Technology
Visualizing Major Tech Acquisitions (1991-2018)
Launch the interactive version below, or go to our story for simpler, static images
Interactive: Visualizing Major Tech Acquisitions (1991-2018)
To stay successful in tech, companies must find a way to walk alongside the cutting edge of innovation.
Companies do this partially by devoting a large portion of their resources towards research and development (R&D) – but to hedge their bets, these companies also are in constant negotiations to gobble up new startups that could be strategic to their futures.
In this giant game of Pac-Man, most of the acquisitions are small and sequential, just like the dots that make up the arcade game’s classic maze. That said, sometimes these tech giants get lucky, such as in Facebook’s acquisition of Instagram, and buyouts turn into power-ups that can change the dynamics of the game entirely.
Tech Acquisitions by Company
Today’s interactive infographic comes to us from IG and it allows you to compare the tech acquisitions made by dominant companies such as Facebook, Apple, IBM, or Cisco.
Acquisitions can be sorted by industry filters (i.e. e-commerce, security, etc.) and different acquiring companies can be switched in. There are also different tabs that show total M&A expenditures by company, M&A activity by CEO, and frequency of acquisitions measured in quantity per year.
The Big Picture
Before we go into specific acquisitions, let’s look at the big picture using images pulled from the interactive version of the graphic.
Here is a comparison of the number of acquisitions made since 1991, for each major company on the list:
Google has made the most acquisitions, averaging about 10 to 11 per year. That adds up to a total of 214 since the company was founded.
Interestingly, while Google has had the most acquisitions, it only ranks in 6th out of this group in terms of dollars spent. Giants like Microsoft, Cisco, and IBM may make fewer acquisitions, but the companies they do buy tend to be more established with higher valuations.
As an example of this: Microsoft bought LinkedIn in 2016 for $26.2 billion. That’s more than Amazon has spent on all of its acquisitions (including Whole Foods) combined.
The Big Five
Finally, here’s a comparison of the big five – Amazon, Apple, Microsoft, Facebook, and Google (Alphabet) – which are also the five largest companies by market capitalization in the United States.
On the interactive version, it’s possible to highlight each acquisition to get the deal value and company name.
But, even on the static version above, it’s noticeable that each of the Big Five has made at least one real sizable acquisition. Those are the circles that stand out the most on the timeline:
- 2011: Google buys Motorola for $12.5 billion
- 2014: Facebook buys WhatsApp for $19 billion, and Apple buys Beats for $3 billion
- 2016: Microsoft buys LinkedIn for $26.2 billion
- 2017: Amazon buys Whole Foods for $13.7 billion
The gobbling activity for these Big Five has continued into 2018, as well.
In fact, just in June 2018, Microsoft announced the acquisition of code repository GitHub for $7.5 billion. The deal is expected to close by the end of the year.
AI
Visualizing the Top U.S. States for AI Jobs
Nearly 800,000 AI jobs were posted in the U.S. throughout 2022. View this graphic to see a breakdown by state.

Visualizing the Top U.S. States for AI Jobs
Much ink has been spilled over fears that artificial intelligence (AI) will eliminate jobs in the economy. While some of those fears may be well-founded, red-hot interest in AI innovation is creating new jobs as well.
This graphic visualizes data from Lightcast, a labor market analytics firm, which shows how many AI-related jobs were posted in each state throughout 2022.
In total there were 795,624 AI jobs posted throughout the year, of which 469,925 (59%) were in the top 10. The full tally is included in the table below.
Rank | State | Number of job postings | % of total |
---|---|---|---|
1 | California | 142,154 | 17.9% |
2 | Texas | 66,624 | 8.4% |
3 | New York | 43,899 | 5.5% |
4 | Massachusetts | 34,603 | 4.3% |
5 | Virginia | 34,221 | 4.3% |
6 | Florida | 33,585 | 4.2% |
7 | Illinois | 31,569 | 4.0% |
8 | Washington | 31,284 | 3.9% |
9 | Georgia | 26,620 | 3.3% |
10 | Michigan | 25,366 | 3.2% |
11 | North Carolina | 23,854 | 3.0% |
12 | New Jersey | 23,447 | 2.9% |
13 | Colorado | 20,421 | 2.6% |
14 | Pennsylvania | 20,397 | 2.6% |
15 | Arizona | 19,514 | 2.5% |
16 | Ohio | 19,208 | 2.4% |
17 | Maryland | 16,769 | 2.1% |
18 | Minnesota | 11,808 | 1.5% |
19 | Tennessee | 11,173 | 1.4% |
20 | Missouri | 10,990 | 1.4% |
21 | Oregon | 10,811 | 1.4% |
22 | Washington, D.C. | 9,606 | 1.2% |
23 | Indiana | 9,247 | 1.2% |
24 | Connecticut | 8,960 | 1.1% |
25 | Wisconsin | 8,879 | 1.1% |
26 | Alabama | 7,866 | 1.0% |
27 | Kansas | 7,683 | 1.0% |
28 | Arkansas | 7,247 | 0.9% |
29 | Utah | 6,885 | 0.9% |
30 | Nevada | 6,813 | 0.9% |
31 | Idaho | 6,109 | 0.8% |
32 | Oklahoma | 5,719 | 0.7% |
33 | Iowa | 5,670 | 0.7% |
34 | South Carolina | 4,928 | 0.6% |
35 | Louisiana | 4,806 | 0.6% |
36 | Kentucky | 4,536 | 0.6% |
37 | Nebraska | 4,032 | 0.5% |
38 | Delaware | 3,503 | 0.4% |
39 | New Mexico | 3,357 | 0.4% |
40 | Rhode Island | 2,965 | 0.4% |
41 | New Hampshire | 2,719 | 0.3% |
42 | Hawaii | 2,550 | 0.3% |
43 | Mississippi | 2,548 | 0.3% |
44 | Maine | 2,227 | 0.3% |
45 | South Dakota | 2,195 | 0.3% |
46 | Vermont | 1,571 | 0.2% |
47 | North Dakota | 1,227 | 0.2% |
48 | Alaska | 970 | 0.1% |
49 | West Virginia | 887 | 0.1% |
50 | Montana | 833 | 0.1% |
51 | Wyoming | 769 | 0.1% |
The following chart adds some context to these numbers. It shows how the percentage of AI job postings in some of the top states has changed since 2010.
We can see that California quickly became the primary destination for AI jobs in the early 2010s, presumably as Silicon Valley companies began developing the technology.
California’s share has since declined, with a significant number of jobs seemingly moving to Texas. In fact, many tech companies are relocating to Texas to avoid California’s relatively higher taxes and cost of living.
The 10 Most In-Demand Specialized Skills
Lightcast also captured the top 10 specialized skills that were required for AI-related jobs. These are listed in the table below.
Skill | Frequency (number of postings) | Frequency (% of postings) |
---|---|---|
Python | 296,662 | 37% |
Computer Science | 260,333 | 33% |
SQL | 185,807 | 23% |
Data Analysis | 159,801 | 20% |
Data Science | 157,855 | 20% |
Amazon Web Services | 155,615 | 19% |
Agile Methodology | 152,965 | 19% |
Automation | 138,791 | 17% |
Java | 133,856 | 17% |
Software Engineering | 133,286 | 17% |
If you’re interested in a career that focuses on AI, becoming proficient in Python is likely to be a good first step.
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