Top 8 Biggest AI Acquisitions of 2021

Illustration of AI text in light blue with multiple connections like in a neural network surrounding it on a dark blue background.
The rise of AI technology.

Artificial intelligence (AI) helps automate repetitive tasks comprising large datasets. This makes it beneficial in many diverse fields and business environments. This has led the demand for such solutions to rise. It’s also driving AI acquisitions as businesses attempt to streamline their workflows. 

In this article, you’ll learn about the 8 biggest AI acquisitions from 2021. Getting to know about them will help you be better positioned to pick the right solution. 

First, though, let’s find out how close we are to reaching the AI utopia, artificial general intelligence (AGI), or sentience. By knowing the state-of-the-art, you can better appreciate AI acquisitions.

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How Close Is AI to Achieving AGI?

AGI is an intriguing concept where an AI program can evaluate, compute, and work on tasks with human-level intellectuality. Despite technological advancements, AGI is still in its infancy. This is because it’s almost impossible to replicate the human brain. This doesn’t stop developers, though, from trying to replicate human intelligence

The coming decade will play a crucial role in accelerating AGI development. In general, experts believe the industry has a 25% chance of achieving AGI by 2030. The current limitations in AGI are due to the lack of working protocols and developers. That said, seamless data sharing will help produce a decentralized development process. This will, in time, likely yield the first true AGI. 

For now, companies remain unsure how to integrate AI in business operations. To help you, let’s look at some of AI’s major use cases.

AI Applications

Though we haven’t reached AGI yet, the growth in AI technology represents a significant step forward. Computers can now become more human-like and perform complex or risky tasks. Here are some common use cases of AI technologies for you to see why companies are looking to conclude AI acquisitions:

1. Natural Language Processing 

This involves analyzing any text or user-generated content to determine the intended meaning. This is particularly useful for handwritten text. First, imaging hardware collects data, and then the matrix filters define each character. After, the AI compares the words against a dictionary and rationalizes meanings. This is useful when handwriting isn’t clear and it’s difficult to detect characters correctly. In this case, the fundamental technology is easy to develop, and an AI acquisition’s value increases with extended features. For example, some upgrades include solutions working in low light or smarter features.  

2. Computer Vision

This AI form handles object recognition to understand the real world. Sensory input in real-time is possible due to remote AI processing. In this case, some applications include driverless cars that process data in onboard computers. You can also apply the technology in multi-sensor systems working with LIDAR. In this context, optical inputs also add value to AI acquisitions.

3. Conversational AI

AI, in this case, relates to conducting a natural conversation with a user by understanding context. These systems are useful for chatbots but need much work still. That’s because the added value for these systems is to understand the context correctly. In turn, it would decide what to say or do next. 

Since these features are still in their development stage, acquisitions help startups fund research and development. It also helps acquirers achieve their ambitions. Let’s discover the biggest AI acquisitions of 2021 and the synergies they created. 

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Artificial Intelligence is catching up to human intelligence.

8 Biggest AI Acquisitions of 2021

AI startups have become a prime target for large companies that want to leverage a specific AI and ML solution. The pace of AI acquisitions is also increasing as companies optimize their workflows. Let’s look at the 8 major AI acquisitions that happened in 2021:

1. Panasonic Corp Acquired Blue Yonder

Panasonic Corp bought Blue Yonder for $7.1 billion in September 2021. The deal comes after Panasonic bought a 20% stake in the company in 2020. 

Blue Yonder provides end-to-end supply chain platforms. In effect, Blue Yonder’s AI commerce solutions will pair with Panasonic’s sensing technologies. This will deliver Panasonic’s and Blue Yonder’s shared idea for an autonomous supply chain solution. 

This pairing can also create more innovative and connected e-commerce strategies. In this case, Panasonic can apply AI to checkout-less payment systems for retail stores. It can also ensure warehouse inventory is correct in real-time without worker data entry. The Panasonic-Blue Yonder acquisition deal comes as integrated supply chains grow; reducing waste.

2. Hewlett Packard Enterprise Acquired Determined AI

Hewlett Packard Enterprise (HPE) acquired Determined AI, a San Francisco startup, in June 2021. The latter creates an open-source AI platform for building machine learning models. This is useful as its open-source ML platform will help HPE remove complexity and make production time faster. In this move, HPE will empower developers, combining the ML platform with its high-performance computing (HPC). In turn, developers can build AI solutions at a much larger scale than before. 

3. Relativity Acquired Text IQ

Relativity, a global legal and compliance tech company, acquired Text IQ, an AI company, on May 27, 2021. Text IQ is a B2B technology company that uses AI to manage and mitigate risks in enterprise data. It also employs natural language processing to search for the most relevant data to a legal case. In this context, Relativity now can embed AI technologies within its core platform. What does Relativity have in mind? It may be specifically aiming to ensure security and compliance as AI goes mainstream. 

4. Atlassian Acquired Chartio

Australian software company, Atlassian, completed Chartio’s, a cloud-based business intelligence and analytics solution, acquisition in February 2021. The goal was to add data analysis and visualization components to the company’s offerings. This move will also bring data visualization to the Atlassian platform, starting with Jira. For Atlassian customers, Chartio’s visualization capabilities will brighten up the user experience.

