AI is not only the future, it is also the present. And now that the metaverse is also involved, the AI revolution is accelerating further, opening up a new field of possibilities. So what are we actually talking about, and what does this mean for the future of work?

What is artificial intelligence?

Artificial intelligence (AI) is the science of creating machines with human skills: they can plan, infer, communicate and learn.

These machines make our lives easier, reduce costs and boost efficiency and profitability. But fears are often expressed about AI’s potential for negative disruption, particularly in the job market, when machines take over low-level, routine tasks.

There are different types of AI, all of which have a profound influence on how we work today and how we will work in the future  :

Machine learning

This type of AI is capable of “learning” from sequences identified in data. This technology is revolutionary because, rather than being programmed, the software can analyze the data fed to it to make predictions, create rules or make recommendations for action. Deep learning takes this process a step further, further reducing human intervention and enabling the use of larger data sets. It is responsible for some of the recent advances in speech and image recognition, and natural language processing. But the quality of machine learning depends on the data used to power it: for example, if this data is biased, the AI results will be biased as well. Generative AI systems, like ChatGPT, are an example of an application of machine learning.


Organizations use robots to automate physical tasks remotely or using algorithms or sensors. Besides robotic arms on production lines, robots have many uses today, from assisting with surgery to inspecting sewers, for example.

Natural Language Processing

Despite their great capabilities, computers have traditionally struggled to understand, respond to, and generate human language. Natural language processing (NLP) addresses this situation using machine learning. NLP has various applications, from translation, speech recognition and transcription to extracting information from reports.

What is the difference between AI and automation?

The terms “AI” and “automation” are often used interchangeably. However, these notions are not entirely identical, although their objective is to help human beings by taking care of routine and repetitive tasks. Automation refers to programming machines to perform tasks, while AI relates to machines that automatically learn by recognizing patterns through data.

Is AI the future?

AI is already deeply embedded in daily life and the world of work. Everything from digital personal assistants to smart devices, from online shopping to industrial robots, is enabled by AI. We are not always aware of it, but almost all of us use AI in one way or another, in the private or professional sphere.

Even if specialists are concerned about the generalization of AI and the lack of regulations, there is no doubt that it will play a fundamental role in the world of work.

Collaboration between humans and AI

Collaboration between humans and AI is still evolving. Two major topics emerge around this theme.

Automation and destruction of jobs

As AI makes it possible to automate and perform routine tasks, some positions will no longer need to be filled and the workforce may suffer.

77% of people who responded to a Forbes Advisor survey say they are worried about the job destruction that AI could cause in the near future. And according to McKinsey, AI could disrupt the jobs of 400 million workers around the world.

According to the World Economic Forum’s “Future of Jobs Report,” 25 percent of jobs will be negatively impacted within five years, and approximately 26 million administrative positions will be eliminated.

Other sectors affected by automation will include administrative and legal services, architecture and engineering, commerce and finance, management, sales, healthcare and art and design.

Creation and transformation of positions

Despite the concerns weighing on the labor market, many job creations thanks to automation are also expected. In 2022, 39% of companies reported hiring software engineers and 35% hired data engineers for AI-related roles. AI is also predicted to create around 97 million jobs.

Additionally, in the case of many jobs, AI does not automate everything, but only the most routine tasks, such as payroll or extracting information from documents, for example. Human oversight of the process is also always necessary in order to intervene if things go wrong.

So rather than replacing humans, AI will work alongside them, helping them work better and focus on the most creative and satisfying elements of their work. For example, although AI can be used to help make medical diagnoses, it will still be up to the medical profession to treat patients.

AI is accompanied by a growing demand for profiles with technical skills, such as programmers, statisticians, scientists and data analysts, as well as for people with creative and emotional intelligence , which AI cannot provide.

The changing world of work

From ChatGPT to the metaverse, AI is progressing in various areas.

  • Metaverse  : Virtual reality and augmented reality technologies are creating an Internet that you can enter, whether to play, entertain, or work. Shared virtual spaces will blend into the physical world and transform collaboration, communication and professional learning.

  • Fraud prevention  : By analyzing large numbers of transactions, AI can reveal fraud trends. It can then automatically block suspicious transactions or flag them for further investigation. It is also possible to use AI in cybersecurity to recognize and block threats.

  • Chat bots and digital assistants  : The capabilities of chat bots are growing at the same pace as NLP, allowing them to communicate more naturally with users instead of just responding with simple “Yes” or “ No “. Customer service thus improves in quality, and staff can focus on the most complex customer requests.

  • AI and health  : the World Health Organization estimates that by 2030, there will be a shortage of 18 million healthcare professionals worldwide. AI could provide part of the solution to this problem by automating routine tasks, improving productivity and, above all, giving staff more time to spend with patients. AI is already used in many spheres, including hospital management, medical diagnostics and patient-focused applications.

Explainable AI

AI does not operate in isolation. Its use by companies in their decision-making raises questions of transparency, confidentiality, fairness and accountability. This is where Explainable AI (XAI) comes in. It aims to ensure that the reasoning of algorithms is understandable by humans. It is also essential to help detect artificial intelligence errors.

AI in human resources

In addition to automating routine tasks, like payroll, AI is transforming recruiting. It can take care of the lengthy process of filtering profiles, pre-screening candidates and scheduling interviews, for example. This makes the process much more efficient, especially at the start of recruitment, saving a huge amount of time and reducing costs. But organizations should keep in mind the risks of AI bias in the context of recruitment.

Embracing AI at Work

Widespread adoption of AI in a business implies big changes in the way staff work. So how can organizations show employees that AI is a force for positive change?

One way to do this may be to emphasize that AI is designed to support, not replace, staff. Most importantly, since people will be working alongside AI, it is essential to ensure they have the necessary technical skills. This will involve improving and strengthening their know-how if necessary, so that they are able to take advantage of all the possibilities offered by AI.

Once AI is implemented, you will see its benefits:

  • Better productivity  : Productivity can skyrocket when employees and resources are not tied up in routine tasks. According to Nielsen Norman Group, generative AI systems improve staff productivity by 66%.

  • Better efficiency  : AI can perform certain routine tasks faster and more efficiently than humans. And of course, unlike employees, AI-driven services are available 24/7 to detect fraud, answer customer questions and analyze applications, saving money time and resources.

  • Solving complex problems  : Thanks to advances in machine learning, AI can now intervene in more complex tasks, such as medical diagnosis, for example, which frees up resources and increases productivity.

  • Innovation  : AI-generated ideas in brainstorming sessions, interactions in virtual spaces in the metaverse, and using AI in the supply chain to understand what customers want (and then make decisions relevant to products) contribute to organizational innovation.


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