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Generative AI - Navigating Platform Shifts

Published October 10, 2023

Generative artificial intelligence is today’s personal computer or cellphone. Think about that for a moment…those two devices revolutionized our lives and the way business is conducted, and resulted in investment opportunities no one knew existed. Apple, which few had heard of forty years ago, has become one of the world’s biggest companies by market capitalization and revenue. Generative AI promises to be the next revolution. What changes do we anticipate, why do they matter and how can our clients capitalize on these tectonic shifts in technology?

The history of technology-driven platform revolutions

Innovation and changing consumer demands are typically the drivers behind technology-driven platform shifts. Recent noteworthy platforms include the shifts to desktop, laptop, Internet, mobile, and cloud computing. New platforms are often meaningfully larger than their predecessors, occurring approximately ten years after the prior one goes mainstream.

Source: AlTi Global

There are several key lessons we can learn from past technology platform shifts. The new market leaders create significant enterprise value: Many of the largest companies today were the market leaders in past platform shifts. Having exposure today to the companies that will become the generative AI winners should have profound implications on investment performance over the coming years.

They take time to play out: Successful platform shifts often require the development of an ecosystem around the new technology. This ecosystem can include other businesses, developers, content creators, and more. The rise of smartphones, for example, wasn’t just about the devices but also about the apps, services, and other businesses that grew around them.

First movers may not always be the winners: Being the first to introduce a new technology doesn’t guarantee sustained success. For instance, Google was not the first search engine, but it became an unmatched market leader.

The influx of capital will foster rapid change: Although artificial intelligence techniques have been around for decades, recent generative AI breakthroughs are exciting everyone and driving investments in cutting-edge research and development. As a result, we have seen significant advancements in natural language processing, computer vision, and machine learning, among others. Overall, increased investment should accelerate how quickly these new technologies become transformative, similar to how the Apple iPhone created new business opportunities for companies like TikTok, Instagram, Uber, Airbnb and Yelp. 

Why does it matter?

Generative AI has become more accessible to consumers and sparked widespread engagement. According to Goldman Sachs, the global AI market capitalization is estimated to grow at a compound annual growth rate of approximately 40% over the next five years and reach nearly $190bn by 2028.

Every industry is likely to be affected by generative AI: Companies must adapt and incorporate AI into their business strategies to stay competitive and relevant. Those who fail to do so risk falling behind their competitors and missing out on the advantages that AI can offer.

Capital expenditure should increase dramatically: The AI demand-driven bottlenecks are being felt across the technology landscape. Semiconductor chips are back-ordered, cloud computing access is being rationed, and off-peak computing is now a business strategy. Until these supply-demand dynamics in the digital infrastructure layer are balanced, companies will need to continue spending to build capacity. Microsoft estimates that over $1 trillion will be needed to expand data center capacity alone.

Access to power is becoming increasingly important. The computational nature of generative AI systems means that they consume significantly more power than traditional ones. The current data center infrastructure cannot accommodate this 4 AlTi Tiedemann Global next wave of power needs. Data center power usage is expected to exceed 35 gigawatts (GW) per year by 2030, more than tripling the amount consumed last year.

Domain expertise is needed to identify what matters: We expect many companies will tout generative AI capabilities even though the technology is more evolutionary than revolutionary. We think the following companies are likely to be beneficiaries:

  • Established businesses with access to unique data sources and significant pools of capital may be better positioned to use generative AI to create competitive moats.
  • Companies that own the key foundational platforms or chips/power/digital infrastructure required to power this platform shift.
  • New disruptors with groundbreaking AI deployments that fundamentally change how consumers or businesses behave, bringing new business models and/or higher levels of enterprise efficiency or productivity.

How to play it from an investment perspective?

We envision the investment opportunity unfolding in distinct waves.

  • Wave 1 involves the foundational infrastructure layer (often called ‘picks and shovels’) needed instead of an end product (eg, SIM cards instead of the cellphone), and this phase is currently underway. It revolves around securing access to GPUs, data centers, and computational power.
  • Wave 2 occurs as companies begin to use Gen AI to address prevailing business bottlenecks, necessitating a substantial increase in capital expenditures and time and a trial-and-error approach until benefits are realized in the form of increased efficiencies and improved profitability.
  • Wave 3 will be the proliferation of new incredible businesses that nobody can envision today and which could become incredibly disruptive.

Given our view that generative AI will roll out in waves, we believe the relationships between capital spending, customer adoption, revenue growth, operating margins, and pricing models will have a significant impact on investment outcomes. The ability of the winners in AI to take advantage of this platform shift may take more time than currently expected by the market. In this dynamic and multi-faceted roll-out, achieving portfolio resilience will likely require a thoughtful asset allocation approach across various investment strategies:

  1. Passive equity exposure: By definition, capitalization-weighted indices will have exposure to growing themes like generative AI which eliminates the risk of being underweight the biggest generative AI winners based on valuation.
  2. Targeted alpha strategies: Active managers who are technology domain experts could have a distinct advantage. We are looking for active exposure via nimble managers that have the ability to move into new opportunities as the different waves develop. We believe there could be the potential for venture-like returns in public markets.
  3. Real assets: Given the demands of generative AI, digital and energy infrastructure will be a critical component of widespread AI deployment.
  4. Private equity: Value-add managers with a proven track record of delivering digitalization-driven growth and improved margins to established companies should have a distinct advantage.
  5. Venture capital: Venture capital should provide the most direct exposure to the most disruptive generative AI-native technologies. Companies embodying AI-native entities (currently beyond our current conceptualization) will be the riskiest investments but also potentially the most rewarding. Given the nature of cloud infrastructure and distributed software, new generative AI businesses should emerge rapidly as the technology takes hold. We have access to differentiated managers in each of these spaces and are currently researching how best to execute this investment thesis.


While still in its nascent phase, the domain of generative artificial intelligence is undergoing swift and expansive growth. The existing array of generative AI applications resembles the initial stages of other transformative platform shifts. Like the emergence of mobile apps after the introduction of the iPhone, the landscape of generative AI is characterized by novelty and ambiguity surrounding competitive advantages and business models. Despite these uncertainties, the applications found within the iPhone ecosystem offer captivating previews of what lies ahead. As we witness machines generate intricate code and remarkable imagery, it becomes effortless to envision a future where their capabilities substantially amplify productivity and creativity, thereby ushering in a realm of substantial opportunities for value creation across an array of investment strategies. We continue to undertake a range of research across asset classes to capture the range of premium returns that will come from this platform shift. We look forward to sharing these investment solutions with you.

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