5. Nano Dimension Acquired Deepcube

Nano Dimension, an industry-leading 3D-Printed Electronics provider, acquired DeepCube. They finalized the deal in April 2021, comprising roughly $40 million in cash and $30 million in Nano Dimension’s American Depositary Shares (ADSs). DeepCube AI/ML/DL solutions use many patented algorithms to improve data analysis. In effect, Nano Dimension will benefit from 3D print validation and process control. 

6. Autodesk Inc. Acquired Innovyze Inc.

Autodesk acquired Portland, Oregon-based Innovyze, Inc., for $1 billion in February 2021. Innovyze supplies water infrastructure design software. This AI acquisition positions Autodesk as a leader in end-to-end water infrastructure solutions. 

Specifically, Innovyze’s simulation and modeling solutions provide Autodesk with better simulation tools. This helps end-users design more cost-effective and sustainably designed water collection systems. It also makes flood protection, water management, and wastewater treatment plant optimization possible. These use cases are essential in the construction industry, where water distribution networks are critical. 

7. AWS Acquired Wickr

AWS acquired Wickr, an end-to-end encrypted communication technology provider, in June 2021. This provides advanced security benefits to customers, unavailable elsewhere. If you’re an AWS customer, keep an eye out for this service on the AWS platform.

8. Accenture Acquired Umlaut

Accenture bought Umlaut on Oct. 1, 2021, an engineering consulting and services company based in Achen, Germany. This deal will integrate 4,200 industry-leading engineers into Accenture’s Industry X services. In this case, the move dramatically scales Accenture’s deep engineering capabilities. For Umlaut customers, Accenture will open up new possibilities to deepen their relationship.

That’s quite an active M&A market! This table will help you put the deals into perspective and compare them.  

Acquiring companyAcquired company Date of AcquisitionPrice of AcquisitionKey TechnologyStartup YearStartup Country
Panasonic CorpBlue YonderSept 17, 2021$7.1 billiondigital fulfillment platform provider2017United States
H.P.Determined AIJune 21, 2021Machine learning models2017United States
RelativityText IQMay 27, 2021 mitigate risks in enterprise data2014United States
AtlassianChartioFeb 26, 2021Business intelligence and analytics solution2010United States
Nano DimensionDeepcubeApril 20, 2021 $40Mcash &  $30Min sharesdata analysis2017Israel
AutodeskInnovyzeFeb. 24, 2021$1 billion net of cash Water infrastructure programming1996United States
AWSWickrJune 24, 2021 Communication technology2011United States
AccentureUmlautOct. 1, 2021Engineering consulting and services 1996Aachen, Germany
AI’s wide application universe is getting center stage.

As we’ve seen, AI and ML-based startups are turning to larger companies since they find it hard to raise capital to scale their operations. At the end of the day, they secure a great exit strategy and larger companies get the technology they need to achieve their goals.

Final Thoughts

Interestingly, the use of AI-based tools and solutions isn’t limited to big tech companies anymore. In fact, small startups are harnessing AI’s potential to innovate, scale up, and remain competitive. Clearly, it’s been a busy and productive year for AI startups and enterprises. That has led the industry to also register many large-scale AI acquisitions. It’s because many companies view AI as the way of the future, and this future looks bright. Next-generation technologies, like AI, will play a pivotal role in business growth. 

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What is Artificial Intelligence (AI)?

Artificial intelligence (AI) refers to systems that mimic human intelligence to perform tasks. It uses an iterative learning process to improve systems, which reduces errors with time. Some use-cases include AI chatbots which mimic human interaction to help keep users engaged. Another use is in applications for processing large datasets in repetitive operations to improve productivity. Finally, recommendation engines can benefit from AI to suggest products or offerings based on user habits, like in online shopping.

How do I know if Artificial Intelligence (AI) is right for my business?

You want to look for time-consuming and repetitive data processing tasks. AI is effectively an automation tool you can use for sensory data, like in process control. It can also handle your database activities, like creating dynamic user suggestions. No matter your intent, you’ll want to make sure AI’s addition results in a positive ROI, or else, you won’t find it a financially sound choice. 

How powerful is Artificial Intelligence (AI)?

AI is a weighted matrix, the more nodes the more powerful AI is at simulating real-world tasks. That said, the more intricate the matrix the more time it takes to run. This is a problem for lightweight platforms that can’t cope with the ideal matrix design. In that sense, you should aim to achieve a balance between performance and error resolution

Will Artificial Intelligence (AI) steal your jobs?

AI stealing jobs is a myth. Bottom line, it’s an automation and productivity tool. You can only use it as a statistical weighting tool for repetitive decision-making tasks. It can’t think or rationalize. Instead, it only processes basic tasks rapidly. In essence, it’s creating jobs, not taking them away. According to Fortune, hiring AI specialists has grown by 74% over the last four years. The demand for skilled AI developers is also reflecting a change in business practices

Should we trust Artificial Intelligence (AI)?

AI is only a statistical decision-making tool. You feed it data and it automates the specific task at scale. It’s like your calculator; you feed it numbers and it performs the calculation. For trust, you need to ensure you use quality software. You also need to feed it correct data. Now, that’s easier said than done. 


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