Why Mentoring Programs Fail — and How to Make Them Worthwhile
Despite the fact that 98% of Fortune 500 companies have mentoring programs, only 37% of professionals actually benefit from them. This disconnect is exacerbating retention issues. So, why are mentoring programs failing to deliver on their promise? The issue lies not with mentoring itself but in the underutilization and ineffective reach of many mentoring programs. Programs are frequently confined to a small group of employees or lack the necessary communication and visibility to attract participation. As a result, many employees are unaware of or uninterested in participating in mentoring opportunities. Moreover, potential mentors might be too overwhelmed with their own workloads to commit to meaningful mentorship, leading to a cycle of under-engagement. Fortunately, there are ways to transform your organization’s mentoring program into a powerful tool for employee retention. It involves strategically communicating effectively, leveraging storytelling, engaging senior leaders, and expanding access.
6 Questions to Find Out How Your Employees Are Really Doing
Do you know how your employees truly feel about their roles, work, and relationships? Asking the right questions in focused one-on-one settings is key to making sure you’re in tune with your people. This article outlines six questions to try to move beyond surface-level interactions. The more you recognize your team members as people with ambitions and dreams — not just cogs in the machine — the better you’ll understand how they feel about their jobs and futures.
Where Humans Still Have the Edge on AI
Gen AI has several attributes that humans lack. It’s always on. It boasts encyclopedic knowledge. It generates output instantly. It can scale endlessly. This new era of AI can feel intimidating for the limited, human life forms that created it. Humans now need to look harder to see where our unique value still lies. What tasks or skills might be difficult for AI for the foreseeable future? What moat can humans continue to own and defend? In this article, the author describes four strongholds for humans, and the associated human skills that remain valuable — for now.
A Guide to Managing Interconnected AI Systems
Increasingly, AI systems are interconnected, which is generating new complexities and risks. Managing these ecosystems effectively requires comprehensive training, designing technological infrastructures and processes so they foster collaboration, and robust governance frameworks. Examples from healthcare, financial services, and legal profession illustrate the challenges and ways to overcome them.
An Early-Warning System Will Make Your Supply Chain More Resilient
The fragility of supply chains has been evident as companies have faced a series of shocks in recent years. Many companies have taken actions to improve their resilience, including building inventory buffers, dual-sourcing, and re-shoring. Even so, fewer than a third of leaders surveyed in 2023 said their companies were fully prepared for a disruption; a quarter admitted to being underprepared. One practical approach to building resilience is to design an early-warning system. Companies can start by creating an integrated and centralized data storage system with both quantitative and qualitative data. Then, they can use AI to identify anomalies in the data that serve as alarms. Lastly, companies will need to rewrite risk-management playbooks to make clear how to identify where the alarm is coming from, what is to be done, by whom, and in what order.
4 Listening Skills Leaders Need to Master
Leaders who listen well create company cultures where people feel heard, valued, and engaged. In addition, employees who experience high-quality listening report greater levels of job satisfaction and psychological safety. If you’re interested in sharpening your listening skills, try using these four techniques: (1) Listen until the end — don’t jump in or interrupt the speaker; (2) Listen to summarize the problem, not to solve it; (3) Balance your focus between building a connection with the speaker and understanding the issue they’re presenting you with; (4) Listen for values — whether someone is ranting about something small or sharing something emotional or complex, it’s an opportunity for you to learn more about what’s important to them.
How Gen AI and Analytical AI Differ — and When to Use Each
Organizations that have recently discovered generative AI are at risk of overlooking an older and better-established form of AI, which the authors call “analytical AI.” This form of AI is by no means obsolete and is still an important resource for the great majority of companies. While a few applications of AI employ both analytical and generative AI, the two AI approaches are largely separate. To make decisions about the relative importance and value of generative AI and analytical AI, organizations must first understand the differences between the two technologies, and the different benefits and risks associated with each. They can then make decisions about which to prioritize under what circumstances based on their strategies, business models, risk tolerance, and other situations. Without an understanding of their differences, however, organizations risk under-utilizing one or both types to transform their businesses.
