How the way we read people in the company is changing — and why the real question is not “who will use AI”, but “who will be able to guide it towards goals that we still can't imagine today”.
The job changes shape: what it means for those who deal with Talent Management
There are times when a technology is not limited to entering the work tools: the very form of the work changes. It happened with the internet, with social media, with the cloud. It's happening again, and faster than before, with generative artificial intelligence.
It is not an alarmistic observation. It is an observation that, as HR professionals, we should welcome with the same methodological seriousness with which we have welcomed every other transformation of the organizational context: updating the tools with which we measure people's potential.
Today, in a growing number of roles, the result that a person produces no longer comes only from his individual skills. It arises from the interaction between that person and a system, the generative AI, which actively contributes to analysis, content, decision preparation.
It is no longer "the person plus the tool". It is a hybrid system that produces performance together.
This changes a question that for decades we have taken for granted in every talent management process: when we observe a performance, what are we really observing?
Because people's potential should be read in the context of Generative AI
In base 9 we have been working for years on a principle that today becomes more urgent than ever: potential is not an abstract quality of the person, disconnected from the context. It is always the ability to respond effectively to the demands of a specific environment (organizational and business), but increasingly mediated by AI.
For this reason, when the environment changes structurally, it also changes what it means to have potential in that environment.
More robust potential assessment models were created to predict how a person will behave in more complex roles within a certain type of organization. They still work, but they were built assuming that the complexity to be managed was only human and organizational.
Today there is a third variable to include: the ability to orchestrate a hybrid Human-AI system to achieve a goal.
It is not an isolated technical skill, like "knowing how to use ChatGPT". It is a transversal competence that crosses the way in which a person delegates, verifies, integrates, decides to what extent to use the output of Generative AI.
And, like any transversal competence that really matters, it is not seen from a self-assessment questionnaire: it is seen in behavior, while it happens.
This is why, as a base 9, we chose not to simply add a “use of AI” item to existing competence models. We chose to rethink the observation setting when it comes to measuring the potential in the company.
Measuring Potential in the AI era: 3 Concrete Shifts for HR
Three concrete shifts, which guide the way we work with our clients today on Talent Management and People Development.
1. From isolated competence to driving ability
The result of the person's work depends more and more on the interaction with the AI. The potential he can express is based on his personality characteristics, motivations, behaviors, and with which approach or strategy he exploits AI in a respected context to achieve the expected result. It is therefore necessary to understand how that person orchestrates the personal and organizational resources available - including AI resources - to achieve a goal in increasing autonomy. It is a reading more faithful to how, in fact, the work is already being carried out today in many organizational contexts.
2. From the declared observation to the observed behavior
Adoption surveys tell how many people use AI. They don't tell how. To measure the potential in this new scenario it is necessary to observe people as they face real professional goals, with the support of generative AI, and detect patterns: how much they delegate, how much they verify, how much they use the tool to expand their thinking instead of replacing it. It is exactly on this principle that we built AI based Challenge©, our proprietary platform, capable of detecting — through specific metrics — how people integrate AI into their work when they pursue a goal.
3. From unique potential to different interaction styles
Not all people relate to AI in the same way, and this is not a defect to be corrected uniformly: it is a fact to be read that expresses the peculiarity of each person. Recognizing Human-AI interaction styles is the first step to understand where to invest in development, and to do it precisely, person by person, not with a generic course for everyone.
A look at the future of Talent Management, not a correction of the past
We're not saying that yesterday's talent management models were wrong. We are saying that the world of work to which they applied is changing shape significantly, and that the models and, above all, tools for measuring and managing talent deserve the same update that HR has always been able to do in the face of every technological discontinuity.
Compared to potential assessments, they are not evolving in two directions.
A more conservative one, which invests in the creation of a behavior observation setting supported by psychological tests and biographical information. These have the merit of being able to be customized on the reality of each Company consistent with business dynamics, culture, leadership models.
A more discontinuous one, which invests in developing a robust battery of tests and some one-to-one simulations and interviews. In this case, the introduction of AI is aimed at managing and harmonizing the data of the different tests and therefore making the process sustainable and economically advantageous. The advantage is to be able to propose a benchmark on large numbers, regardless of the peculiarities of the business context.
In base 9 we have worked for more than two years to maintain a direct observation setting of people, but creating contexts in which they are called upon to achieve the required objectives by also using AI. This allows us to bring out individual approaches and inclinations to the use of AI that is based on how it drives a hybrid Human-AI system.