Artificial Intelligence is advancing at extraordinary speed. New models surpass previous versions within months. For many organisations, that speed generates hesitation instead of momentum. This hesitation is what we call AI paralysis; an inherent fear of the unknown and a fear of committing at the wrong time. It often hides behind careful language about timing or market maturity. The underlying logic is that “Clarity will arrive if we wait.”

I think that waiting for that clarity is a high cost to pay, but let’s unpack it.

The Myth of “Too Early” and the Wait-and-See Trap

Large language models have existed for nearly a decade. What the market is experiencing today is refinement, accessibility, and productisation.

Progress will continue at pace as companies such as OpenAI, Google and Anthropic all continue to compete for AGI or maybe even ASI if you’re a believer…. The assumption that the market will settle into a neat, obvious path, and will reward those unwilling to commit now, is a pretty unrealistic position to have. Since the reality is very different, the path forward is shaped by the organisations that experiment, implement, and adapt. Your experience becomes the differentiator.

An example of a common argument that sounds financially disciplined:

“In six months, the models will be twice as good and half the price.”

In a vacuum, that logic feels correct. However, in production, it's eroding any competitive position you may have or could gain. Your competitors are already outperforming you because they're taking the AI benefits offered right now. And those benefits compound over time. Consider Kodak: The company invented the digital camera, massive potential market and had the opportunity to be a leader. However, leadership delayed commercialisation to protect its film business. Development slowed and any momentum they could capitalise on, faded away. Meanwhile, Sony and other electronics manufacturers invested heavily in digital imaging. Granted, their early cameras were limited, the image quality was modest, and the hardware was hilariously bulky.

But they kept building!

Over time they accumulated manufacturing expertise, design refinement, supply chain strength, and market understanding. Finally, when digital photography matured, those companies held the advantage. Kodak possessed the original invention and had all the opportunity any organisation in a similar position could ask for! However, they didn’t jump on it and look where they are now…

AI adoption follows the same dynamic. Teams that experiment now accumulate knowledge, experience, best practices, and gain maturity. Teams that delay face a steep learning curve while competitors keep getting ahead.

Just Start Building

At SSW, YakShaver began during the GPT-3.5 era. Model quality was lower and that meant that hallucinations were more frequent.

The objective at the time for development were the following:

• Architecting AI-enabled systems
• Designing resilient infrastructure
• Training developers in prompt engineering and evaluation
• Embedding AI into daily workflows

We didn’t want to hamstring ourselves in development, so we focused on core ideas that meant when the inevitable model upgrades rolled around, we had minimal structural change. The architecture and business logic remained intact while the actual AI layer improved. Teams started to solve problems and as the technology evolved. YakShaver simply got better and better. AI can help compress proof-of-concept timelines dramatically. Prototypes that once required weeks now can be built in hours. Nowadays, it’s likely to have a working app during the concept phase of a new product. Stakeholders can now interact with a working solution instead of reviewing slides theorising about what could be the product to market.

This shift completely reshapes the decision-making process. As requirements become clearer and misunderstandings surface early, the project becomes tangible and usable in such a short period of time. Ultimately, speed can overcome uncertainty and having a working app builds confidence. This eliminates a lot of the analysis paralysis stakeholders have as they now see tangible outcomes.

Stay Competitive

The true divide between yourself and the competition is your company's appetite on experimentation and innovation. Early technology adopters are currently accumulating the essential building blocks of the future. They are gaining institutional knowledge with AI and encouraging internal champions to push the envelope with these technologies, and quickly seeing many ROI opportunities that start paying off immediately. In contrast, late adopters will eventually face the frantic reality of compressed timelines and external pressure, where learning is forced by urgency rather than by curiosity (remember Kodak!).

While model performance will continue to improve, pricing will fluctuate, and new entrants will inevitably emerge, the ultimate decisive factor will be - is your business already positioned to benefit from those AI improvements? AI paralysis may offer a sense of temporary comfort, but jumping on now will build a durable advantage. The market will not wait; instead, the organisations that move now are the ones developing the very certainty that everyone else is still waiting to find.