My AI assistant has also created a podcast episode for the following article. If you prefer listening to reading, you can listen to the podcast via the following link (ATTENTION: Podcast is created exclusively by AI, no guarantee for accuracy).
AI technologies are quickly seen as the enemy of humans or as a trigger for job losses.
I see it the other way around. AI technologies are our friends and they should not primarily be used to dismiss employees from their jobs, but to RELIEVE employees from their jobs. In my opinion, challenges such as burnout, countless hours of overtime or a shortage of skilled workers are far greater than the risk of job losses.
In the following article, I show what successful collaboration between artificial intelligence and humans can look like and, above all, how we can find the right balance between AI technology and human input.
What are AI technologies?
What are AI technologies?
Artificial intelligence (AI) is a field of computer science that deals with the development of systems and machines that can perform human-like intelligence. This includes learning from experience, understanding natural language, recognizing images and making decisions. AI technologies use complex algorithms and large amounts of data to recognize patterns and solve problems that traditionally require human thinking. Despite its impressive capabilities, it is important to understand what AI can and cannot do in order to effectively utilize its advantages and respect its limitations.
What can AI technologies do?
AI technologies have made enormous progress in recent years and are now being used in numerous areas, industries and fields of activity. In general, the capabilities of AI technologies can be divided into the two areas of automation and analysis.
AI technologies for automation
AI technologies are able to efficiently automate repetitive and time-consuming tasks. For example, thanks to AI, machines in the manufacturing industry can work precisely and consistently without showing signs of fatigue. In office work, AI-based systems take over routine tasks such as sorting and creating emails, planning appointments, creating images, presentations and documents or recording data. This frees up human labor that can be used for more creative and demanding activities.
AI technologies for analysis
Another important area of application for AI technologies is data analysis. With the ability to process large amounts of data in a short time and recognize patterns, AI technologies help companies make informed decisions. In the healthcare sector, AI systems analyze medical data and help to make diagnoses or optimize treatment plans. In the financial sector, they identify fraud patterns and enable more precise risk analyses. In marketing, AI technologies analyze user behavior and provide suggestions for further sales activities.
What can’t AI technologies do?
Despite their broad and constantly growing capabilities, AI technologies also have limits. It is important to recognize these in order to be able to realistically assess the role of AI and design its areas of application in a meaningful way, especially with regard to collaboration between humans and machines. Here are some areas where AI technologies are (still) reaching their limits:
Creativity and innovation
Although AI systems are able to recognize patterns and generate new content based on these patterns, they lack real creativity and innovation. Creative processes such as writing a novel, composing a piece of music or developing a completely new idea require a deep emotional and cultural intelligence that machines do not possess. AI can provide support and assist with repetitive creative tasks, but original and inspiring creation remains the task of us humans.
Emotional intelligence
Another area in which AI technologies are limited is emotional intelligence. Human emotions are complex and multi-layered, and although AI systems can recognize certain patterns in language and behavior, they lack a deep understanding of human emotions and empathy. For situations that are strongly characterized by interpersonal interactions, these skills are essential and cannot simply be replaced by an AI.
Ethics and morals
Decisions that require ethical and moral considerations are another area where AI reaches its limits. While machines can make decisions based on data and algorithms, they lack a deeper understanding of moral principles and ethical dilemmas. This type of decision requires human judgment based on experience, values and cultural norms.
Self-reflection and awareness
One of the most fundamental limitations of AI is the lack of self-awareness and self-reflection. AI technologies cannot have their own experiences or be aware of themselves. They work on the basis of the data and algorithms available to them, without having their own awareness or subjective perspective. This limits their ability to think and learn about their own existence and actions.
How do companies find the balance between humans and AI?
Even if companies understand which activities an AI can perform particularly well and which are less suitable, the challenge of finding the right balance between AI and human skills remains. While some underestimate AI technology, others are so fascinated by the new possibilities that they give AI too much responsibility or overly complex tasks.
The following matrix is intended as a decision-making aid to find the right balance between human and AI-supported tasks.
Matrix for decision-making
The matrix divides processes or dialogs into the dimensions of complexity and importance. Complexity refers to the degree of difficulty of the task. Tasks that focus on automation and analysis can typically be performed to a high standard by an AI. On the other hand, there are highly complex tasks where AI is overtaxed due to a lack of human skills and which should therefore be performed by human employees.
As usual, there are not just two fixed solutions in a matrix, but four quadrants and numerous combinations between these quadrants.
