We’ve seen remarkable advances in the capabilities of artificial intelligence (AI). The recent leap forward in natural language-processing, where AI models can comprehend and generate human-like text, has opened the door to sophisticated chatbots that effectively mirror human conversation partners.
One area AI continues to advance is the coaching arena, where research shows AI-enabled chatbots can rival human coaches to help individuals attain their goals. This has caused somewhat of a stir in the coaching industry but has implications for managers in organizations as well. If coaching bots are becoming effective agents of individual change, will they replace the need for managers to coach their employees for development?
AI-driven coaching as a means of employee development may indeed offer an enticing array of advantages that can revolutionize how companies nurture talent and drive performance. However, like any disruptive technology, AI coaching also comes with potential challenges and limitations.
Pros of AI Coaching for Employees
Scalability: Among the most significant advantages of AI coaching is its ability to deliver personalized guidance and support to a vast number of employees simultaneously.
Convenience and Frequency of Interaction: Unlike human interaction constrained by a manager’s availability, employees can interact with a coaching bot at their convenience and as often as they would like. This provides a greater opportunity for real-time adjustments and growth.
Data-Driven Insights: AI-driven coaching bots can be programmed to instantly analyze performance metrics, learning patterns, and other relevant data that may surpass a manager’s processing capability, enabling them to extract valuable, data-driven insights.
Cons of AI Coaching for Employees
Lack of Emotional Intelligence: As advanced as natural language processing has become, it (as of now) is still not capable of feeling. Many employees may find it difficult to connect in a meaningful way to a coaching bot, diminishing the potential power of the coaching relationship.
Limited Contextual Understanding: Having the ability to analyze vast amounts of data doesn’t necessarily equate to being able to appropriately contextualize that data. There are certain levels of understanding that a manager might bring to a situation that no amount of data-crunching would surface for a coaching bot.
Risk of Coded Bias: While managers aren’t necessarily free of bias, AI algorithms are only as unbiased as the data on which they’re trained. If the data contains inherent biases, the AI coaching bot will inadvertently perpetuate those biases, potentially leading to unfair coaching practices.
While there are several potential benefits to AI-driven coaching, there are concerns, as well. Organizations would be wise to use caution as they adopt this technology, recognizing that the best strategy may be to use AI to augment rather than replace manager coaching of employees. Finding the right balance between AI and manager coaching is likely the key to maximizing the benefits of both approaches and fostering a supportive and empowering learning environment for employees. ●
Melvin L. Smith is Professor of organizational behavior, faculty director of executive education at Case Western Reserve University’s Weatherhead School of Management
