The research involved interviews with 39 executives across 10 countries and diverse industries, plus an online workshop with 36 enterprise data leaders to explore how digital technologies address sustainability challenges. Additionally, surveys of 360 Swiss manufacturing employees revealed approaches to energy efficiency. Rising global energy costs, heightened by geopolitical events like conflicts involving the U.S., Israel, and Iran, press companies financially, especially in energy-intensive sectors such as cement, chemicals, and metals. These industries, along with manufacturers relying on complex supply chains, face profit margin pressures due to increased fuel and power expenses.

Businesses are expanding efforts to enhance energy efficiency not only to support sustainability but also to achieve tangible cost savings, bolster resilience, and enable growth. Some have cut energy consumption by up to half at certain facilities and improved process efficiency by 10-20%. Success stems from comprehensive strategies integrating digital system upgrades and clear executive accountability with performance targets.

Three key strategies emerged: first, investing in data collection and analysis to enable real-time energy management through sensors, dashboards, and centralized platforms; second, redesigning operations to optimize energy use, reduce waste, and deploy AI for continuous improvement; and third, creating products and services that help customers meet energy efficiency goals.

Companies like Clariant utilize digital platforms and AI to monitor and reduce energy use across global sites, achieving significant savings. Similarly, Georg Fischer combines energy-saving technologies, renewable energy, and circular economy practices to lower fossil fuel dependence and emissions. Producers like ABB and DMG Mori offer energy-efficient products and data-driven services that help customers reduce consumption and improve operational efficiency.

The findings highlight a reinforcing cycle where visibility into energy consumption drives operational redesigns, funding further innovations for customers. Organizations that prioritize energy efficiency with clear goals position themselves advantageously amid volatile fossil fuel markets.

At Alturas Capital Partners, advances in generative AI have enabled in-house legal teams to handle lease work traditionally outsourced to outside counsel, delivering significant cost savings and faster turnaround times. This shift threatens some external providers with irrelevance as AI reduces their role, reshaping how firms define their services. While some firms expand their offerings, others lose business to clients adopting AI internally. The pressure on pricing is evident, with major banks recently urging law firms to reduce fees due to AI efficiencies.

Generative AI is lowering costs for producing legal documents, market insights, creative assets, and software, enabling in-house teams to replicate many functions once outsourced. To stay relevant, service providers must not rely solely on expertise but also compete on production cost and ease of delivery.

Providers should focus on three key strategies:

1. Improve Unit Economics: By investing in scalable, automated systems and leveraging proprietary data, firms can produce outputs more cost-effectively than clients can in-house. WPP exemplifies this with its agentic marketing platform and self-serve options that combine data, expertise, and AI tools.

2. Simplify Procurement: Reducing the friction in purchasing services by integrating AI agents that fulfill requests directly within clients’ existing tools makes outsourcing more attractive. Moody’s and law firms like A&O Shearman demonstrate this approach by embedding AI-driven services into clients' workflows.

3. Manage the Operational Burden: Taking on quality control, compliance, and ongoing maintenance costs that clients face if they internalize work strengthens the provider’s value proposition. Thomson Reuters’ CoCounsel Legal product is an example, offering robust, legally vetted AI research that firms cannot easily replicate internally.

Service providers must critically analyze which deliverables are vulnerable to in-house AI production and develop cost-effective, easy-to-access, and low-maintenance offerings. Success lies in making outsourcing cheaper, more convenient, and operationally less burdensome than building internal AI capabilities. While AI challenges traditional expertise, it also raises the bar for providers to innovate and integrate technology with human skills to stay competitive.

For years, social media giants faced criticism for promoting harmful content to drive engagement. However, a recent Los Angeles court ruling held Meta and Google accountable not just for content, but for the addictive design choices underlying their products. This highlights a critical issue: traditional user-centered design methods like design thinking, while popular and effective in meeting user needs, can inadvertently cause harm by overlooking ethical concerns.

Design thinking involves understanding user needs and iterative testing, but our research with 27 senior leaders from tech, pharma, and design firms reveals recurring blind spots. For example, addictive features and polarizing content can emerge despite following best practices. Juul's rise in e-cigarettes shows how design focused on user appeal without ethical foresight can lead to serious societal harm.

Four key challenges arise from a user-centered focus: ignoring environmental impacts, neglecting stakeholders beyond primary users including vulnerable or malicious users, sacrificing thoroughness for speed, and failing to anticipate harm at scale. Governing these challenges requires leadership to embed ethics alongside user needs by starting with clear purpose, accounting for broader systems influencing design, and pausing to assess risks before scaling.

Ethical innovation demands inclusive stakeholder consideration, alignment of incentives with societal good, encouraging designer voices, and leveraging tools like AI to simulate risks. While diligence may increase costs upfront, it is essential to prevent costly consequences such as legal liabilities and reputational damage. The question companies face today is not if they can afford to be ethical, but if they can afford not to be.

In today's rapidly evolving marketing landscape shaped by AI and media fragmentation, CMOs face critical challenges and opportunities. They must elevate marketing to an executive growth function, seamlessly integrate AI to reinvent workflows, and adapt talent strategies to focus on skills like creativity and critical thinking. Navigating a highly personalized, fractured media environment demands innovative approaches to reach consumers and measure impact. Marketing leaders who embrace change proactively will redefine their role and drive enterprise-wide growth, positioning marketing not just as a cost center but as a strategic business driver for the future.

Corporate sustainability efforts frequently face significant challenges. Net-zero commitments are being quietly scaled back, regulatory pressures are easing in some regions, and shareholders increasingly demand clear business value. Sustainability leaders often find themselves defending their role instead of expanding it. This leads to a common tension: balancing profit with purpose.

