The market is ripe for more AI M&A deals as enterprise demand for AI talent, MLOps and vertical applications rose during the pandemic.
By
Paula Rooney
Published: 09 Jun 2021
Microsoft's $20 billion deal to buy Nuance, DataRobot's acquisition of Zepl and Smart Eye's purchase of Affectiva -- all over the last two months -- are harbingers of an anticipated wave of mergers and acquisitions in the AI software market this year and next.
"There's definitely more deals ahead. The maturity timeframe for AI has been accelerated, right in line with the acceleration of digital transformation plans due to the pandemic," said Fred McClimans, technology and equity analyst at Futurum Research. "Developing AI-based technology is not cheap or fast, and most tech providers will find it more efficient and effective to acquire rather than develop in-house."
In the first half of 2021, the pace has picked up considerably, with Panasonic's $7.1 billion deal to buy Arizona-based Blue Yonder, BigBear.ai's merger with GigCapital4, IBM's acquisition of Turbonomic and People.ai's purchase of Hero Research among the most notable deals. In the robotic process automation sector of the AI market, ServiceNow's acquisition of LightStep and UiPath's purchase of Cloud Element contributed to the increased pace of M&A activity.
AI latest sector seeing M&A action The ferment in the AI software market comes as other tech sectors are also undergoing dramatic consolidation, with analytics and data management vendors acquiring tech companies to broaden and complement their own platforms. It also reflects a certain maturity in the AI sphere as startups have developed their technologies to the point at which they are commercially viable but need a more powerful go-to-market player to financially actualize their AI products.
The merger and acquisition activity puts pressure on vendors to get their AI products and platforms in order -- and that is not so easy for an industry still not long out of its infancy.
"Acquisitions to acquire technology, or time to market, and customers, or market share, are both likely to increase over the coming 18 to 24 months," McClimans said.
Developing AI-based technology is not cheap or fast, and most tech providers will find it more efficient and effective to acquire rather than develop in-house.
Fred McClimansTechnology and equity analyst, Futurum Research
"A lot of these acquisitions are about purchasing talent. AI researchers and engineers are rare and expensive, and I've heard of instances where acquisition prices are based on the engineering headcount, particularly for younger companies," said Chris Shipley, a partner in CR Strategy Partners and investor in Sherpa.ai, an AI vendor in Bilbao, Spain.
"AI, of course, isn't one technology but many areas of specialized engineering so the dipping of toes is largely dependent on a company's product ambitions," Shipley added. "Where AI was once esoteric, it's now gone mainstream, and I suspect companies of all stripes, not just pure tech companies, will be getting into the swim."
Microsoft-Nuance deal
Some might argue that Microsoft's acquisition of Nuance was not a pure AI buy because of its healthcare focus. But Nuance was one of the first developers of Siri for Apple, and the software company offers core ingredients for natural language processing, speech recognition, document processing, image recognition and AI expertise across all industries.
U.S. trade regulators approved Microsoft's mega deal to buy Nuance on June 4. Early last month, DataRobot acquired Zepl, an open source notebook for coders -- the AI vendor's eighth acquisition since 2017.
Two weeks later, Smart Eye, based in Sweden, which has developed driver monitoring systems for more than 20 years, acquired Affectiva, a vendor of automotive interior sensing systems.
Another analyst said these deals fall into the category of acquisition deals he sees coming in the months and years ahead.
Verticals
"M&A activity in the AI space is just getting started," said Mike Leone, an analyst at Enterprise Strategy Group. "I see two angles of M&A activity that are really working in parallel."
"The first is building out a complete AI lifecycle technology portfolio," Leone said. "The thing I would keep an eye on here is the MLOps space. The biggest headache for organizations today is deploying AI. And over the last year we've seen several new vendor offerings and several new companies introduce ways to simplify the deployment and management of machine learning models."
DataRobot's Zepl deal, for example, fits in here because it provides AI coders with an effective tool that to help them develop machine learning models.
The next group of targets will be AI specialists that target vertical markets, such as Affectiva, which develops AI-based computer vision technology mainly used in the auto industry, Leone said.
"The other area that I see a large opportunity for M&A activity is AI solution-based offerings," Leone said. "There are hundreds of extremely talented partners that focus on one or two AI use cases within a given vertical. It would not surprise me to see larger vendors start scooping up those small partners as they double down on bringing more specialized AI solutions to market."
Enterprise Strategy Group (ESG) is a division of TechTarget.
