There are no two ways about it: the use of generative AI has a role in the future of all things career development. AI-powered tools can assist individuals in tasks like writing resumes, preparing interview answers and offering general career advice. They can fill in the gaps in some technical knowledge and provide quick access to information and resources.
AI’s use in powering chatbots has also gained popularity in providing career-related guidance and support. This can include coaching and mentorship – pillars in any holistic career development programming. If you dig into the use of AI in mentorship relationships, you’ll likely come up with everything from mentorship software that uses AI to make matches, all the way to chatbots that function like coaches, mentors or friends.
As AI chatbots rapidly grow in popularity, and increasingly become used in career development software or training programs, it is important to acknowledge the power of human-to-human connection. Mentorship style relationships foster a sense of purpose and meaning by providing the guidance, support and encouragement needed to excel in work, develop a fulfilling career and build strong, meaningful relationships. While AI is helpful, the shared human experiences are uniquely capable of creating this fundamental aspect of personal and professional development.
The importance of connection
Having become widely available only recently, there is still relatively little research on the psychological impact of chatbots on people. However, we know that psychological safety is an important aspect of a trustworthy and connected mentorship relationship.
Human-to-human connection is critically important for people. Social connection can lower anxiety and depression, help us regulate our emotions, lead to higher self-esteem and empathy, and actually improve our immune systems. Not only that, but it helps us to develop dynamic foundational skills required for the workforce today, such as communication, adaptability and resilience.
A chatbot or AI-generated response lacks the depth that comes from lived experience and the real-time vulnerability that a human relationship can provide which are crucial in mentorship relationships, in particular in reskilling or pathway-to-work style programming. With limited contextual knowledge, AI chatbots may have difficulty understanding the unique context and individual circumstances of mentees, leading to generic or irrelevant advice.
Genuine lived experience becomes an advantage in a mentorship program. In real life, people are complex. They come from different socioeconomic backgrounds, cultures, religions. Things like food and housing security play a role in how people show up in their careers. The lived experience of having navigated through life’s complexity is invaluable.
AI limitations
Additionally, gen AI tools like Chat GPT 3 and 4 and Jasper (an AI model developed for speech-related tasks) have not worked out all their kinks yet. Tom Chivers, author of The AI Does Not Hate You: Superintelligence, Rationality, and the Race to Save the World, shares the current limitations of AI, chiefly that the “knowledge” is bound by a limited understanding of human emotions, ability to interpret social cues or needs, access to quality data, and inability to read contextual nuances. Showing inherent bias and working with limited in-depth knowledge of career development experiences across diverse cultures and ethnicities can be problematic.
“When engaging in a human-to-human mentorship program, there’s an opportunity to provide support and resources to mitigate the impact of subconscious biases …”
When LaFawn Davis said “technology is reflection of ourselves” during her talk at Indeed FutureWorks 2023, it seemed connected to the sentiment highlighted in Chivers’ book – AI only works within the knowledge or data it is fed. This is why, at EnPoint, we use it successfully in our mentorship software to make matches. We are only using the data that participants have provided. The reality is there is work to be done in changing the systemic barriers for any and all marginalized or under-represented groups, so we can then surmise the inherent bias still present in the world’s current AI models.
When engaging in a human-to-human mentorship program, there’s an opportunity to provide support and resources to mitigate the impact of subconscious biases (e.g. by providing participants with EDI training). The ultimate goal of a great mentor is to be able to provide highly personalized guidance tailored to the specific needs and goals of a mentee. For instance, supporting students, newcomers, and those new to the workforce or returning after a long hiatus requires safe space and added capacity to deep dive into the barriers and challenges unique to these groups.
In an article on “Why AI Can’t Make Human Creativity Obsolete,” technology writer Alberto Romero says, “A personal essay written by a fellow living human with human experiences, human emotions, human drives and dreams and hopes pulls us more than anything qualified as perfectly written – it’s not the pristine paragraph but the one that resonates with us best that makes us want to read on.” The same concept is applied here; humans who have been through real-life experiences, good and bad, are more relatable and encouraging.
A supplementary tool
When considering the mentorship sector, there are some helpful ways that AI can be used. For example, EnPoint’s mentorship software uses algorithms to support effective mentor-mentee matching. We also encourage mentors and mentees to use generative AI tools like ChatGPT or Ask Sage to support their ongoing relationship. An example might be asking for analysis of recorded conversations or worksheets, to help a mentor identify behavioural insights and patterns, or analyze a mentee’s goals, strengths and areas for improvement. A mentee could also opt to do this themselves to synthesize their mentor’s main points of advice and/or to consider their own verbal communication skill.
AI tools can also suggest specific actions, learning resources and milestones to support a mentee’s growth. Using prompts such as “Tell me how to find out how my engineering mentor got his current job” could help mentees generate helpful lists of questions to ask their mentors. Mentors could use it to suggest “big-picture” discovery questions to ask mentees to help them reflect on their career goals and/or obstacles.
Chatbots and other tools (if used properly) can provide quick access to information or guidance on writing an action plan with smart goals, coming up with career exploration questions and many other practical things. However, human mentors are required for deeper discussions and personalized guidance that generates long-lasting inspiration, self-confidence and the motivation necessary to sustain focus on career development goals long after the relationship ends.
What’s your view on using AI in supporting career development or mentorship programming? How are you using it already?