Rather than outright failures, many sustainability transformations gradually lose their drive. Initial ambitious goals fade as everyday decisions increasingly mirror those made without sustainability in mind. This gradual weakening often goes unnoticed until much later.

Our research following six startups committed to sustainability or social impact revealed that the key factor differentiating success from failure was cognitive approach. Teams that saw profit and purpose as mutually exclusive tended to struggle or fail. Conversely, those that embraced the paradox of balancing both goals—maintaining a flexible, iterative approach—were more successful.

This mindset shapes early structural decisions, from target-setting to team composition, creating lasting impacts on the transformation’s path. Often, the dominant pragmatic voice in established companies pushes for strong business cases first, risking sidelining sustainability ambitions permanently.

To counteract this drift, transformation leaders should:

1. Build teams with diverse viewpoints to encourage productive tension.
2. Incorporate early reality checks through stakeholder feedback to avoid premature lock-in.
3. Start with simple, adaptable program designs before scaling complexity.

By fostering a culture that holds profit and purpose in creative tension, companies can navigate the pressures threatening sustainability initiatives and preserve their transformative edge.

Businesses are moving rapidly to adapt to change, yet B2B marketing tactics have largely stayed the same. While the shift to digital and data-driven targeting has increased precision, many marketers still cling to outdated ideas about how corporate buying works. Traditionally, it’s been assumed that B2B purchases are mostly logical, based on product features and price, ignoring the emotional and social influences that shape decisions. But our research reveals B2B buying is deeply emotional and influenced by unseen stakeholders beyond the primary buyer, such as executives or procurement staff, whose opinions can sway up to half of the decision. Brand reputation and cultural alignment between vendor and buyer company also play crucial roles. Buyers prefer defensible choices, favoring established brands that reduce risk. This means that brand marketing, which connects on values and identity, is as essential in B2B as in consumer markets. For B2B marketers, success depends on understanding these hidden influencers, the company culture, and the emotional context behind purchases—not just product specs or price. C-suite leaders must embrace brand-driven approaches to truly connect with today’s complex buyers and win deals.

A vice president of product opens her laptop to find the AI model her team spent weeks developing has been overtaken by a new, faster, and cheaper alternative. The CEO shares news about a competitor's similar move, and the team faces constant pressure to keep up. Unlike past disruptions, AI is relentless and self-accelerating, meaning there is no finish line—only continuous waves of innovation. The old playbook of moving fast to survive no longer suffices, as it risks exhausting organizations and their people. Instead, companies must adopt strategies to endure this steady-state disruption by building permanent AI teams, operating with dual tempos (fast and slow innovation cycles), and embedding continuous learning into everyday work. These approaches help shift the burden of change from individuals to organizational structures, preventing burnout and fostering sustainable adaptation. Leaders who embrace this mindset and restructure their organizations accordingly will thrive amid the ongoing AI revolution.

How do companies like Ørsted and Microsoft transform amidst disruptive market shifts? Both faced major industrial changes—Ørsted moving from fossil fuels to becoming a leader in offshore wind, and Microsoft pivoting from missed mobile opportunities to cloud and AI dominance. Their success lies in leveraging what we call "kernels of reinvention"—deep, transferable capabilities rooted in their original businesses but adaptable to new markets. These kernels, whether technical like Fujifilm’s chemistry or relational like Microsoft’s enterprise trust, must be deep, generative, defensible, and coherent. Reinvention involves diagnosing market disruptions, identifying these kernels, building new growth strategies around them, managing transitions carefully, and crafting a narrative that balances change with continuity. The key insight is that companies should not completely abandon their legacy but transform by carrying forward core strengths to remain relevant and competitive in a shifting landscape.

For the fifth consecutive year, MIT Sloan Management Review and Boston Consulting Group (BCG) have consulted a global panel of AI experts—including academics and industry leaders—to delve into the implementation of responsible AI across organizations worldwide. This year, the focus has been on the delicate balance between AI agent autonomy and accountability. While 72% of experts agree that treating AI agents as fully autonomous decision makers in governance is destined to fail, the discussion reveals complex nuances around the nature of autonomy. Experts note that AI agents are operationally autonomous, capable of independent technical action without continuous human oversight, but this autonomy does not extend to moral or legal accountability. AI systems cannot bear responsibility, own outcomes, or face legal consequences; such responsibilities must lie with humans and institutions behind them. Treating AI as autonomous risks creating an accountability void where organizations might shirk responsibility by blaming the AI. The panel emphasizes that governance should focus on the broader sociotechnical system, including developers, deployers, and users rather than the AI agent alone. Practical steps recommended include calibrating AI autonomy to the stakes involved, embedding limits into system design, assigning clear human accountability, governing the entire ecosystem, and fostering a culture where accountability is shared and transparent. This approach ensures ethical oversight and aligns AI operation with human values and legal frameworks.

Rob Dobi's article is based on a four-year ethnographic study of a professional services firm that attempted a major transformation to reverse declining performance but ultimately failed. The research involved extensive observation, interviews, and document analysis. It reveals how leadership anxiety, if unacknowledged and unmanaged, paralyzes organizations and leads to defensive behaviors that sustain the status quo rather than change. Anxiety among leaders manifests as fear about their competence and social expectations, creating a cycle of idealizing comforting visions, blaming others, engaging in empty rituals, and ultimately scapegoating. The study emphasizes that successful transformation requires leaders to recognize, share, and manage anxiety by cultivating courage to face worries, curiosity to seek feedback, and care to support others. The article counters the traditional view of leadership as flawless confidence and calls for a culture that humanizes anxiety and channels it toward adaptive change.