As the pace of artificial intelligence acquisitions quickens – and the pool of acquirers expands – here are the companies leading the AI charge.
Artificial intelligence has long been a major focus for tech leaders across industries. Big corporations across every sector, from retail to agriculture, are trying to integrate machine learning into their products. At the same time, there is an acute shortage of AI talent. This combination is fueling a heated race to scoop up top AI startups, many of which are still in the early stages of research and funding.
Below, we dig into AI acquisition trends, from which companies are the most acquisitive to what areas of focus are attracting the most attention. Leading the race for AI are tech giants like Facebook, Amazon, Microsoft, Google, & Apple (FAMGA), all aggressively acquiring AI startups in the last decade. Among the FAMGA companies, Apple leads the way, making 20 total AI acquisitions since 2010. It is followed by Google (the frontrunner from 2012 to 2016) with 14 acquisitions and Microsoft with 10.
Apple’s AI acquisition spree, which has helped it overtake Google in recent years, was essential to the development of new iPhone features. For example, FaceID, the technology that allows users to unlock their iPhone X just by looking at it, stems from Apple’s M&A moves in chips and computer vision, including the acquisition of AI company RealFace. In fact, many of FAMGA’s prominent products and services came out of acquisitions of AI companies — such as Apple’s Siri, or Google’s contributions to healthcare through DeepMind.
Tech giants are not the only companies snatching up AI startups. Since 2010, there have been 635 AI acquisitions, as companies aim to build out their AI capabilities and capture sought-after talent . The pace of these acquisitions has also been increasing. AI acquisitions saw a more than 6x uptick from 2013 to 2018, including last year’s record of 166 AI acquisitions — up 38% year-over-year. In 2019, there have already been 140+ acquisitions, putting the year on track to beat the 2018 record at the current run rate.
Part of this increase in the pace of AI acquisitions can be attributed to a growing diversity in acquirers. Where once AI was the exclusive territory of major tech companies, today, smaller AI startups are becoming acquisition targets for traditional insurance, retail, and healthcare companies. For example, in February 2018, Roche Holding acquired New York-based cancer startup Flatiron Health for $1.9B — one of the largest M&A deals in artificial intelligence.
Despite the increased number of acquirers, tech giants are still leading the charge. Acquisitive tech giants have emerged as powerful global corporations with a competitive advantage in artificial intelligence, and startups have played a pivotal role in helping these companies scale their AI initiatives.
Retail & CPG topped all other industries in the number of AI acquisitions (67 since 2010), due to record-level M&A activity last year. These acquisitions have added AI-driven customer analytics, in-store inventory management, and personalized e-commerce experiences to retailer’s capabilities. Recent examples include McDonald’s $300M acquisition of personalization platform Dynamic Yield, Ulta Beauty’s acquisitions of virtual makeover startup GlamST and customer engagement software company QM Scientific, and Nike’s acquisitions of inventory management company Celect and guided shopping experience platform Invertex.
The Speech, NLP/(G), and Computer Vision category, which includes startups working on computer vision and natural language processing, has seen 66 acquisitions since 2010. Large tech companies have scooped up smaller startups in this category to boost their internal AI R&D. For example, Apple acquired facial recognition firm RealFace and voice assistant startup Novauris Technologies, Google acquired human-computer interaction company Api.ai, and Microsoft acquired speech recognition & NLP startup Semantic Machines and voice assistant company Maluuba.
The race has just begun.
Here is a puzzle for AI. When you accumulate the understanding of why a pizza is baked round, put in a square box, and eaten in triangles, you’ll probably be able to understand women