Weak signals are often presented as a subject for experts, reserved for mature organisations, or as a secondary, almost superfluous topic. This is a dangerous mistake, especially with the explosion of AI.
AI affects our perception of things, and as you know, perception is a subjective BUT critical dimension. Our decisions are made on this perception, at all levels of the hierarchy, on issues of varying importance. And all it takes is one link to break at a critical moment for the whole structure to collapse.
It is on this perception that hackers and manipulators act to create chaos and extort money, opinions and influence.
The only way to measure the positive or negative impact of this perception on your organisation in a crisis is to listen to the weak signals. They are the subtle music of your potential to manage the crisis with your teams, whose human and logical reactions can mitigate or aggravate the damage… depending on the governance put in place.
Unfortunately, in most cases, weak signals are only considered at the time of the crisis and inevitably in a negative light. But if they were observed at their true value and managed correctly well in advance, they would become a force for stimulating vigilance, commitment and cohesion in your organisation.
- Overview of companies’ preparedness for cyber risksAI
- The four main families of weak signals, and why they become explosive with AI
- Integrating the weak signals in dashboards, provided that you change your posture
- A concrete example of integrating weak signals in dashboards
2025-2026 Overview of preparedness for crises
The findings are clear. Most companies, especially SMEs, are aware of the risk of cyberAI. But this awareness does not translate into adequate preparation.
We have conducted a study on the subject, which highlights major shortcomings in:
- integrated cybersecurity governance
- the existence of crisis plans that are truly ready to be activated
- cyber crisis communication
- regular simulation exercises
- knowledge of AI and its risks
- Taking weak signals into account
In other words, the risks are identified, but the capacity to deal with them collectively remains largely insufficient.
👉 For a detailed analysis, read our article, which will also give you a rough idea of your CyberIA preparedness level.
What weak signals are and why they become explosive with AI
Weak signals are the subtle, early signs of a system under psychological strain, which may or may not indicate a gradual deterioration in an organisation’s cohesion and its collective ability to perceive, interpret and make the right decisions under pressure.
This point is widely documented in work on crisis management, systemic risks and information governance (notably ENISA, WEF and ANSSI – French Cybersecurity department). All these eminent organisations agree that major crises do not arise suddenly, without warning signs. They develop silently.
There are four main categories of weak signals, the significance of which is profoundly altered by AI.
1️⃣ Perception weak signals
Irony, rumours, visual distortions, sarcasm, memes, ambiguous comments. These signals do not directly attack the facts. They attack the credibility, legitimacy and trust placed in the organisation’s words.
Cybersecurity authorities and organisations specialising in information risks emphasise that these dynamics often precede reputational crises. Mistrust is already established before any formal incident occurs.
Consequences when ignored
- gradual erosion of stakeholder trust;
- loss of control over the public narrative;
- amplification of biased or hostile interpretations when a real incident occurs;
- increased difficulty in being believed, even when the facts are established.
In other words, when the crisis erupts, the groundwork has already been laid. Official communication comes too late, in an environment that has become hostile.
2️⃣ Human weak signals
Chronic fatigue, self-censorship, unusual silences, withdrawal from teams, gradual disengagement. These signals are well known from studies on organisational accidents and systemic crises.
Numerous post-crisis analyses (in the cyber, industrial and healthcare sectors) reveal a recurring pattern: warnings existed but were not circulated.
Consequences observed when they are ignored
- disappearance of early warnings;
- decisions made on the basis of partial or biased information;
- rigidification of the organisation in the face of uncertainty;
- weakening of human coordination at critical moments.
In many cases, the crisis does not worsen because leaders ignored data, but because teams stopped talking.
3️⃣ Algorithmic weak signals and AI
Abnormal amplification of content, credible fakes, deepfakes, automated reputation attacks, biased or misinterpreted algorithmic recommendations. Recent reports from ENISA and the World Economic Forum agree on one point: AI accelerates, amplifies and obscures crisis dynamics.
