What 7 Wonders Teaches Us About the Coming Inflection Point in AI

Have you ever played 7 Wonders? This paragon of the modern board game era became a staple in the board game market thanks to its simple rules yet diverse paths to victory.

Throughout the game, players choose from different categories of cards, such as:

• Resource cards, which enable them to afford more powerful cards in later rounds.
• Commercial cards, which allow them to use their neighbors' resources.
• Civilian cards, which provide direct victory points.

The game is played over three "Ages." Each Age has its own deck of cards, forcing you to constantly adapt your strategy to a changing context. In the first Age, most cards help you build your economic engine by gathering the resources needed to play cards in the following Ages. By the third Age, nearly all cards provide victory points, directly or indirectly.

This means that during the second Age, which contains a mix of economic and victory point cards, you must execute a crucial pivot from the "engine-building" phase to the "harvesting" phase. Pivoting too early means you start scoring sooner, but may lack the resources for more valuable cards later. Pivoting too late leaves you with a powerful engine but insufficient time to convert your resources into enough victory points to overtake your opponents.

IRL (In Real Life)?

YouTube, Google Search, and Facebook all started as free products. They were widely adopted and became integral to people's daily lives. Eventually, these services were monetized, either through subscription fees or by displaying ads to generate revenue. This was the inflection point—the shift from the engine-building phase to the harvesting phase. Here, engine-building meant acquiring resources (users and data), while harvesting meant converting those resources into revenue.

So, what About AI?

As of today, most people simply open an LLM interface and type a question to get a rich, detailed answer. Users are becoming accustomed to these models. Soon, they may not be able to imagine their workflow without an AI assistant.

Needless to say, an inflection point will arrive when AI is broadly monetized. Unlike a Google search, where sponsored links are clearly marked at the top of the results, an AI can be influenced by its sponsors through hidden pre-prompts, subtly steering its responses to favor their interests.

What Can We Do?

For a company, relying on "free" public AI tools means accepting the risk of influence from the AI provider's sponsors, but also accepting to teach public AI models with their own business data. The danger is obvious, especially when LLMs are used for strategic decision-making.

Ideally, a company should choose and implement a dedicated, private AI engine, ensuring its employees have a reliable and unbiased tool at their disposal. This is why, as a software provider, we design our products to connect to our customers' private AI engines, helping them establish governance over their data and AI activity.

Take-Away

The beauty of 7 Wonders is that the rules for all three Ages are printed in the box, enabling players to make insightful decisions from the very start. In the great game of technology, however, the rules are being written as we play.

Some players at the table are in a position to draft the global rules—the fundamental laws of how the game will be won. The rest of us are left to define our own personal or corporate strategy for navigating the game. The true challenge, then, is to constantly read the global rules as they are being written, and to adapt our own in response.

In this game, just as in 7 Wonders, winning won't be about having the best strategy from the start. It will be about mastering the art of adaptation and opportunism—of writing our own rules with the full awareness of those being written for us.

To read more about AI integration, see:

https://www.uxopian.com/blog/secure-your-data-in-one-click-automating-redaction-with-fast2-and-ai