For many years, data volumes have been accelerating.  By 2025, global data volumes are expected to reach 180 zettabytes (1 zettabyte=1 sextillion bytes), up from 120 zettabytes in 2023. 

In the age of AI, data is viewed as the currency for large language models (LLMs) and AI–enabled offerings. Therefore, demand for tools to integrate, store and process data is a growing priority amongst enterprises.  

The median size of datasets required to train AI models increased from 5.9 million data points in 2010 to 750 billion in 2023, according to BofA Global Research. As demand rises for AI-enabled offerings, companies are prioritizing tools to integrate, store, and process data.

In BofA’s survey, data streaming/stream processing and data science/ML were selected as key use cases in regard to AI, with 44% and 37% of respondents citing usage, respectively. Further, AI enablement is accelerating data to the cloud. Gartner estimates that 74% of the data management market will be deployed in the cloud by 2027, up from 60% in 2023.

Data infrastructure software [1.] represents a top spending priority for the IT department. Survey respondents cite that data infrastructure represents 35% of total IT spending, with budgets expected to grow 9% for the next 12 months. No surprise that the public cloud hyper-scaler platforms were cited as top three vendors. Amazon AWS data warehouse/data lake offerings, Microsoft Azure database offerings, and Google BigQuery are chosen by 45%, 39% and 35% of respondents, respectively.

Note 1. Data infrastructure software refers to databases, data warehouses/lakes, data pipelines, data analytics and other software that facilitate data management, processing and analysis. 

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The top three factors for evaluating data infrastructure software vendors are security, enterprise capabilities (e.g., architecture scalability and reliability) and depth of technology.

BofA’s Software team estimates that the data infrastructure industry (e.g., data warehouses, data lakes, unstructured databases, etc.) is currently a $96bn market that could reach $153bn in 2028. The team’s proprietary survey revealed that data infrastructure is 35% of total IT spending with budgets expected to grow 9% over the next 12 months. Hyperscalers including Amazon and Google are among the top recipients of dollars and in-turn, those companies spend big on hardware.

Key takeaways:

• Data infrastructure is the largest and fastest growing segment of software ($96bn per our bottom-up analysis, 17% CAGR).
• AI/cloud represent enduring growth drivers. Data is the currency for LLMs, positioning data vendors well in this new cycle
• BofA survey (150 IT professionals) suggests best of breeds (MDB, SNOW and Databricks) seeing highest expected growth in spend

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BofA analyst Justin Post expects server and equipment capex for mega-cap internet companies (Amazon, Alphabet/Google, Meta/Facebook) to rise 43% y/y in 2024 to $145bn, which represents $27bn of the $37bn y/y total capex growth. Despite the spending surge, Mr. Post thinks these companies will keep free cash flow margins stable at 22% y/y before increasing in 2025.  The technical infrastructure related capex spend at these three companies is expected to see steep rise in 2024, with the majority of the increase for servers and equipment. 

Notes:

• Alphabet categorizes its technical infrastructure assets under the line item ‘Information Technology Assets‘
• Amazon take a much a broader categorization and includes Servers, networking equipment, retail related heavy equipment & fulfillment equipment under ‘Equipment‘.
• Meta gives more details and separately reports Server & Networking, and Equipment assets.

In 2024, BofA estimates CAPEX for the three hyperscalers as follows:

• Alphabet‘s capex for IT assets will increase by $12bn y/y to $28bn.
• Meta, following a big ramp in 2023, server, network and equipment asset spend is expected to increase $7bn y/y to $22bn.
• Amazon, equipment spend is expected to increase $8bn y/y to $41bn (driven by AWS, retail flattish). Amazon will see less relative growth due to retail equipment capex leverage in this line.

 On a relative scale, Meta capex spend (% of revenue) remains highest in the group and the company has materially stepped up its AI related capex investments since 2022 (in–house supercomputer, LLM, leading computing power, etc.). We think it‘s interesting that  Meta is spending almost as much as the hyperscalers on capex, which should likely lead to some interesting internal AI capabilities, and potential to build a “marketing cloud“ for its advertisers.

From 2016-22, the sector headcount grew 26% on average. In 2023, headcount decreased by 9%.  BofA expects just 3% average. annual job growth from 2022-2026. Moreover, AI tools will likely drive higher employee efficiency, helping offset higher depreciation.

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Source for all of the above information:  BofA Global Research