AI in the workplace: the impact of artificial intelligence

It is currently difficult to predict how artificial intelligence will develop in the future. However, so-called “strong” AIs that are equal or even superior to humans are currently more of a philosophical concept.

What role does AI already play in the world of work?

The actual extensive use of AI is far less widespread than one might initially think. The feared rapid, disruptive change is therefore not yet on the horizon.

The reason for this is comparatively simple: the development and implementation of highly complex intelligent systems, as would be necessary for many tasks, is associated with high costs.

Nevertheless, the role of AI is becoming ever greater, the world of work is facing a major change – the inhibition threshold for the use of AI in the company is constantly falling.

An expert survey conducted by the Bertelsmann Foundation revealed the following scenarios that could realistically develop by 2030:

Scenario 1: Inertia scenario: slowed development with minor consequences for the world of work

Scenario 2: Automation scenario: Automation in the traditional corporate world

Scenario 3: Platform scenario: Global companies operate AI-based automation

Scenario 4: Ambivalence scenario: Dynamic AI development, but trapped in the old world of work

Scenario 5: Transformation scenario: AI creates new working environments in a dynamic network

Only then could scenario 6 be realized, namely the vision scenario with AI as a problem solver in a post-employment society.

Where is AI already being used today?

Around one in eight companies currently uses artificial intelligence. Two current examples of the use of AI models:

• Effective online media monitoring (Condat AG): Condat AG has developed an AI system for the North Rhine-Westphalia Media Authority that is designed to speed up and simplify online media monitoring. Until now, employees have manually searched for and removed depictions of violence, incitement to hatred and pornography. The KIVI software can search more than 10,000 pages a day – and thus relieves employees of a burdensome task.

• Faster MRI scans (Siemens Healthineers): The narrow tube in an MRI scanner poses a challenge for many patients. With Deep Resolve, Siemens Healthineers has developed a technology that offers medical staff shorter scan times with the same image resolution – or even enables a higher resolution.

Opportunities and challenges of AI in the world of work

Experts are certain that AI will be the defining universal technology of the century. And while this change offers some opportunities, it also brings challenges.

Opportunities and potential

Automation of routine tasks 

AI can automate repetitive and time-consuming tasks and thus relieve employees of monotonous activities. This not only increases efficiency, but also allows employees to focus on more complex and creative tasks that require interpersonal skills.

Improved decision-making

By analyzing large amounts of data, AI helps companies to make more informed decisions. Algorithms recognize patterns and trends that would be difficult for humans to identify, providing valuable insights that can be incorporated into decision-making.

Personalized customer service

AI-supported systems such as chatbots make personalized customer service possible around the clock. Simple and repetitive customer queries in particular can be answered quickly and efficiently using AI-based systems. The result: more satisfied customers.

Process optimization

AI identifies inefficient processes and directly highlights opportunities for improvement. This enables companies to improve their business processes sustainably. This is particularly useful in areas such as supply chain management, logistics and production.

More innovation

By analyzing data and identifying trends, AI can help companies discover new business opportunities and develop innovative products and services. Only those who think innovatively will remain competitive in the long term.

Improved security

AI can also help to improve safety in the workplace by identifying risks in real time and suggesting immediately actionable measures. In areas such as cybersecurity, AI can also identify and ward off threats at an early stage.

Further training and retraining

AI can create personalized learning and training programs that are tailored to the needs and skills of individual employees. This promotes continuous learning and helps employees to adapt to the changing requirements of the working world.

Better recruiting

AI-supported systems make the recruitment process more efficient by analyzing CVs, identifying suitable candidates and speeding up the hiring process. A helpful tool, especially in times of skills shortages.

More flexibility

By using AI, companies can react more flexibly to changes in the market. For example, AI can make adjustments in production to better cope with fluctuations in demand.

Sustainability and resource efficiency

AI can contribute to the sustainable use of resources by optimizing and thus reducing energy consumption. This is particularly beneficial in production and energy management.

Challenges

Job losses and job relocations

One of the biggest challenges is the potential displacement of jobs through automation. Repetitive and simple tasks in particular could be replaced by AI in the future, potentially resulting in job losses. At the same time, however, the use of AI will also create new jobs.

Qualification gap

The change brought about by AI requires new skills and knowledge. Many employees need to be retrained or upskilled accordingly in order to meet the requirements of the new technologies. This poses major challenges for both companies and employees.

Ethics and responsibility

The use of AI raises ethical questions, especially with regard to data protection, transparency and decision-making. This makes it all the more important that AI systems are fair and unbiased, are regularly monitored – and that there are clear responsibilities when mistakes happen.

