Making Sense out of Change: Investing in the AI Cycle

The topic of the year and the decade—and beyond—is artificial intelligence (“AI”). In an effort to steward client funds well at Eventide, we have sought to build a sound ethical and fundamental structure for investing in AI and want to share our approach with curious investors. Eventide is utilizing what we call our “mosaic approach” to create a framework for investing multidimensionally to maintain thoughtful exposure across a wide range of AI-based opportunities. But to have a proper understanding of the current cycle, we think it wise to first consider other recent tech cycles—specifically AI’s predecessor, the cloud cycle.

The cloud’s golden era, which started in the late 2000s, took place as companies realized that moving data and software development to the cloud was a transformational innovation for businesses of the future. Previously, companies had lived “on-prem,” meaning that data, infrastructure, and processes were stored within their own data centers. This system involved large, highly customized licenses. Then, Software as a Service (“SaaS”) burst onto the scene, precipitating a new model which moved data and architecture from a company’s own hardware to the outsourced public cloud. Companies no longer had to maintain their own data center footprint; updates to the software stack could be implemented immediately for all customers; and the potential for scaling businesses was seemingly unlimited for the software companies that offered these services.

This was a challenge to the status quo of the largest tech companies in the world at the time. The sheer volume of data that needed to be transferred and the intricate networks of code that had to be redesigned left these companies struggling with years-long system overhauls. Small, nimble companies, on the other hand, born alongside the genius of the cloud, were advantaged in this new era. This created an environment where small/mid-cap companies could innovate quickly and deliver impressive investor returns, bucking the traditional risk profile of a burgeoning, non-blue-chip company.

Unlike the cloud cycle, where the beneficiaries were SaaS companies that could easily maneuver without the albatross of outdated complex technological systems, AI has its roots in data and is largely being developed on top of pre-existing architecture. In this case, typically the largest companies are the ones either sitting on reems of proprietary information or with the infrastructure to most efficiently process data. These institutions are well positioned to capture shareholder value. This creates a healthy counterbalance with small/mid-cap companies, which are naturally more agile. We don’t know how this cycle will play out, but we have reason to suppose it will be quite different than last time—perhaps even market cap agnostic.

This isn’t the only reason to invest across tech holistically in the medium term. With a more challenging landscape for initial public offerings, companies are staying private for longer and are entering public markets as mid-cap or even larger companies. Which companies make up the small-cap tech universe, in that case? We believe many of them are suboptimal investment opportunities, weighed down by challenges with their ability to scale, middling execution, underwhelming management, or one of another million ways businesses fail to attain the status of a generational technology leader. There is value across market caps, and it’s prudent for our investment allocation to take a wide-angle view across the AI value chain.

This wide-angle view brings us to our mosaic approach.  In essence, we are investing across both the value chain and varying levels of business maturity. The AI value chain starts with the basics: the land and buildings where data centers are housed. These buildings are then filled with chips and other hardware which must be powered, stoking exponentially growing demand for energy. Finally, the output is the software, process automation, and other potential end products that will be derived from this infrastructure. We are seeking to invest across this full spectrum which spans many industries, all united in support of AI growth. Eventide’s team of analysts discussing these dynamics are therefore not just tech analysts; we integrate excellence across many sectors, synthesizing a confluence of viewpoints into the final portfolio. We believe this approach will help avoid blind spots that other sector specialists may miss.

The other key axis we consider is the business cycle, which we split into four essential buckets. The first is for companies which are established quality compounders that have already developed products and built entrenched moats and are now buoyed by consistent profitability and free cash flow generation. Next are companies with strong and underappreciated fundamentals, which have a finished product and accelerating profits. Moving up in risk to the next bucket are investments based on “S-curves.” Here we seek companies with emerging products which, although not core to the business, could provide a significant bump in equity valuation if they can gain traction and boost financials. Lastly, the final bucket is for emerging growth companies with higher risk and reward profiles based on potential AI use cases primed to disrupt the market with management teams we believe can execute.

The goal is to be invested across the full matrix of business types along the AI life cycle. Within this dominant yet emerging space, our goal is to focus on where we see the most encouraging momentum and fundamentals within the full mosaic so that we can build an aggregate portfolio with high conviction.

Eventide’s consistent focus on strong management teams with integrity—inherent to our proprietary Business 360® and fundamental research process—has particular meaning when investing with so many unknowns. We are seeking companies that can adjust nimbly as the AI industry matures, and leadership is core. Besides business savvy, the ability to integrate AI better than the competition, and products and services that promote human flourishing, we also must consider the ethics of management. Thinking on the topic of privacy for a moment—it can be tough to not give in to the temptation to use private data for financial gain. This is why it is essential for our portfolio companies’ management teams to align with our values. Ultimately, we believe wise, experienced leadership with a strong moral compass will champion value for all stakeholders, including shareholders.

No investment case is well-built if it doesn’t consider the risks. Within AI, the two biggest risks have long been known as hallucinations—also known as mistakes—and the matter of privacy. Besides these fundamental risks, we are also considering broader risks for all stakeholders involved. Ethics, job replacement potential, and the multifaceted impact of AI’s infrastructure build-out makes the picture infinitely more complicated. As diligent investors, we believe considering all these factors is essential in the current wave of technology. Trying to stay ahead of this at Eventide, we have been actively evaluating the risks and benefits in ongoing discussions and ultimately asking the question of how human flourishing will likely be impacted by these leaps forward in innovation.

Finally, we aren’t too proud to admit when we are wrong. As the evidence changes, so must our thesis. Investment conviction and fluidity are both central as the rapid pace of innovation and barrage of new datapoints illuminate the path forward. With so much yet unknown, we believe in grounding ourselves in what we do know, seeking to diligently apply our mosaic approach, and always staying humble as we navigate ahead.