The AI Value Chain: Looking Beyond the Headlines
The bottom line first: The trends driving AI go beyond a few technology companies. While these themes are driving markets, it’s important to maintain a broader perspective and longer time horizon with a focus on long-term financial goals.
Computers, smartphones, and other technology have become part of daily life. We expect them to work whenever we need them, but there is a tremendous amount of infrastructure and coordination behind the scenes that makes that possible.
Artificial intelligence (AI) is no different. Asking a chatbot a question may feel simple, but there is a complex network of companies, technology, and resources that make those interactions possible. AI has quickly become one of the biggest themes influencing financial markets and the economy, which is why it's important to understand that the story extends far beyond a handful of well-known technology companies.
While AI has the potential to reshape how businesses operate and how people work, it's still difficult to know exactly how quickly these changes will occur or which companies will benefit the most. That uncertainty can create excitement and opportunity, but it can also lead to market swings. So how can people think about AI while maintaining a long-term perspective?
The AI Ecosystem Extends Far Beyond Chatbots
One of the most important things to understand is that AI is not a single company or investment. While many people think about names like OpenAI, Anthropic, or Google when AI is mentioned, those companies represent just one part of a much larger ecosystem.
Behind every AI tool is a broad network of businesses involved in producing computer chips, building data centers, developing software, and providing the infrastructure needed to support these technologies. Each plays a different role and faces different opportunities and risks.
At the foundation are the specialized computer chips that power AI. These chips are used both to build AI models and to support their day-to-day use. Training AI models requires processing enormous amounts of information across thousands of computers, often taking weeks or months to complete.
Once those models are built, they still require significant computing power every time someone uses them. Whether an individual asks a chatbot a question or a business integrates AI into its operations, the technology relies on substantial computing resources behind the scenes.
As demand grows, companies must expand the facilities that house this technology. This is where data centers come in. Think of a data center as a massive building filled with computers operating around the clock. These facilities require electricity, cooling systems, security, and ongoing maintenance to keep everything running smoothly.
Spending on data centers has become a major driver of economic activity. Since the launch of ChatGPT in late 2022, construction spending on data centers has increased dramatically and now exceeds spending on other types of office construction.1 While AI is helping fuel this growth, broader trends such as increased technology adoption and automation have also contributed to rising demand for computing resources.
The final piece of the puzzle is how businesses actually use AI. Some companies are incorporating AI into existing products and services, while others are developing entirely new tools. This may ultimately be where much of AI's value is created, but it is also one of the most difficult areas to evaluate. Success will depend on whether companies can use AI to improve productivity, strengthen their products, and better serve customers.
Will AI Investments Deliver Long-Term Results?
One of the biggest questions today is whether the hundreds of billions of dollars being invested in AI infrastructure will ultimately generate enough value to justify the spending.2
Demand for computing power has surged as companies race to build and expand AI capabilities. At the same time, advances in technology may eventually make AI systems more efficient, allowing them to accomplish the same tasks using fewer resources.
This uncertainty helps explain some of the ups and downs in AI-related stocks. Periods of optimism about future growth have often been followed by concerns about whether demand will remain strong enough to support continued investment.
More recently, some market participants have questioned whether newer, more efficient AI models could reduce the need for massive computing infrastructure. History suggests, however, that technological improvements don't always lead to lower demand. In many cases, making technology faster, cheaper, and easier to use actually increases adoption and creates new uses that were previously impossible.
Think about electricity or personal computers. Both became more efficient over time, but that efficiency encouraged broader use rather than reducing demand. The same could prove true for AI.
Even so, markets have a long history of getting the timing wrong when it comes to new technologies. The internet ultimately transformed the world, but many of the expectations surrounding internet-related companies in the late 1990s took years, and in some cases decades, to fully materialize. That's one reason maintaining a long-term perspective remains so important.
High Expectations Are Already Reflected in Prices
As excitement around AI has grown, stock prices for many technology companies have risen as well. As the chart above shows, valuations within the Information Technology sector remain elevated compared to both their own history and the broader market. Similar trends can be seen in sectors such as Communication Services and Consumer Discretionary, which also include many large technology companies.3
It's important to remember that valuations are not useful for predicting what markets will do next week, next month, or even next year. Instead, valuations help provide context when building a portfolio that aligns with long-term financial goals.
While AI-related companies may continue to create opportunities, they are not the only areas of the market with attractive prospects. Many other sectors remain reasonably valued and are experiencing strong earnings growth as well. As always, maintaining a diversified portfolio and focusing on your long-term goals remains one of the most effective ways to navigate changing market environments.
Sources and Footnotes
- https://www.census.gov/construction/c30/c30index.html
- The Magnificent 7 companies include Meta, Amazon, Apple, Alphabet, Nvidia, Microsoft, and Tesla. Data as of July 17, 2026
- Clearnomics research and LSEG data as of July 17, 2026