Big data and analytics

Staying committed on net-zero goals is crucial as companies navigate pressure from the Trump administration and difficult economic conditions.

The business case for AI is realized when the application is scaled. Use this checklist to ensure the transition from a successful use case to a transformative project.

Vinted founder Milda Mitkute shares how she turned a wardrobe cleanout into Lithuania’s first tech unicorn and why responsible growth matters.

As organizations become increasingly complex, fast paced, and interconnected, one of the key skills that will set leaders apart will be how they show up and communicate.

The case examines how a New York-based 10-year-old start-up, Lemonade Inc., successfully disrupted the insurance industry. Powered by artificial intelligence, Lemonade's mobile app replaced brokers and bureaucracy with bots and machine learning. The combination of simple product, no jargon, zero paperwork and an all-digital engagement allowed Lemonade to collapse costs, not at the expense of customer experience but to delight young customers with "instant everything" – from buying insurance in 90 seconds to getting claims paid in 3 seconds. Lemonade's notable milestones include surpassing $1 billion in in-force premiums in March 2025, a net loss ratio improvement from 97% in 2022 to 75% in 2025, and its first full year of positive adjusted free cash flow in 2024. Despite strong top-line growth, the company was yet to turn a profit, and its stock performance had been rocky. Lemonade posted a $202.2 million net loss in 2024, and its market capitalization stood at $4.2 billion in August 2025, significantly below its $9.8 billion peak in January 2021. Looking ahead, Lemonade aimed to increase in-force premiums tenfold, to $10 billion, by aggressively acquiring customers without significantly raising costs. As the stock regained market attention, bullish analysts highlighted ongoing progress toward profitability and improving loss ratios, whereas bearish analysts questioned the fundamentals behind the highly positive narrative presented by CEO Daniel Schreiber. A key question was whether the company could sustain its data- and AI-enabled competitive advantage or whether incumbents with deep pockets and growing technological investments would catch up. Against a backdrop of geopolitical tensions, uncertain macroeconomic conditions and increased competition, should institutional investors continue to invest in Lemonade or not?

Leadership is no longer just about directing tasks or achieving short-term goals. It is about navigating complexity, fostering growth, and addressing the human dimension of work in an era of constant change. Today’s leaders are expected to balance...

IMD’s AI Maturity Index shows how leading global companies advance their AI capabilities, revealing what it takes to move from pilot to implementation at scale.

Discover the 2025 Future Readiness Indicator revealing how tech, pharma, and fashion companies thrive amid AI disruption and geopolitical shocks.

Longevity was once seen by traditionalists as a proxy for good leadership, but successive generations attach less value to length of time served. As with anything, there are benefits and disadvantages. Here are the pros and cons of longevity to co...

This technical note presents a comprehensive framework for achieving adaptive advantage, which is the ability to consistently evolve at a speed that surpasses environmental and competitive change. In today's rapidly changing business environment, characterized by technological advancement, AI disruption, geopolitical turbulence and climate shifts, organizations must adapt continuously rather than through periodic transformations. The note identifies seven essential elements that form an integrated system for adaptive advantage: capable growth-minded people; psychological safety and trust; small, semi-autonomous, cross-functional teams; clear mission ownership with outcome accountability; distributed decision-making authority; external and internal sensing with transparency; and lightweight coordination mechanisms. These elements are organized into three categories: foundation (people and culture prerequisites), operating model (how work gets done flexibly), and enabling systems (how information and coordination support adaptability). Through systematic analysis of six popular organizational models (Military Mission Command, Lean Startup, Agile/Scrum, DevOps, Team of Teams and Teal Organizations), the note reveals why existing frameworks fall short: Most address only three to five elements while leaving significant gaps, and organizations often implement them superficially without the deeper cultural foundations that make them work. The note explores the leadership and talent transformations required for implementation, emphasizing the shift from commanding to enabling leadership approaches. It also demonstrates why this framework is critical for successful AI integration, as adaptive organizations can evolve into human–AI hybrids that leverage the best of both intelligences. The note concludes with practical guidance for assessing organizational adaptive readiness and implementing the framework through a foundation-first approach.