The Race for AI Company Acquisitions: Why It's Happening, and Its Lessons for You
Acquisitions have been a long-standing strategy companies use for a wide range of reasons. Some companies acquire others because of strategic benefits like access to a new market, product or service. Others do it to achieve economies of scale, leverage synergies or diversify their portfolios. Also, an acquisition can be a reaction to specific market changes in order to remain competitive, or a means of protecting existing market share.
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Every industry has experienced acquisition activity -- and that includes emerging business segments. More acquisitions tend to appear when the market starts to realize that a particular segment is offering new revenue opportunities. That’s why numerous niches in technology have become the target of increased acquisition activity in recent years.
The most recent technology niche in the acquisitions races? Artificial intelligence (AI): More than 250 private companies that use AI algorithms across different verticals have been acquired since 2012, with 37 acquisitions taking place in the first quarter of 2017, according to CB Insights.
There are many reasons why the area of AI is ripe for acquisition activity -- and why so many candidates are now being eyed for acquisition. Here are some of those reasons:
Driving factors for AI growth
There are many reasons why AI is growing and showing up in more industries, niches, and applications. The explosion of big data and interest in it have created a need for technology solutions to control, organize and analyze all this information. Companies are now generating huge amounts of data. And this requires a fast and accurate way to understand the data for more effective business decisions and solutions that address competitive pressure.
AI also helps to provide an enhanced customer experience, while offering inexpensive parallel processing power and increased adoption of smart devices.
The competitors in the AI race
The companies behind these AI acquisitions are tech giants that want to reinforce their leadership position in artificial intelligence. At the very least, they are looking to make up for lost ground. Google is the most active acquirer, with 12 acquisitions since 2012. In second place is Apple, with eight acquisitions.
Related: 4 Lesser-Known Ways Artificial Intelligence Is Changing Business Today
Next on the list are Intel, Microsoft and Facebook. Intel acquired three startups in 2016 alone, including Itseez, Nervana Systems, and Movidius. Recently, Facebook acquired Masquerade Technologies and Zurich Eye. Microsoft has also been busy, acquiring Genee and Maluuba. Google's parent company, Alphabet, has completed six acquisitions since 2014.
Other tech brands are also following suit. For example, Amazon bought Graphiq, Harvest.ai, Angel.ai, and Orbeus. BOX acquired Wagon Analytics and Greply while Dropbox purchased Clementine Labs, and Predictive Edge Technologies. IBM recently acquired Expert Personal Shopper, AlchemyAPI, Cognea, and Vivisimo.
Finally, even non-tech companies are getting into AI. Ford Motor Company invested $1 billion in Argo AI in 2017. This AI startup was founded by former executives that were on self-driving teams at Google and Uber.
AI companies on the acquisition radar
Numerous AI companies are on the watch list for being possible acquisition targets by these tech giants and major brands. Here are some of these potential acquisition candidates:
Clarifai. Clarifai specializes in image and video recognition. It automatically tags all your images and video so you can quickly organize, manage and search through content. The user can teach the platform to recognize new concepts with only a handful of data examples. It can then create a custom model for unique cases.
Google and Nvidia are notable investors. Clarifai's customers include Buzzfeed and Unilever. It has been approached about a dozen times by prospective acquirers since it launched in late 2013.
SparkCognition. SparkCognition has proprietary classification and prediction algorithms that collect large amounts of sensor data and transfer it into actionable insight. It offers support root-cause analysis along with a cognitive layer in the form of its DeepArmor deep machine learning anti-malware software. It can simulate most of what a human security analyst can do, but it does so at machine speed and Big Data scale. This enables it to provide predictive threat intelligence for users.
With this type of proprietary technology, this AI company has the potential to create a bidding war among companies that recognize the unique value of this technology.
Textio. Textio is an augmented writing platform for creating highly effective job listings. It takes more than 10 million job posts each month and analyzes the hiring outcomes of those jobs. From this analysis, the AI platform can predict how your listing will do and offer recommendations on how to improve it. Its AI solution has proved valuable to clients like Cisco and Johnson & Johnson, as they use it to recruit better talent.
Textio has raised $20 million in new funding led by Scale Venture Partners and existing investors, such as Bloomberg Beta, Cowboy Ventures, Emergence Capital and Upside Partnership. This level of funding illustrates the value the company has for others interested in using it for many applications.
Findo. Findo emerged with a tool that could provide smart search capability for management. Natural language processing and machine learning give teams a way to find documents without using keywords. The AI-enabled tool can sift through massive amounts of personal and corporate data to find what users describe in their own words. Findo now has other features that extend their value.
Yva Task Assistant is an AI-driven “invisible” task assistant that identifies the who, what, when and status for tasks found within emails and message. Once it locates those, it then generates task lists and reports. The AI tool also sends reminders about important tasks as a web app and a mobile app.
