Google is worth over $100 billion. It's not just the name of a company; it's slang for an internet search. Using an alternative brand can get you laughed at by friends and leave questioning looks on colleagues. All this, and it wasn't the first search engine on the Internet. Before Google was Yahoo!, AltaVista, and others. The first search engine was Archie. Have you ever heard of it?

Google won the internet search game and has held that market for some time. Many don't know, but the way they won was by implementing an innovative algorithm called PageRank. This algorithm, developed by Google's co-founders Larry Page and Sergey Brin, revolutionized how search results were ranked and displayed. PageRank's introduction led to more relevant and reliable search results, which quickly gained the favor of users. This innovation, coupled with Google's clean, user-friendly interface and commitment to speed, helped it outpace competitors.

What did Google get right? They were in the right place at the right time. Investments in internet technologies at the moment of its founding were plentiful. But more than that, leveraging an algorithm to provide superior customer experiences cemented the win. Investors remember that billion-dollar win, and they want more. Today, investing in AI is the playbook. These investments are often referred to as "Billion-Dollar Bets" because, like the pioneers of the internet boom in the 1990s, today's investors are looking for redefining opportunities that promise substantial returns. With the ground-breaking capabilities of modern AI foundational models, businesses have the potential to discover transformative applications and achieve unprecedented success. For some, this will result in a landslide of monumental victories, just like it did for shareholders of Google.

The journey to today's AI innovation has been significantly fueled by open research and collaborative efforts in the tech community. Much like the early days of the internet, the openness of resources and research has accelerated development and adoption. However, as the industry finds ways to capitalize, a shift toward proprietary, closed enterprise solutions is becoming the trend. This change means that many of the tools and advancements that were once readily available are now becoming exclusive and costly.

This transition presents a dual challenge and opportunity. Companies now face the task of navigating a more complex ecosystem where early access to the latest technologies can be a significant advantage. Those who engage early may secure foundational technologies at a lower cost and adapt these innovations to gain a substantial market edge. Conversely, businesses that delay their entry risk facing higher costs later, as they may need to invest in more expensive, closed-source solutions to remain competitive.

In this context, quickly launching an AI foundation within an organization becomes crucial. Businesses need the foresight to recognize potential wins and the agility to act swiftly. The current environment offers a rare chance for companies to innovate on open, low-cost foundational models and potentially reinvent themselves or their industries, just as early internet companies once did. For many, this could be the moment to lay the groundwork for future success, making strategic investments that will pay off as the AI field continues to evolve.

Investors are not just participating in a trend. They are on a quest to discover the "next big thing" that will provide a competitive edge. What does this remarkable result look like? It could be an AI system that drastically reduces operational costs, a new data-driven product that anticipates customer needs, or a machine learning model that significantly reduces the time for R&D processes. The challenge lies in identifying which of these possibilities could turn into a real, tangible advantage for a business.

Creating a compelling AI investment case requires a deep understanding of how AI can be specifically tailored to address a particular industry's unique challenges and opportunities. This understanding is critical because, like the internet in the 1990s, AI today is a broad field with numerous applications. Not every investment will pay off, and what works for one business might not for another, but well-informed choices—rooted in strong business commercials and a clear understanding of AI capabilities—can lead to extraordinary outcomes.

Moreover, crafting an effective business case begins with an understanding of the specific needs of the business and an assessment of the potential future impact of the AI solution under consideration. Rather than simply asking if AI can be applied, companies should focus on strategically leveraging AI to maximize benefits. This necessitates a detailed internal assessment, extensive market research, a solid grasp of current technologies, and a forward-thinking approach to future possibilities.