This report delves into the adoption of ML and Data Science Platforms by the Global Top 100 companies, both privately-held and publicly-traded, as ranked by size, including employee count and revenue metrics, such as those found in the Fortune 1000 and Global 2000 listings. We explore how these leading enterprises are leveraging ML and Data Science to pursue strategic goals and drive lasting benefits across various business functions.
The adoption of ML and Data Science within these top companies reveals significant investments in ML technology, highlighting a broad and diverse approach. These organizations frequently partner with multiple vendors, integrating complementary ML and Data solutions to achieve their business objectives. This multi-vendor approach allows them to tailor ML and Data Science deployments that drive competitive advantages, operational efficiencies, and overall sustainability.
Our latest findings detail the software purchases related to ML and Data Science platforms among these top 100 enterprises, their technology investments span a range of ML tools and solutions, underscoring the complexity of ML and Data Science adoption at this level.
ML and Data Science Vendors Among the Global Top 100
Amazon Web Services (AWS) currently holds a 15% market share in the ML and Data Science space, making it the leading provider among the Global Top 100, followed by Microsoft Azure, Google Cloud, SAP Leonardo, and H2O.ai.
Source: APPS RUN THE WORLD, 2024
The insights derived from our research will empower marketers, product managers, and IT professionals to better understand the adoption trends shaping the future of ML and Data Science. These trends can potentially lead to significant shifts within the competitive landscape, impacting strategies and market positioning for years to come.
By monitoring these top enterprises and their technology choices, we equip our clients with the knowledge needed to anticipate changes and stay ahead in the rapidly transforming world of enterprise software and ML innovation.
Custom data cuts related to the ML and Data Science Platforms Market are available:
- Top ML and Data Science Vendors, Market Size and Market Forecast 2023-2027
- ML and Data Science Platforms Market By Vertical Market (21 Industry)
- ML and Data Science Platforms Market By Country (USA + 45 countries)
- ML and Data Science Platforms Market By Region (Americas, EMEA, APAC)
- ML and Data Science Platforms Market By Customer Size (revenue, employee count, asset)
- ML and Data Science Platforms Market By Channel (Direct vs Direct)
- ML and Data Science Platforms Market By Vendor or Product
Global Top 100 adopting ML and Data Science Platforms
The influence of these top 100 organizations on the broader AI market is profound, despite their representation of only a small segment of the digital transformations we track annually. These companies often serve as early adopters and trendsetters, shaping the future of AI and driving innovations that impact the industry at large.
Our Buyer Insight Technographics Database provides a closer look at these major organizations, capturing the size and intricacy of their IT stacks, along with the frequency of their technology investments. This unique database reveals patterns in AI adoption and highlights emerging trends, which are crucial for understanding the evolving landscape of ML and Data Science Platforms.
Our research team continuously tracks the adoption of various ML and Data Science platforms, drawing on both publicly available information, such as press releases and case studies, and proprietary data sources. Each quarter, we update our records to reflect new AI implementations, providing clients with current and relevant insights into market shifts.
Here are the Global Top 100 companies and their adoption of ML and Data Science platforms
Source: APPS RUN THE WORLD, October 2024
Research Methodology
Each year our global team of researchers conduct an annual survey of thousands of enterprise software vendors by contacting them directly on their latest quarterly and annual revenues by country, functional area, and vertical market. We supplement their written responses with our own primary research to determine quarterly and yearly growth rates, In addition to customer wins to ascertain whether these are net new purchases or expansions of existing implementations.
Another dimension of our proactive research process is through continuous improvement of our customer database, which stores more than ten million software purchases and records on the enterprise software landscape of over 2 million organizations around the world.
The database provides customer insight and contextual information on what types of enterprise software systems and other relevant technologies are they running and their propensity to invest further with their current or new suppliers as part of their overall IT transformation projects to stay competitive, fend off threats from disruptive forces, or comply with internal mandates to improve overall enterprise efficiency.
The result is a combination of supply-side data and demand-generation customer insight that allows our clients to better position themselves in anticipation of the next wave that will reshape the enterprise software marketplace for years to come.