Data protection and security

AI systems require large amounts of data in order to function effectively. This places considerable demands on data protection and data security. Companies must ensure that personal and sensitive data is protected and not misused.

Transparency and explainability

Many AI algorithms are complex and difficult to understand. This is another reason why it is not always easy to understand on what basis the AI has made which decision. This is another reason why it is important that AI decisions are kept as transparent and explainable as possible.

Regulation and legal issues

The regulation of AI is still in its infancy. There are many unresolved legal issues, such as liability in the event of errors in AI systems or compliance with data protection laws. Clear and uniform regulation is still necessary in order to create legal certainty when dealing with AI.

Cultural change

The introduction of AI automatically requires a cultural change within the company. Employees must be open to change and ready to accept and use new technologies. This requires a clear change management strategy and competent managers who can allay their employees’ fears and build trust.

Costs and investments

In most cases, the implementation of AI systems is also associated with considerable costs. Companies have to invest in technology, infrastructure and training. This is often a major challenge, especially for small and medium-sized companies.

Quality of the data

AI systems are heavily dependent on the quality of the data they process. Poor or incomplete data can lead to incorrect or unreliable results. This makes it all the more important that the AI is comprehensively trained and “fed” with all the necessary data. This is the only way for companies to ensure that they really benefit from AI.

Dependence on technology providers

Depending on which AI technology companies rely on, there is also a dependency on the corresponding provider. This becomes a problem when pricing, the technology itself or data protection regulations change. In the worst case scenario, an entire company comes to a standstill.

AI and the climate

Sustainability and environmental protection play a greater role today than ever before. However, climate protection is also a problem with regard to the widespread breakthrough of AI.

This is because cutting-edge systems such as ChatGPT require huge computing capacities and, accordingly, large amounts of energy in their application. Potsdam computer science professor Christoph Meinel told dpa: “Many expectations of AI seem exaggerated to me and also unrealistic in terms of its energy consumption.”

What is needed for AI to really be widely used in the labor market are, above all, more energy-efficient systems. Otherwise, the use of AI will be difficult and unsustainable, especially with regard to achieving our climate targets.

How will Artificial intelligence  change the world of work in the future?

AI is changing the world of work at micro, meso and macro level. In short, artificial intelligence will cause massive and overarching upheavals in almost all areas of work.

This is because the areas of application for AI are diverse:

• Predictive analytics

• Resource management

• Quality control

• Robotics

• Autonomous driving

• Automation

• Sensors

• Knowledge management

However, it is almost impossible to make reliable statements about how the development of AI technologies will affect the world of work, because:

• The technology is very new and the field is therefore extremely broad and open.

• The effects of a technical development always depend on social and labor policy factors.

However, the effects of so-called LLMs, i.e. large language models such as ChatGPT, have been comparatively well studied. An online experiment by Noy and Zhang revealed the following developments in the use of LLMs:

• The work of employees is getting better

• The time required is reduced

• Employees’ skills improve

• Job satisfaction improved

A study from the USA by Eloundou, Manning, Mushkin and Rock from 2023 found that LLMs such as ChatGPT could be used in around 47-56% of work tasks in the future.

In the case of LLMs, almost all occupational groups are affected – as are all employment and salary levels. In contrast to digitalization, however, higher income groups and professions that require a degree are more affected by the introduction of LLMs.

The reason: on the one hand, AI makes specialist knowledge more widely accessible and, on the other hand, can solve complex tasks, but sometimes requires routine input.

Most affected are:

• Authors

• Mathematician

• Tax experts

• Financial analysts

• News analysts

• Reporter

• Web designer

• Legal services

• Educational professions

A study published in 2023 by Briggs and Kodnani also shows that around 2/3 of occupations are potentially exposed to AI – albeit to varying degrees. Around 1/4 of jobs could be replaced by generative AI if AI is allowed to fully develop.

At the same time, however, technological innovations always bring with them new fields of employment. Massive unemployment is therefore unlikely. It is more likely to be a shift in the workforce.

In Germany alone, the still very limited use of AI applications created 48,000 new jobs between 2018 and 2018.

How strong the influence of AI will be on our labor market depends on various factors:

• How autonomous and intelligent are the systems really?

• How well can employees deal with them?

• How quickly will the legal framework be created?

• What are the benefits of the technology?

• What are the social conditions like in the workplace?

• Does the activity require interpersonal interaction?

Most experts currently assume that AI will make human work more productive – but will not replace it completely.