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Imagining the Future of Design and Collaboration

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Imagining the Future of Design and Collaboration

Imagining the Future of Design and Collaboration

New technologies are getting adopted faster and faster.

In the modern business environment, it no longer takes multiple decades for new ideas to take root. Instead, thanks to increased connectivity, instantaneous communication, and big leaps in computing power, these new innovations can rise to prominence in much shorter time spans.

As these changes surface, companies can either help pioneer these new technologies – or they can be caught off guard by their impact on industry.

A Fundamental Shift

Today’s infographic comes to us from Schneider Electric, and it dives into the many technological forces that will be re-shaping the future of design and collaboration.

It touches on an exciting but uncertain future for industrial designers, architects, engineers, and other design-oriented industries, in which rising processing power and new technologies are re-wiring the fundamental relationship between the designer and the end product.

Almost certainly, these forces will shape a competitive landscape for the design industry that will seem almost completely unfamiliar over the next decade or so.

The Computational Era

Computer-aided design (CAD) has already revolutionized design, but it turns out that CAD only scratches the surface of what is possible with computers.

The rapid increase in processing power, the miniaturization of devices, new algorithms, and increased connectivity are leading to a new era of computational design.

Instead of designers using computers as a tool, computers are now able to generate insights, make creative leaps, and jump to decisions using massive data sets – and this will fundamentally change the designer’s role in the creative process.

In the future, designers will be more like mentors for computers by providing their guidance and experience.

The Forces Shaping Design

What do we mean when we say “computational design”?

Infinite computing
Tapping into cloud-based computing power to try thousands of design permutations.

Big data & predictive analytics
Using billions of data points and predictive analytics to create new or highly customized products.

Generative design
Computers mimic nature’s evolutionary approach to design.

AI / Machine learning
Designing a system that learns and adapts over time.

The Forces Shaping Collaboration

But how design is changing doesn’t stop there – how we collaborate on design is also undergoing a revolution:

AR/VR
Virtual collaboration can be achieved across the globe, allowing designers to work in parallel.

Cloud-based collaboration
Design is no longer siloed and can be democratized between different stakeholders. Further, teams can work simultaneously from all over the world.

Crowdsourcing
Input for design and specialized parts can be crowdsourced.

3d and 4d printing
Design and manufacturing can be integrated seamlessly, even to customize individual items. 4d printing is a new frontier where printed objects adapt to various circumstances.

An Uncertain Future

Data, computing power, and new tools are enabling a rapid transition in how we design and collaborate.

No one can be certain about how different the future of design and collaboration will be, or how it will affect business models – but for companies to remain relevant and competitive over the coming years, they will need to be watching this technological revolution very closely.

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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.

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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.

RankStateNumber of job postings% of total
1California142,15417.9%
2Texas66,6248.4%
3New York43,8995.5%
4Massachusetts34,6034.3%
5Virginia34,2214.3%
6Florida33,5854.2%
7Illinois31,5694.0%
8Washington31,2843.9%
9Georgia26,6203.3%
10Michigan25,3663.2%
11North Carolina23,8543.0%
12New Jersey23,4472.9%
13Colorado20,4212.6%
14Pennsylvania20,3972.6%
15Arizona19,5142.5%
16Ohio19,2082.4%
17Maryland16,7692.1%
18Minnesota11,8081.5%
19Tennessee11,1731.4%
20Missouri10,9901.4%
21Oregon10,8111.4%
22Washington, D.C.9,6061.2%
23Indiana9,2471.2%
24Connecticut8,9601.1%
25Wisconsin8,8791.1%
26Alabama7,8661.0%
27Kansas7,6831.0%
28Arkansas7,2470.9%
29Utah6,8850.9%
30Nevada6,8130.9%
31Idaho6,1090.8%
32Oklahoma5,7190.7%
33Iowa5,6700.7%
34South Carolina4,9280.6%
35Louisiana4,8060.6%
36Kentucky4,5360.6%
37Nebraska4,0320.5%
38Delaware3,5030.4%
39New Mexico3,3570.4%
40Rhode Island2,9650.4%
41New Hampshire2,7190.3%
42Hawaii2,5500.3%
43Mississippi2,5480.3%
44Maine2,2270.3%
45South Dakota2,1950.3%
46Vermont1,5710.2%
47North Dakota1,2270.2%
48Alaska9700.1%
49West Virginia8870.1%
50Montana8330.1%
51Wyoming7690.1%

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.

SkillFrequency (number of postings)Frequency (% of postings)
Python296,66237%
Computer Science260,33333%
SQL185,80723%
Data Analysis159,80120%
Data Science157,85520%
Amazon Web Services155,61519%
Agile Methodology152,96519%
Automation138,79117%
Java133,85617%
Software Engineering133,28617%

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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