Navigating the AI Frenzy: What to Focus on?

Every day brings another headline about AI. From new features or products, Nvidia’s stock price fluctuations, to debates about energy consumption, AI news is everywhere. Media outlets and commentators alike are quick to offer predictions, often with a sense of urgency that can leave one overwhelmed.

As someone at an AI-first start-up, we are more sensitive than most to these developments. With few assets and a fast-moving market, we constantly grapple with the question: which new technology or trend demands attention? And perhaps more importantly, which ones should we ignore? It’s easy to feel like we are falling behind, but chasing every shiny object can be just as dangerous as ignoring the critical ones.

Here are a few guiding principles that have emerged from our experience in this relentless environment. While our specific context is that of a young AI company, the lessons here apply to anyone seeking to navigate the shifting AI landscape.

1. Separate News from Predictions—Focus on Inevitabilities

The sheer volume of AI news can blur the line between fact and speculation. While it’s tempting to latch onto the latest predictions, remember the quote - “It’s tough to make predictions, especially about the future.” (attributed to Yogi Berra, Niels Bohr, and others). The only certainty is uncertainty.

For business leaders, the key lies in identifying “inevitable truths” rather than succumbing to short-term noise. One such truth: computers will become faster. Another: AI will become cheaper and more pervasive. As leaders, we must anchor our strategies around these certainties rather than the flurry of speculative analyses about the future of AI. For example, news about the rising energy costs of AI might dominate headlines, but what matters is how unit economics will shift with AI, customers, and the computing needed. Can you reasonably expect those costs to decline in your operational context? Or are there efficiencies to be gained elsewhere?

Recognize that no business can afford to chase every development. The challenge is discerning which trends affect your operations and which are distractions. Steve Jobs famously ignored countless trends because he focused on where technology intersected with what his customers truly valued. That focus is more relevant than ever in today’s AI-driven market.

2. Keep Your Eye on the Prize: Define Your AI Core

AI is not a single technology; it is a suite of capabilities, each with its own implications. Likewise, your business is more than a singular entity. It is a dynamic system with multiple facets, all of which can be impacted by AI in different ways. The trick is to define how AI creates, enhances, or protects value for your customers. Once you know that, every new development must be evaluated through the lens of your core value proposition.

For us, at Nurish, the core value lies in how large language models (LLMs) translate voice input into specific, actionable nutritional insights. This is our north star, and we evaluate any new AI development by asking: will this enhance the accuracy, speed, or scalability of that process? If not, we have to pass—even if the technology is exciting. The biggest risk we face is being distracted by the next great innovation at the expense of what is truly valuable to our users.

Business leaders in more established enterprises face a similar challenge. Deciding what’s core is not just about defending the status quo. It’s about ensuring that your core strategy has been validated by the market, not simply entrenched because of past investments. 

3. Maintain a Dual Budget: Core vs. Opportunistic AI Investments

While focus on the core is essential, innovation often comes from unexpected places. Leaders should adopt a dual-budget mindset—one that protects the core, while also allocating resources for opportunistic experiments in AI. At Nurish, we limit our core AI spend to the technologies that directly enhance our primary value proposition. But we maintain a separate budget for fast, low-cost experiments.

For instance, we experimented with offering a simple interface in the GPT Store to attract new users. It wasn’t core to our strategy, but it didn’t drain substantial resources, either. These small experiments can quickly be discarded if they fail, but if they show promise, they can shift from the periphery to the core. 

For large enterprises, this mindset is even more crucial and more nuanced. The goal isn’t to become rigidly focused on your primary strategy but to retain the flexibility to seize new opportunities when they arise. 

4. Don’t Be Blinded by AI—Other Trends Matter Too

AI’s glow is so bright that it risks casting shadows over other critical trends in technology, society, and economics. Business leaders must remember that AI is just one piece of the puzzle. Many other developments in these areas, especially when adjacent to your market domain, could have just as significant an impact on your business. Ignoring these broader trends in favor of chasing AI is a mistake.

At Nurish, we keep an eye on developments outside the AI bubble, particularly user behavior and health. But this is easier said than done. Trends are difficult to spot and sometimes they are clear only in hindsight. I would argue that this is much harder than spotting AI trends. 

5. AI is a Tool, Not a Strategy—Don’t Ignore the Basics

No matter how transformative AI appears, it remains a tool, not a strategy. Foundational business principles—solid operations, clear customer value propositions, and sustainable economics—still apply. In our zeal for AI, it’s easy to overestimate its importance and underestimate the fundamentals that make businesses successful. Yes, you must adjust and innovate in them due to AI or with AI, but you cannot ignore them. 

Executives, particularly those who are not technical, can become enamored with the allure of AI. But while AI can drive efficiencies or create new value, it doesn’t replace the functional needs or execution, whether done by humans or an AI-first approach. As Michael Porter reminds us in his work on competitive strategy, true differentiation comes from understanding the unique sources of competitive advantage, not from the technology itself.

Conclusion: A Balancing Act for Business Leaders

The future of AI is undoubtedly full of promise, but there is not one clear well-lit path. Business leaders must walk a fine line between staying informed and not getting swept up in the hype. Focus on inevitable truths, define your AI core, maintain a dual-budget mindset, and never forget that AI is just one tool in your broader business strategy. And most importantly, remember that technology changes—core principles of value creation do not.

The AI race is far from over, and it’s only going to accelerate. The winners will be those who can discern which developments are worth chasing and which are distractions. We haven’t figured it all out, but try to do what we can. How are you doing?