While generative AI is establishing itself in strategic intelligence systems, a metamorphosis is taking place in silence.
Long considered a discreet technician supporting strategic functions, the watchman is today experiencing a profound transformation of his activity. Driven by the emergence of generative artificial intelligence (AI), this mutation pushes it to increase its skills, to the point of embodying a central figure in strategic analysis. Far from being marginalized by AI, this professional sees his role transfigured: he is increasingly becoming a high-level analyst, at the crossroads of data and decisions.
Generative AI: a silent revolution in monitoring practices
Over the past two years, it must be said that strategic monitoring tools have undergone a real transformation. Automatic summaries, content summaries, instant multilingual translations, semantic categorization, prioritization of sources… Generative AI has crept into every corner of the daily life of watchers. What required tedious work yesterday can now be automated on a large scale.
In monitoring cells, within private organizations as well as public structures, the change is palpable: professionals now use assistants capable of processing massive corpora in a few seconds. Artificial intelligence allows accelerated reading of the news, immediate feedback of alerts, partial contextualization of the highlights. It even offers ready-to-use formulations, at the risk of tipping monitoring towards a form of excessive automation.
But behind this technical revolution lies another, more strategic challenge: that of increasing skills. Because if AI can produce content, it can neither judge their contextual relevance nor draw detailed lessons from it. The watchman is thus called to occupy a new, more central position.
A finesse of analysis on the edge of the predictive
One of the major contributions of generative AI lies in its ability to spot weak signals or improbable correlations within complex data sets. It crosses, extrapolates, projects. It detects, for example, that a social movement in the heart of a region of South America could impact the supply chain of a French supplier. Or that a discreet patent filing in Korea announces a technological breakthrough in six months.
This power of analysis brings to light at least two old dreams of strategists. The first is that of access to the “hidden weak signal”, this micro-information which, if correctly interpreted, makes it possible to anticipate a trend or a risk before anyone else. The second is that of prediction: increasingly fine-grained, supported by computing powers without equal until now, informational data is proving increasingly capable of adjusting predictive scenarios. But to exploit this new mass of data, as precise as it may be, you still need to know how to query the right information, understand it and put it into the context of the company.
This is where the watchman currently changes status. It is no longer just an information sensor; he becomes an expert analyst, a decoder of meaning, an architect of signals. The monitor interprets the results of the AI, cross-checks them, compares them to reality on the ground, to the strategy of the organization to which he belongs, to the culture of his sector of activity… Then he formulates hypotheses, proposes scenarios, and contributes more and more directly to decision support. In a word, it becomes a real analytical brain, in permanent interaction with the machine.
Human intelligence, more valuable than ever
This is how we are currently witnessing a paradoxical dynamic: the more powerful AI is, the more valuable human analysis – and with it a form of subjectivity – becomes. Because if content generation tools are capable of aligning sentences, they cannot nuance, nor prioritize according to issues, nor detect implicit or symbolic signals. They know neither the right tone to adopt, nor the corporate culture, nor the strategic unsaid. In this new landscape, humans remain at the center of the game, and the watchman must now demonstrate broader intelligence: critical thinking, sense of the hierarchy of information, detailed knowledge of ecosystems, ability to project consequences.
So, generative artificial intelligence does not augur the end of the watchman profession: it signals a re-foundation of it. However, our context of rupture remains Schumpeterian, with ruptures that we already know how to identify in managerial and organizational terms. Let us look at this situation with clarity. How can we humanly support this profound evolution that we are experiencing? How to think about the redeployment, internally, of certain human skills? This is also the challenge of change that organizations are currently facing.
