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Sure, strategy is challenging. It’s about making decisions in a constantly changing environment. But here’s the real problem: no matter how sophisticated your theories or how detailed your plans, reality always turns out to be a MF; the real world rarely aligns with your projections. According to a recent McKinsey survey (link below), only half of executives believe their companies effectively align budgets with corporate strategies. Despite the use of data analytics and scenario planning, many decisions still rely on

While AI promises to revolutionize every aspect of business, much of the current use merely scratches the surface. We see employees secretly using personal AI tools and teams automating minor tasks without strategy, all while leadership questions whether AI is just another passing trend. The reality is that organizations find themselves caught in a cycle of superficial implementation and underwhelming performance. The AI implementation dilemma Deciding where and how to implement AI in your organization is a complex challenge. With

The challenge in unlocking AI’s potential within your organization is not at all about adopting the latest technology; it’s about ensuring that every AI initiative aligns closely with your business objectives, and offers measurable returns on investment (ROI) or operational expenditure (OPEX) improvements. As AI continues to reshape industries, the difference between success and stagnation will be determined by whether you’re doing the right thing. From efficiency to value creation One of the most common pitfalls in AI implementation is

Recently, I heard someone mention the concept of so-so technology: disruption without delivering real improvements. This perfectly describes some of the AI innovations I see today. There’s a lot of focus on easy wins, leading to unfulfilling so-so technology solutions. Sure, things get automated, but are they better? Or even cheaper? The power of AI I think using AI should be about more than just replacing the existing. Imagine having a million brilliant assistants at your disposal—eager to help, willing

PROJECT OVERVIEW Recently, The Only Constant partnered with Stookers Gin, an Amsterdam-based dynamic micro-brand in the gin industry. The goal was to explore how we could revolutionize Stookers’ digital marketing through AI automation. This business case describes the first project: Stookers-ai. The project addresses the challenges of social media management—resource intensity and the need for constant content innovation—by leveraging artificial intelligence to create a fully autonomous social media department. Challenge and opportunity Social media, while a vital channel for brand

While AI seems to be able to shake up every part of business, I see a lot of talking, and way less doing than I think is needed. I guess this is like a grown up version of a kid in the candy store; if everything is an option, choosing becomes impossible. In a recent blogpost Ethan Mollick shared an interesting approach on how to break this problem. He poses four pivotal questions essential for leaders that want to start

Long-term strategic planning… Does that still cut it when the next quarter feels like a distant future? It certainly makes talking about three-year plans seem strange. We think it is time to make strategy more agile and believe that synthetic user data can help! The age of Synthetic User Data and AI What’s synthetic user data, you ask? It’s data that’s artificially generated, yet mirrors real-world respondents so accurately that it can be used validate strategies and concepts. Recent research

For me, one important takeaway from last week’s IMF blog findings stands out: AI’s impact on how we work is already here, and it is reshaping organizations globally. This change isn’t limited to specific sectors, it’s affecting most industries and jobs, with recent estimates suggesting over 60% of work changing. In case you were wondering: Yes, It’s time to rethink your organizational structures, your processes, your services, and products. AI implementation, often approached as a bottom-up process (which is not