Lesley Ronaldson EMEA Vice-President, Gong, on Revolutionising Coaching through AIB
For high-performing teams, coaching employees is essential. Gartner reports that only 40% of salespeople in the industry I work for have a strong coaching culture. This gap between the demand for training and what workers get is not surprising. Training is time-consuming and requires commitment on all sides. Senior staff may find it difficult to make time to do it in their busy schedules.
The advent of AI, and in particular, generative AI, has provided business leaders with a powerful tool to identify and address their teams’ developmental areas. Many have yet to take advantage of this, despite the rush of other businesses to implement AI. While 82% of British companies are eager to embrace this emerging technology, fewer understand its potential as a coach’s aid.
The barriers to effective Coaching While employees benefit from constant feedback in order to improve their skills, they feel that their managers are not able to provide them with adequate support because of the time constraints. Only 38% of sales reps say that their managers do anything to help them develop their skills, and an even smaller number–34%–says they get support for their career advancement. The average sales manager spends 9% of his time coaching each of his seven direct reports. That’s less than 1% per person.
It is hard to give each person the attention they need for their growth when coaching takes so much time. Tasks can accumulate and senior members of a team are often pulled into situations with high stakes that require their full attention. It’s impossible for managers to dedicate the time necessary to track their direct reports’ progress, development goals, and performance if they are left to human beings. With generative AI, managers can get all the information they need to make decisions about coaching – whether it’s providing additional support for people who are in need or creating new challenges for high performers. By relying on data more, biases of humans can be avoided. Data can be used to create a neutral backdrop for designing tailored development strategies. What one person perceives as a flaw might not alarm another.
What is Generative AI and how does it work?
AI can deliver targeted, data driven support to managers and direct reports. It does this by analysing large amounts of performance data and delivering personalised, useful feedback and guidance. The power of generative AI is to uncover what was previously hidden. A manager would have to be extremely diligent in order to monitor every phone call made by their team, but AI tools can help. It can then generate insights from the transcript, giving a manager and salesperson previously inaccessible visibility. Team leads don’t have to rely on the data manually entered into CRMs, but can dig deeper into what is really going on during these crucial interactions. The generative AI, for example, can identify areas where salespeople focus too much attention on irrelevant details (like an overly detailed description or using jargon) and suggest alternatives. The vast datasets that AI models are trained with inform these suggestions, which are based on real-world success.
The AI generated by Generative can also identify subtle communication errors and suggest solutions. For example, it can highlight how often a person interrupts, or if they use words or phrases which have an impact on their effectiveness. This data-driven method provides consistent feedback, which was previously not possible without listening to every single call.
Scorecards and evaluations of performance are valuable coaching tools, but they can also take managers’ time to create if they have to collect the data themselves. This is the type of workflow that machines excel at. It’s why generative AI is a perfect fit for this application. The manager only needs to decide what action to take after letting the machine crunch data and convert insights into a readable form.
Generative AI is a tool that helps organizations make coaching consistent and scalable for more employees. It also helps bridge the gaps created by time constraints.
GenAI augmenting Human Expertise
We can’t stress enough how important it is to not lose the personal touch, which makes coaching so effective. The technology is an excellent tool for managers, but should not replace the human element. AI cannot replicate the qualities of coaching, which include building trust, understanding subtleties and showing empathy.
AI enables me to focus more on relationship-building by taking over routine tasks like data analysis and feedback tracking. Automating these tasks allows me to devote more time to the personal aspects of mentoring, like listening, empathising, and guiding mentees as they face their own challenges.
The potential of Generative AI to transform coaching is that it can make it more objective and consistent. It also makes coaching scalable. Data-backed insights in real-time enhance the feedback, while addressing common challenges such as subjectivity, resource constraints, and frequency of sessions. The technology provides managers with personalised and consistent guidance on how to develop employees’ agility, resilience and skills. This helps them create more robust experiences for employee development than traditional coaching could achieve.
The original version of this article AI revolutionising coaching appeared first on HR news.
