We are pleased to share an article entitled “How Artificial Intelligence Can Support Coaches’ Professional Development ” written by Carla Benedetti 
When asked about their experience of becoming a professional coach, many coaches say that reaching the end of their training program is an emotional moment. They start feeling a sense of nostalgia mixed with the pressure of starting a new business or, if they are internal coaches, promoting their new set of skills within their company.
Especially at the beginning, keeping themselves focused on their practice and feeling confident about their ability to coach can be challenging.
Those who intend to gain an ICF credential receive at least one cycle of mentor-coaching sessions. Others may hire a mentor coach for a few sessions to get some useful feedback. In any case, the process is limited to a short amount of time. After that, it’s mainly learning by practice, which means a lot of time spent before raising the standard.
What I have learned, over many years of experience, is that in order to really grow with confidence from the very beginning, coaches need continuous feedback, and feedback from professional mentors is expensive. Peer coaching and community practice are valuable ways to learn from each other. Still, a specific evidence-based mentoring on coaching is missing.
Could technology assist coaches in getting that support? Artificial Intelligence is entering the world of coaching in different ways. The mobile apps and platforms available are focused on two main areas:
- Marketplace and productivity platforms
- AI-powered coaching
Marketplace and productivity platforms use AI to match coaches with potential clients according to topic, industry, country, experience, etc… They also usually offer other tools and services to manage the business administration. Some of the most popular are BetterUp, CoachHub, and CoachingLoft.
These platforms have in some way democratized coaching by offering a huge portfolio of international coaches at accessible prices, while creating a business growth opportunity for coaches.
AI-powered coaching applications are different. They are basically chatbots using AI to converse with a client on different business and personal topics such as action plan, self reflection, and behavior monitoring. Some examples are Sally Digital Business Coach, The GoodLife Ai, and CoachEm.
This type of AI-powered coaching can be useful in simple tasks, where AI can respond easily, but it cannot replace a real coach. Machines can learn how to imitate humans, but cannot learn to be human.
In my research for the best AI coaching tool, I could not find a model focused on coaching skills, providing detailed, objective feedback on a coach’s performance. That’s when I decided to build it myself with my technical team.
My experience as a mentor helped me to design the concept and the first model. After months of intense research, development, and testing, I have launched THeach, a new AI-driven tool that helps coaches improve their performance. It’s the first of its kind, the first mentor-coaching system™, and I trust it will revolutionize the coaching profession.
The first version could analyze the transcript of a coaching session uploaded by the coach and provide feedback. The new version can generate the transcript from an audio or video file before sending the result to AI for a feedback report. This allows for a better user experience and even more accurate and detailed results.
How it works
AI language analysis is usually executed on one single text, with THeach we ask the machine to analyze the conversation between two persons: the coach and the client. In seconds the coach receives a report on coaching competencies based on the International Coaching Federation guidelines and best practices. It is a quite complex process and a completely new perspective.
During our testing, several times I have been asked:
“Why can’t we use Artificial Intelligence to analyze the audio recording directly? This would avoid the creation of a transcript and the process would be faster.”
It is a good question, and I see the point, but such a model is not yet available. Though we are surrounded by all sorts of technology that makes everything look very simple, to this day AI speech recognition cannot analyze dynamic criteria in a speech, it can create a transcript first which is not 100% accurate. This is when it is directed to one person, and even more challenging when it has to elaborate on a two-person conversation.
The best speech recognition programs from IBM, Otter, Amazon, Google, and Microsoft can reach up to 90/95% accuracy, and we are talking about the most sophisticated models that have been instructed to recognize content/words and variations in one speaker’s voice.
Can you imagine how difficult would it be for a machine to deal with a coaching session where two persons are engaged in a conversation, with variations in both voices in terms of tonalities, emotions, and rhythm? The outcome of the analysis, the feedback for the coach, would not be reliable. Without using a transcript as validation, we can not even know if the machine has worked on the correct content or on a close but not precise one. Skipping the transcript is a goal of the future.
Back to THeach, once the automatic transcript from audio or video recording is ready, you can review it in case some editing is needed. At least at the beginning, then the more you use it, the less you need to edit. Machines learn after all.
By the way, going through the session transcript is a great exercise to increase awareness about our coaching presence and skills, but that is another story.
What else is new about THeach?
Coaching effectiveness is usually validated through the client’s assessment, or self-assessment, taken before and after the program. Though this methodology gives us a good understanding of the client’s progress, we still cannot tell whether that was the best possible intervention.
For example, how often, especially at the beginning of your career as a coach have you found yourself doubting your client’s willingness to go deep into the coaching exploration? You might have noticed some resistance in moving forward, the sessions seemed to loop, or maybe your client’s answers didn’t have much to do with your questions. Your conclusion was that the client was not ready to be coached.
What if it was you? What If, due to lack of experience, personal thinking, internal dialogue, or bias, you did not realize that your client was just waiting for the right question? You were missing something and you did not even notice.
The features
The AI-driven mentor-coaching system™ provides feedback on a variety of skills, including:
- The percentage of time that the coach talks
- The similarity of language between the coach and the client
- The keywords used by both parties
- The types of questions the coach asks
Feedback is presented with graphics and comments to help coaches observe their sessions using an evidence-based approach. It is a private reflection, aimed at self-development.
One of the things that sets the app apart is its objective feedback. Because it’s driven by AI, there’s no room for personal bias or subjectivity. This makes it an invaluable resource for coaches looking to improve and grow in their profession. The coach is able to notice what really happened in the coaching sessions.
But THeach doesn’t stop there. It also offers features like session-by-session skill monitoring, report storage in client folders, personal reflection tools, and resources to delve into relevant topics.
We’re constantly working on further development, and we have big plans for the future. One of our goals is to make Theach available as a web version with more integrated features.
If you’re a coach looking to take your skills to the next level, I encourage you to try the app for free. And if you wish to be part of our new community, let us know. We will be happy to welcome choice Magazine readers with a special starting pack.
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