There is more on the horizon for Findo. In the future, it plans to release Team Performance Supervisor. The objective is to create more efficient HR management by providing a way to identify employee issues before the company loses its best employees. The tool can also help managers see who is being less productive and who is excelling.
X.ai. X.ai has a virtual assistant, "Amy," which helps schedule meetings for users. All you need to do is copy Amy into the email and the technology virtually schedules meetings. Using machine learning and natural language processing, Amy schedules the best time and location for your meeting based on your preferences and schedule. It also provides a way to bring structure to a significant amount of unorganized data.
With so many companies looking to add structure to their data, this tool would offer numerous ways to achieve that goal.
Zoox. Zoox is a robotics company that has pioneer autonomous mobility-as-a-service. It is developing a fully automated electric vehicle fleet along with the supporting ecosystem necessary to scale it for the market. Staffed by some past Apple employees, Zoox has received considerable amounts of funding. So far, seven investors have provided $290 million over the course of two rounds of funding.
The autonomous vehicle industry is expanding and becoming more mainstream, putting Zoox in a good position to be acquired for its capabilities.
Bloomreach. BloomReach is an open, intelligent Digital Experience Platform (DXP). Operating within the cloud, it analyzes big data to help clients identify relevant content through search engines. Applications include content management, SEO, role-based analytics, site search and page management. BloomReach has proven itself working for companies like Staples, Autodesk, Mailchimp, REI, and Neiman Marcus.
The company has raised $97 million in four rounds from six investors. There is more interest already in the wings.
Numer.ai. Numer.ai is a hedge fund that is framed by an artificially intelligent system that chooses all the trades. Since Numer.ai abstracts its financial data, data scientists do not know what the data represents. Therefore, human biases and overfitting are overcome. It also encrypts its trading data before sharing it with the data scientists.
This strategy prevents fund managers from mimicking the fund's trades. Yet, the encrypted data is also organized in a way that enables data scientists to build models that can potentially improve trades.
With so many opportunities converging on the investment industry, this solution could not have appeared at a better time.
Motion.ai. Motion.ai is a chatbot-building platform that relies on natural language processing to bring the bots to life. Companies like SONY, Wix.com, KIA, and T-Mobile are already using this chatbot. The benefits include integration with Messenger, SMS, Slack and email. The company has enterprise solutions. It also provides a team that works with a company’s inner resources to further enhance its features list.
Chatbots are one of the hottest growth areas, so this company could potentially provide a larger enterprise with the capability in this area they are seeking.
Fuzzy Logix. Fuzzy Logix speeds the process for getting intelligence from large structured datasets. Its DB Lytix product works within existing databases to perform predictive analytics. The process does not require data export. It takes only hours rather than days. The company has been able to improve cross-company forecasting and deliver analytic solutions to multiple divisions of Fortune 500 companies and across industries like finance, retail, health care and manufacturing.
With the ability to help so many with a unique solution, Fuzzy Logix is one of the most attractive AI acquisition candidates out there.
Prospectify. Prospectify offers intelligence for data-driven revenue teams. It uses machine learning to predict the right emails for outdated contacts on your prospect list. In this way, you can clean up your list and automate the process of lead generation. Prospectify also enables quicker scoring and qualifying, critical context and timely alerts for crucial trigger events.
Numerous companies with sales issues are struggling, so this solution would provide an attractive feature to their toolbox and give them a competitive edge.
Acquisitions predicted to boom
The rest of 2017 and into 2018 will likely be an exciting time for artificial intelligence, natural language processing and machine learning. New applications, tools and platforms will emerge while others will integrate and assimilate into other organizations to meet those company's needs.
Lessons for entrepreneurs
AI startups will enjoy many opportunities as businesses and consumers realize the value it delivers. And even for startups not in the AI environment, this boom in acquisitions has three lessons to teach:
First, always be aware of what is happening within your industry and those impacted by it. This means paying attention to trends and shifts in preferences so you can be prepared to pivot in order to maintain the value you are adding to your audience and to any companies that might consider acquiring you.
Second, a startup must always have an exit strategy in mind. While it may seem unrealistic to be thinking of the potential end to your connection to a business that you are only ramping up, the reality is that you need to be prepared to move on. Acquisitions are one of the most attractive exit strategies. Depending on the situation, you may be able to get a complete buyout or retain a portion of the company and a leadership position.
Third, know what you want should you be approached by a company interested in acquiring your business. Seek advice from legal team and other business advisors who have participated in acquisitions, so they can help shape your response, negotiation and transaction.
Related: With Whole Foods Purchase, Amazon Just Bought a Playground for Big Data
Overall, the AI industry’s boost in acquisitions illustrates just how important disruptive companies are to existing and established ones. When looking to create your own startup, focus on how you can generate that value by doing something completely different.
The AI startups listed here all started by recognizing a significant gap and the demand for what they could offer. Do the same: Take the time to develop that angle, and you’ll be part of your own acquisition race.