Coaching & AI — how artificial intelligence will shape the future of coaching

For most, coaching is a personal and human encounter that is felt through the empathy of the coach. Empathy in this context means the ability and willingness to recognize, understand and empathize with the sensations, emotions, thoughts, motives and personality traits of another person. Coaching has gained great awareness and acceptance as an accompanying function within organizations, especially in the areas of learning, growth, well-being, self-awareness, career management, and behavior change of people. But what if, in the future, the coach may not be a human at all, but a machine?

AI systems in coaching

The rapid growth in the application of Artificial Intelligence (AI) has been called the most significant event in recent human history, with the potential to change virtually all aspects of human life. However, expectations about the capabilities and potential of AI (artificial intelligence) are mostly very unrealistic. All existing AI applications such as autonomous driving, spam filtering or conversational AIs (Artificial Intelligence) like Alexa & Siri are based on the first development stage of artificial intelligence, weak artificial intelligence. Here, AI is usually only used for a specific, predefined task. This is partly due to the fact that weak artificial intelligences only take the required information from specific data sets and are thus bound to them. In their respective fields, however, the applications already act in real time and often surpass human efficiency in their work. It is extremely unlikely that we will have AI that equals human intelligence, so-called strong AI, in the near future. Experts disagree on whether and, if so, when general AI will become a reality. Estimates range from 2030 to 2060. We need not fear superintelligence in our lifetime.

However, that doesn’t mean AI isn’t already having a significant impact in many contexts, including helping professions such as healthcare and psychology. It is also already in its first use for application areas in coaching. It is therefore inevitable that all coaching stakeholders need to think about how to responsibly use, develop and deploy AI in the coaching industry. Only through the participation of all coaching stakeholders such as coaches, coaching associations, research institutes and companies can meaningful, ethical and quality-assured applications be developed and brought to market here in the future.

The three most important ingredients in creating an AI system are high-quality data, carefully crafted algorithms, and the necessary computer power. The great growth of AI systems in recent years is based on exponentially growing computer power. Most of the algorithms used today have been around since the 1960s and 1970s. However, due to poor computing capabilities at the time, use cases could never be successfully implemented. This means that although we already have good algorithms and enough computing power for AI systems, the issue of data plays an enormously important role today. We are talking about a data rush, which is often compared to the gold rush. Without reasonable data, even with the best adapted algorithms and the best computing power, we cannot achieve good results in overall AI.

Therefore, it is important to think about what will achieve this data quality from the beginning. It is the coach’s responsibility what confidential coaching data they share with digital providers. This also depends on which digital provider he hopes to get the most value from in the coach-coachee relationship. If you don’t pay anything for a product, you are usually the product yourself (or your own data).

Where is the use of AI in coaching helpful?

The use of AI in coaching is always helpful where AI can really add value compared to real coaches. This is especially the case in the area of speech and pattern recognition, location analysis, bias detection, and unlimited capacity. AI-based assessment tools allow users to receive daily notifications based on their personal assessments and reflect on content learned via reminder features. AI enables coachees to access coaching as a low-threshold offering in a low-risk environment on their own schedule. An AI-powered suggestion system can offer coachees further suggestions based on their previous sessions, such as working on beliefs after uncovering inner conflicts. Human coaches can also use AI to regularly track changes in a user’s behavior, as it can more easily detect these deviations in behavior.

Bias in coaching is something we as coaches are always confronted with and should be aware of. Studies suggest that objectivity is not part of the human condition; that our minds are not capable of being completely objective. Our perceptions are always interwoven with our understanding of the world, our own history, our past, etc. One of the most common biases in coaching is the “confirmation bias.” In this, the coach attempts to confirm his or her initial hypothesis regarding the coachee’s issue and, as part of this, risks not capturing the coachee’s whole story or point of view. This type of bias can be counteracted through the use of AI when algorithms are created on a high-quality, diverse, and unbiased data set.

Chatbot Coaching

Systemic and solution-oriented coaching follows standardized process flows and steps (e.g. the GROW model) through which even a smart coaching chatbot, such as the one from evoach ( can guide the coachee step by step along a decision tree structure. The coaching chatbot only needs the right question sets for the respective process steps as well as well digitally visualized coaching methods, which it integrates into the process depending on the coachee’s topic. As in personal coaching, the coachee is responsible here for the content, the coach for the process of the coaching session. The challenge here is the careful and professional design of such digital, intelligent process flows and the creation of meaningful algorithms. The expertise of experienced coaches must be incorporated, and coaching associations should review the quality of applications for ethical and content standards. Research institutes can then explore their effectiveness and impact on the coaching process.

Dr. Nicky Terblanche, a researcher and head of coaching program of Stellenbosch University discovered with his goal-achievement chatbot Vici as part of his English study “A Design-Framework to create AI Coaches” that a chatbot, created purely on a decision tree structure, was able to support coachees just as successfully as a human coach after only 10 months.


Although AI is destined to take a firm hold in the coaching industry in the near future, human coaches need not worry that the industry will become completely automated anytime soon. The use of AI in coaching currently needs to undergo more research and testing to see how AI can be made truly effective and beneficial in coaching. In the meantime, human coaches should prepare for further collaboration with AI.

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