Bottom left: Tasks for the AI
The lower left quadrant contains tasks that can mostly be performed entirely by AI technology. The fewer human skills such as empathy, self-reflection, creativity or ethical assessments are required, the more suitable these activities are for an AI. The same applies to the degree of importance: the lower the impact of the respective task on the company’s success, the more likely it is that this activity can be performed by an AI.
Top left: Important tasks that require few human skills
The upper left quadrant contains activities that are of great importance to the company but require few human skills to perform. In this case, the process is started by humans, but can often be solved better by AI than by humans themselves. Examples of this are complex analyses for which modern AI technologies are better suited.
Bottom right: Complex but less important tasks
The lower right quadrant contains complex tasks, but these are of lesser importance. In most cases, companies decide to hand over the majority of tasks to AI, despite their greater complexity, and only use humans as a backup. Due to the minor importance of these processes, many of these tasks are also entrusted to AI. However, AI must be carefully monitored and further developed.
Top right: Complex and important tasks
The upper right quadrant contains tasks that are both complex and highly important for the company. The focus here is clearly on people. Humans initiate and carry out most of this process, but can call on the support of AI at any time to scale and optimize their work.
This matrix is designed to help companies find the right balance between human and AI-supported tasks and thus increase the efficiency and quality of their processes.
Applying the matrix – from theory to practice
What often seems simple often poses major challenges for companies in practice. This also applies to the application of the matrix described above. The following recommendations can help.
1. classify processes
As a first step, companies should list all processes and distribute them within the matrix. It is advisable to work in interdisciplinary teams that can evaluate the processes from different perspectives.
2. prioritize processes
It is hardly possible to achieve the optimum balance between AI and humans in all processes at the same time. Companies should prioritize processes and gradually re-evaluate each process with regard to the collaboration between humans and AI. It is advisable to start with one or two use cases, gather initial experience and use this knowledge to optimize further processes.
3. educate and train employees
Only well-informed and trained employees can work effectively with AI technologies. Companies must therefore train their employees and teach them the key principles of AI technologies. This also includes information on data protection and the careful and responsible use of AI technologies. Take a look at my offer on AI with foresight.
Best practice: humans and AI in perfect balance
As part of my AI Trend Report, I accompanied a large number of Generative AI projects at the beginning of 2024 and analyzed them with regard to the opportunities and possibilities of automation and collaboration between humans and machines. These include the success story of the B2B company Unite Network SE.
Initial situation and challenges before the introduction of AI at Unite
Unite Network SE has an enormous variety of products, which makes it difficult to provide a service-oriented and efficient service, as not every product and the supplier behind it can be known to employees without prior research. In addition, the customer structure is extremely heterogeneous, with small commercial customers, public sector clients and large corporations as stakeholder groups on the platform. Every month, Unite receives up to 80,000 inbound contacts, mainly by e-mail, while telephone inquiries are on the decline. Due to the international coverage, inquiries have to be processed in several languages, which is why 10 foreign languages are spoken in customer service at the Leipzig site. In addition, many new order requesters with individual requirements have to be taken into account in the shortest possible time. Individual opinions and individual needs must also be recorded and processed. In view of Unite’s growth ambitions, the solutions must also be scalable. These diverse and complex challenges form the starting point for the introduction of the new automated solution for customer relationship management.about Unite Network SE
The solution with AI and humans in balance
Unite has opted for automation in customer service with the help of AI while keeping humans in the loop. The AI technology never takes over the service process completely, but acts as an AI companion to provide advice. The recommendations for action made by the AI are finally checked by the employees before the responses generated by the AI are sent. People at Unite therefore take on a “gatekeeper function”, which allows them to delegate individual process responsibility to artificial intelligence.
In practice, AI ensures high efficiency and empathy in customer communication at Unite. The AI not only automatically recognizes the content and tone of a conversation, but also creates response suggestions in real time that are complete, spelling and legal compliant and individual. And this in one of 10 languages spoken at Unite. It is also possible to train the artificial intelligence to use different tonalities for different areas of application and have these output automatically depending on the situation.
You can read the entire success story“Humans and AI – examples of successful collaboration” in my blog post on the AI Trend Report.
Humans and AI: Do you also want to find a balance?
Were you inspired by the article and now you want to use the matrix in your own home? I am happy to support you with workshops, advice or other templates.
Just send me a message with your request – preferably via WhatsApp message or e-mail.
This article is also available as a podcast episode
Attention! The podcast was created entirely by my AI-Assistant based on my contribution – no guarantee for incorrect content.
*I used SwissGPT’s AI technology to optimize the language of this article.