Joining a Professional Group Where Everyone Already Knows Each Other
Even for experienced professionals, it can feel intimidating to join a new professional group or association — especially if you discover that you’re practically the only new member and everyone else already seems to know each other. How can you break in and build relationships when no one else seems to feel the need? Here are four strategies to help you feel more comfortable, so you can stick around long enough to enjoy yourself and the benefits of membership: 1) Ask for networking help. In most cases, you’ll know at least one person in the group who can help you break in. 2) Commit to understanding the dynamics of the group. 3) Overindex during your first year. Because you’ll feel like a stranger at first (and you are) the antidote is to make yourself a “regular” as quickly as possible. 4) Double-check your assumptions.
Continuing the Work of DEI, No Matter What Your Company Calls It
While DEI has faced significant backlash in the last year, companies across industries are still looking for ways to build healthy, inclusive workplace cultures where everyone can do their best work. New data at shows that even during this year of backlash, companies continued to make progress on many of their DEI initiatives. There are three ways companies should consider shifting their approach to DEI, both to be responsive to the current moment and to achieve greater impact: resetting the narrative, using data more effectively, and moving from siloed efforts to an embedded organizational focus on creating cultures that work for everyone.
What Is Agentic AI, and How Will It Change Work?
From the early days of mechanical automatons to more recent conversational bots, scientists and engineers have dreamed of a future where AI systems can work and act intelligently and independently. Recent advances in agentic AI bring that autonomous future a step closer to reality. With their supercharged reasoning and execution capabilities, agentic AI systems promise to transform many aspects of human-machine collaboration. The agentic AI prize could be great, with the promise of greater productivity, innovation and insights for the human workforce. But so, too, are the risks: the potential for bias, mistakes, and inappropriate use. Early action by business and government leaders now will help set the right course for agentic AI development, so that its benefits can be achieved safely and fairly.
How AMD’s Lisa Su Is Thinking About AI
In a conversation with HBR editor-in-chief Adi Ignatius, Lisa Su, CEO of leading semiconductor company AMD, discusses its evolution toward high-performance and adaptive computing, the future of AI use in sectors from healthcare to tech to personal productivity, and the importance of responsible risk-taking. She advocates for fast experimentation and implementation while ensuring safety through initiatives like AMD’s Responsible AI Council, active learning within the organization and among industry peers and partners, and the hiring of diverse talent to drive innovation.
The UnitedHealthcare CEO Shooting Should Be a Turning Point for Corporate America
The murder of Brian Thompson — and the public’s reaction to it — shows that frustration with corporations has reached a fever pitch. We seem to have moved from a world of “I don’t trust you” to “I hate you,” and, many Americans feel a great antipathy toward capitalism and capitalists. This is due, in part, to the failure of business, at large, to deliver value to customers, employees, and communities (as well as shareholders) simultaneously. Corporate leaders should step back in this moment and reflect on what role their organizations play in society and what trade-offs they’ll need to make to ensure that their businesses work for everyone, not just investors. Three case studies show that such strategic, socially responsible thinking pays dividends.
6 Lessons from Companies That Shut Down Their Business in Russia
Increasingly, companies are being pressured to decouple from regions that customers, employees, politicians, advocacy groups, and even leaders deem politically fraught. This can pose a dilemma for executives, as research both shows that fast decision-making is vital, but some circumstances require deliberation and care. Interviews with 16 leaders from 10 companies who faced pressure to exit Russia after the 2022 invasion of Ukraine offer six lessons for organizations facing similar situations: 1. Public opinion expects immediate and binary decisions. 2. For consumer brands, speed may trump deliberation. 3. B2B firms may have more time to calculate. 4. Even 1% of sales can be 100% of a company’s reputation with employees. 5. Business and brand value initially took a hit, but CEOs still feel good about having done the right thing. 6. Crisis offers an opportunity to rethink and restructure.
