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The Future of Collaboration in the Artificial Intelligence Era

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The Future of Collaboration in the Artificial Intelligence Era

The Future of Collaboration in the Artificial Intelligence Era

How humans collaborate with one another has been closely linked to technological progress.

Before the invention of the telephone, we had to be in the same room to communicate in real-time – and prior to the internet, we had to be in the same building to share our designs, new ideas, or other documents.

Collaboration has always been a moving target, and in modern times we shouldn’t be surprised that new technological innovations are again shifting how humans work and coordinate together.

The New Collaboration Cycle

Today’s infographic comes to us from Schneider Electric, and it shows that humans are no longer making things using a linear approach.

Instead, modern collaboration is a cyclical process with no defined start or end points – and it often involves more users and stakeholders, continuous access, and an increasingly decentralized workforce.

The 24/7 Knowledge Factory

All around the world, the way that teams work together is changing.

Instead of always being centralized at a local level, teams are adding talent from around the world who bring diverse perspectives and new ideas to the table.

The modern organization never sleeps – it has people from different countries, time zones, and cultures all working together to create new designs or products simultaneously.

Collaboration on projects is happening in real-time, at all times of the day, and this has several benefits. It brings together a broader range of skills and perspectives, makes teams more customer-centric, reduces errors and wasted money, and enhances both decision-making and product development cycles.

Working Together is Changing

How are teams collaborating 24/7 in real-time from locations around the world?

VR/AR
Designers, engineers, and other team members can collaborate in parallel, using mixed reality as a common medium.

Collaborative Intelligence (AI)
Multi-agent, distributed systems where each agent, human or machine, is uniquely positioned, with autonomy to contribute to a problem-solving network.

Advanced Modelling (3D and 4D printing)
Design and manufacturing can be integrated seamlessly, even to customize individual items. 4d printing (fourth dimension: movement) is a new frontier where printed objects adapt to various circumstances.

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

Computer Supported Collaborative Design (CSCD)
The synchronous sharing of information and interaction with ideas, in an AI-driven, data-intensive environment. Here, problem solving, data and service “agents” support, or replace, labor intensive work and possibly the human traits of intuition and decisi, as well.n making.

The Next Wave

How humans work together is changing, but also shifting is how humans and AI will collaborate together.

The new technological landscape creates many questions and uncertainties for companies today:

  • Will new “collaborative” technologies really change how we engage, and innovate with, our colleagues?
  • Will a hyper-networked, always-engaged global collaborative environment create “too many cooks in the kitchen”?
  • With more opportunity to get involved in processes, how does the role of the end-customer change?
  • Will traditional design and implementation switch to being more service-based, as time goes on?
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Charted: The Jobs Most Impacted by AI

We visualized the results of an analysis by the World Economic Forum, which uncovered the jobs most impacted by AI.

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Charted: The Jobs Most Impacted by AI

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

Large language models (LLMs) and other generative AI tools haven’t been around for very long, but they’re expected to have far-reaching impacts on the way people do their jobs. With this in mind, researchers have already begun studying the potential impacts of this transformative technology.

In this graphic, we’ve visualized the results of a World Economic Forum report, which estimated how different job departments will be exposed to AI disruption.

Data and Methodology

To identify the job departments most impacted by AI, researchers assessed over 19,000 occupational tasks (e.g. reading documents) to determine if they relied on language. If a task was deemed language-based, it was then determined how much human involvement was needed to complete that task.

With this analysis, researchers were then able to estimate how AI would impact different occupational groups.

DepartmentLarge impact (%)Small impact (%)No impact (%)
IT73261
Finance70219
Customer Sales671617
Operations651817
HR57412
Marketing56413
Legal46504
Supply Chain431839

In our graphic, large impact refers to tasks that will be fully automated or significantly altered by AI technologies. Small impact refers to tasks that have a lesser potential for disruption.

Where AI will make the biggest impact

Jobs in information technology (IT) and finance have the highest share of tasks expected to be largely impacted by AI.

Within IT, tasks that are expected to be automated include software quality assurance and customer support. On the finance side, researchers believe that AI could be significantly useful for bookkeeping, accounting, and auditing.

Still interested in AI? Check out this graphic which ranked the most commonly used AI tools in 2023.

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