AI meets skills development. And professional practice picks up the pace

A contribution by the Excellence Education/Concentric Team

In the previous article, we asked ourselves how AI is changing the work of financial advisers, managers and sales networks. The conclusion was that competitive advantage does not come from technology itself, but from people’s ability to use it with judgement, method and confidence. If this is true, then the next question we must ask ourselves as a training and change management company becomes inevitable: how does skills development change when AI becomes part of training and professional practice programmes?

Same goals, different ways to practise

Every professional faces different situations, difficulties and decisions. With AI, we can personalise practice and make it more continuous, supporting people before, during and after each session, without losing sight of the method and shared goals.

Practice begins with decisions, not answers

In our approach, practice starts with decisions: interpreting the context, drawing on experience, recognising automatic patterns and consciously choosing how to act. This is one of the principles of andragogy, or adult learning: people learn better when they recognise a practical use for what they are practising and can apply it to the real situations they are experiencing.

For over 20 years, we have been designing programmes and opportunities, with and without digital tools, that treat people not as recipients of solutions, but as active participants in building them. The starting point is what they already know how to do; they engage with real problems, experiment, choose and verify. Even when tackling new activities and upskilling, prior experience and attitudes remain resources to draw on and enhance.

AI, therefore, does not make andragogy important. It is andragogy that makes AI more useful and relevant today. We now turn these principles into deeper, more personalised and continuous experiences. Personalising, however, does not mean making things simpler or standardised: it means designing experiences and engaging people to encourage behaviours and motivations that truly help them grow consciously, taking into account challenges and goals, both corporate and otherwise.

When the right answer does not “arrive” immediately

AI can provide immediate answers, but in learning and practice, speed does not always equate to effectiveness. What is often needed is AI that asks questions, raises objections and challenges beliefs, rather than directly suggesting the solution.

This is why we use AI as a dialogue partner capable of stimulating reasoning. The aim is to preserve the cognitive effort that leads a person to formulate hypotheses, test choices, take responsibility, recognise mistakes and improve decisions.

Before, during and after training

The challenge for a management team and sales network is to combine shared reference points and individual priorities to meet mutual goals. The method can be shared, but the decisions that need to be practised vary from person to person.

In our programmes, AI supports this work even before the classroom session or training event.

• From consultations and surveys, we develop contextualised, actionable briefs; participants carry out self-assessments designed with Claude’s support and prepare the topics and questions they wish to work on.
• During our sessions, AI helps organise ideas, compare alternatives, justify priorities, test choices and refine approaches.
• After the session, what has emerged becomes material to build on for further practice.

In activities aimed at engaging clients, prospects, candidates and colleagues, AI also enables us to create more realistic and personalised scenarios, useful for role-play, simulations and targeted exploration.

True personalisation, therefore, does not consist of offering different content to each person, but of placing each person in front of the decisions they really need to practise making.

Practice continues in everyday work

Reality rarely follows plans. Changing priorities, unexpected conversations and unforeseen results become opportunities to reflect on what worked and what can be improved.

For us, the point is not simply to make AI available to people, but to design the interaction: which questions to ask, which automatic patterns to challenge, when to suggest and when to ask people to develop an alternative. At the same time, people learn to use AI with increasing awareness.

The method thus becomes the link between practice and work. It allows people to review decisions, compare them with the results achieved and guide subsequent actions.

Tools such as sales and advisory playbooks also evolve: they are no longer merely collections of guidance, but dynamic, customisable reference points to be continually tested against one’s own experience. After each practice programme, activities, guidelines and reporting allow both the people involved and the organisation to monitor progress against the defined goals and decide how to proceed accordingly.

The choice that matters

AI introduces an often underestimated risk: cognitive substitution. We can use it so effectively that we fail to notice what people stop practising.

A well-constructed plan or a convincing strategy is not enough to understand how solid the skills that produced them actually are. For a Sales Department or a Training Department, the issue is not simply adopting AI, but deciding which role to assign to it and which to leave to people.

We can use it to increase dependence on ever-better answers or to develop the ability to tackle increasingly complex questions and situations. This is the difference between using AI and truly putting it at the service of practice. And when choosing a training partner or a coach, it is a difference that matters and has an impact all the way through to the business plan.

As we observed in the previous article, the risk is not that AI is inadequate, but that it is used as a shortcut. When we stop exercising judgement, critical thinking and decision-making skills, efficiency can increase while skills weaken. This is why the aim is not to have AI work in people’s place, but to use AI to help people become more effective.