Lately, every boardroom feels the same. Someone leans forward, half-serious, half-tired, and asks the question hanging over everyone else: “How do we invest in AI with confidence when everything keeps changing?”
It’s a fair question. The problem isn’t ambition. It’s the floor constantly moving under your feet. New models, new tools, new promises. Plans that looked smart six months ago already feel old. Others never make it out of pilot mode because no one’s quite sure which way to turn next.
In our latest white paper, ‘AI with real ROI’, we’ve tried to make sense of the chaos. After months of client work, late-night debates and a few strong coffees, we landed on four forces that are quietly, and sometimes loudly, pulling strategies in opposite directions. Once you see them, you can’t unsee them. Most organisations already feel these forces every day, even if they haven’t given them names yet.
- GenAI Model Innovation: The first force is the relentless pace of innovation from the giants. OpenAI, Google, and Meta. They’ve moved from building models to empires. One week it’s Gemini. The next it’s VEO. Blink and the map’s redrawn. Here’s the catch. The danger isn’t just falling behind, it’s standing still. Many firms decide to pause and catch up later, only to realise the next wave has already rewritten the rules. Keeping up isn’t about chasing shiny toys. It’s about making sure your people and systems can still speak the same language when the next upgrade arrives.
- Incumbent Applications: Then there are the big enterprise platforms: SAP, Salesforce, and ServiceNow. Some had AI plans sitting in drawers for years. Others are bolting conversational layers onto legacy cores and calling it innovation. They bring scale and reliability, sure, but their speed can’t match the tech giants. The real danger lies in comfort. It feels safe, until someone quicker takes your spot. Staying loyal to the familiar can be a costly habit when the market begins to shift.
- Personal AI Applications: The wildcard is personal AI tools, ChatGPT, Perplexity, and Claude. They’ve changed what people expect from technology. Employees are experimenting on their own, often miles ahead of company policy. Leaders tend to whisper, half-guilty, that their teams are using these tools far more than IT would prefer. Their concern is entirely justified. Not just for compliance reasons, but because control has already shifted from systems to individuals. The smartest organisations aren’t trying to ban it. They’re learning how to harness it safely and openly. Pretending it isn’t happening just drives it underground.
- Custom AI Applications: Then comes the gold rush. Start-ups, consultancies, and domain experts are moving fast, scrambling to stake their claim before the platforms swallow them whole. Nvidia’s NEMO libraries show just how quickly the market is specialising. However, there’s a trap here. Clients’ risk backing the wrong horse. What looks brilliant today can be outdated tomorrow. The trick is to stay light on your feet, test fast, learn fast, but don’t bolt anything down until you’re sure it’s worth the metal. Flexibility wins this race, not blind commitment.
These four forces aren’t a neat model to admire. They’re crashing into each other inside every large company. Between functions, between global and local teams, between ambition and reality. No wonder so many AI strategies feel stretched thin before they’ve even started.
Here are the three moves leadership teams can take:
- Map the forces: Get them on the table. Talk about how each one touches your data, talent and business model. You’ll be amazed what misalignment that exercise uncovers
- Sequence your plays: You can’t chase everything at once. Pick your battles, build momentum, and make deliberate trade-offs. Running in all four directions burns time, cash and patience
- Build for flexibility: Procurement and platform roadmaps rarely move together. Your architecture needs to flex with the market. Don’t look for a forever solution. Build so you can pivot without starting again each time
The Four Forces framework isn’t about simplifying AI strategy. It’s about seeing what’s really happening so leaders can make better calls. Once you name these forces, the noise quiets. You see where the tension really is. That’s when strategy stops feeling like guesswork and starts to feel like leadership.
In our next article in the series, we will dive into GenAI Model Innovation and why keeping pace with the giants isn’t about imitation. It’s about survival.
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