Identified consequences
- rapid spread of false or misleading content;
- confusion between real signals and artificially amplified signals;
- decisions made under pressure based on a distorted perception of the situation;
- inability to regain control of the pace of information.
In this context, the problem is no longer just detection, but the ability to distinguish between what is real and what has been manipulated, in time. The response time is no longer measured in days but in minutes.
4️⃣Organisational weak signals
Recurring malfunctions, persistent silos, postponed decisions, reassuring but misleading indicators, unclear responsibilities. These signs reveal a structural inability to see, decide and act in time.
Post-crisis analyses (cyber, industrial, health, financial) show a consistent pattern: the information existed, but the organisational system did not allow it to circulate or be effectively taken into account.
Identified consequences
- gradual weakening of decision-making capacity;
- chronic delay in responding to warning signs;
- accumulation of decisions made by default or inertia;
- increased reliance on partial or retrospective indicators;
- loss of control over critical sequences of events.
In other words, when an organisation is already slow, fragmented or blind, AI does not fix anything. It accelerates bad decisions, amplifies blind spots and freezes default trade-offs.
Incorporate weak signals into dashboards, provided you change your stance
Weak signals are not invisible. They are relegated, deliberately or not. Because they already exist in HR data, collaborative tools, digital uses, internal exchanges and IT support processes. They are concrete, accessible observations produced by the daily functioning of organisations.
The problem is therefore not the lack of data, but the way in which it is interpreted, or rather what we choose to do with it.
In reality, these signals are, at best, considered secondary; at worst, they are ignored or neutralised because they do not fit into traditional performance frameworks.
Taken in isolation, they seem insignificant – lower participation, shorter responses, longer delays, fewer cross-functional initiatives. But taken together, over time, they reveal chronic collective fatigue, a loss of confidence, a deterioration in relationships, and a gradual withdrawal of local leadership.
Contrary to what one might fear, integrating weak signals into a dashboard does not require complex tools or sophisticated models. Above all, it requires a change in attitude, accepting that certain indicators are not used to optimise, but to alert.
Where traditional dashboards seek to confirm that everything is working, weak signals indicate precisely where something is beginning to crack, long before the crisis becomes visible, nameable or exploitable by the media.
Making weak signals visible, an example
The table below illustrates how ordinary indicators — often tracked for other reasons — can become powerful warning signals when interpreted as more than just operating metrics.
Modern prevention isn’t about stacking more KPIs. It’s about connecting micro-variations across the system — human, social, informational, emotional.
| Domain | Signal to observe | Where to detect it | What it really means |
|---|---|---|---|
| Internal Climate | Drop in survey participation Shorter, more neutral responses | HR tools Anonymous forms | Care is declining. The emotional fabric is thinning. |
| Digital Interactions | Rise in emails with +3 recipients Slower response times | Internal messaging | Trust is eroding. Communication turns defensive. |
| Collective Energy | Increase in micro-absences Drop in activity on Mondays and Fridays | HR Data Badge logs System log-ins | Energy is leaking. The collective is running on empty. |
| Governance Transparency | Growth in anonymous feedback or “no-name” questions | Feedback tools Internal Meetings | People still speak — but no longer face-to-face. Rumours fill the gap. |
| Cohesion & Belonging | Fewer reactions on internal posts Decline in cross-team initiatives | Intranet Yammer Teams | The we turns into each for themselves. |
| Proximity Leadership | Cancelled meetings Fewer informal exchanges | Agenda On-site observations | Management is drifting away from reality. |
| Perception of Security | Surge in “unconfirmed” tickets or false cyber alerts | Helpdesk / IT | The emotional climate of safety is deteriorating. |
👉 These signals complement traditional indicators. They capture the human dimension that figures overlook: confidence, fear, fatigue, loyalty.
The CMVRH fact sheet on workplace discontent lists classic manifestations of weak signals: withdrawal, isolation, tardiness, demotivation, decreased concentration, etc.
In an industrial setting, the HSE Guide points out that unusual noise from a machine or an unusual frequency of minor incidents are weak signals that are often overlooked.