Research: Why Your Board Should Include a Long-Tenured Director
The presence of long-tenured independent directors on corporate boards can be an effective governance mechanism that leads to greater performance and reduced exposure to outside risks. However, there is a need for balance. Boards should not have too many long-tenured directors, otherwise they risk entrenchment. Maintaining one or two is crucial for providing stability, knowledge, and credible oversight. Long-tenured directors should be viewed as part of a co-evolutionary process with the firm, rather than subject to strict tenure limits.
It’s Time for CFOs to Rethink Scenario Planning
As companies navigate today’s complex business and geopolitical landscape, CFOs have seen risk management rise to the top of their priorities. They’re increasingly using scenario planning as a key tool to manage risk and strategically unlock new value-creation opportunities. This involves three approaches: 1) Being rigorous and cross-functional, integrating scenario planning into the company’s strategic framework; 2) Being outward looking and externally informed by staying ahead of the curve on regulatory updates and policy trends; and 3) Continually refreshing and monitoring scenarios, incorporating new and emerging data, and translating insights into compelling stories that help stakeholders grasp not only the financial implications of scenarios, but also the strategic rationale behind key decisions.
The Irreplaceable Value of Human Decision-Making in the Age of AI
The rise of AI presents an opportunity for humans to step up to the challenge of refining, emphasizing, and applying our own human strengths to differentiate corporate decision-making. However, human capabilities, like making moral judgments, and using imagination or intuition, are often untrained, impulsive, or implicit. Thus, to distinguish and elevate their decision-making processes, organizations need to actively codify and foster the requisite human decision-making skills. This article outline five imperatives towards this end.
Is Your Company’s Problem Complicated? Or Complex?
Complicated problems, which can be solved with systematic approaches, are different from complex problems, which require adaptive strategies and continuous learning. Many leaders conflate the two types, have more experience with complicated problems, and therefore may struggle to manage complex situations. These six steps can help.
AI Thinks Differently Than People Do. Here’s Why That Matters.
Generative AI isn’t the strategic oracle many say it is. Like any other form of AI, it is a mirror that reflects patterns, trends, and decisions of the past. It cannot reliably break new ground or generate truly novel solutions given that it relies on pre-existing data and learned probabilities. But there are three ways leaders can leverage generative AI to support forward-looking decision-making that steer organizations toward growth and innovation: as a sounding board, to explore scenarios, and as an ideation tool. To effectively employ any AI in strategic decision-making, it is vitally important for managers and leaders to understand the limitations that are inherent in the way it generates output.
Manage Capital Investments Like a Supply Chain
With generative AI, the rewiring of global supply chains, and investments in clean energy and associated technologies, business is on the cusp of capital investments the likes we’ve never before seen. Traditionally, organizations see a capital project as a single behemoth, broken down into a number of constituent components that ultimately must come together at the end for the project to succeed. Instead, organizations should think about a capital project as an integrated, end-to-end supply chain, where “demand” (i.e., what the project is meant to deliver) informs the supply (everything upstream the organization must orchestrate to fulfill demand). Supply chains and operations functions today deliver on trillions of dollars every week with limited failures. The reason is, the techniques companies use to manage and operate supply chains have been enhanced, refined, and continuously improved over a long period of time. Applying these techniques to the new breed of capital projects can significantly increase these projects’ prospects for success — and generate the return on investment companies are looking for.
3 Reasons Change Initiatives Fail — and How to Ensure Yours Succeeds
It’s a well-known problem: Organizations launch well-planned change initiatives with the best of intentions but then struggle to achieve their goals. To understand why this happens so often, the authors conducted a large-scale study that provided deep insights into the underlying challenges that organizations face when embarking on transformation initiatives. Building on those insights, they designed a five-step process to drive successful transformation initiatives, and in this article they discuss the process and offer advice on how to implement it.