Key takeaways:
From tools to environments
Ambient AI marks a shift from discrete, screen-based tools to pervasive, intelligent environments that actively shape our experience. As foreseen by Mark Weiser with his ubiquitous computing, intelligence is dissolving into our surroundings, becoming a silent, anticipatory presence.Co-thinkers and perceptual partners
Ambient AI extends human cognition and reshapes perception and emotion, subtly influencing how we feel and decide through mood-aware systems, gaze tracking, and emotionally responsive agents.Workplace and factory as shared cognitive fields
In both corporate and industrial settings, AI evolves from assistant to co-worker. It operates alongside humans, orchestrating workflows, simulating environments, and creating real-time, self-adaptive systems that guide decisions and optimize labor.Invisible power, designed values
As AI embeds itself into our environment, its ethical footprint becomes ambient too. The systems we inhabit are shaped by a few powerful actors, encoding specific values and potentially reinforcing human and social asymmetries.Staying human in intelligent surroundings
To dwell lucidly in an ambient world, we must cultivate critical awareness, systemic understanding, and the ability to intervene. The infosphere we inhabit is not neutral, it is designed. It’s up to us to design it in alignment with human dignity, agency, and meaning.
From tool to milieu: the rise of “Ambient AI”
The 20th century trained us to think of machines as tools: distinct, graspable, optional. We turned them on, we turned them off. They had edges. But with the rise of ambient AI, those edges are dissolving. Intelligence is no longer contained in screens or devices. It is dissolving into the walls, weaving through workflows, listening silently, suggesting discreetly.
When I talk about Ambient AI, I’m thinking of systems that are everywhere, quietly tuned in, and easy to overlook. They watch without asking. Sometimes, they respond before we even realize we need them to. They start to learn how we move, think, and decide, often before we’ve fully noticed it ourselves.
This evolution was foreseen as early as the 1990s by Mark Weiser, who coined the term “ubiquitous computing” and, in his 1991 article The Computer for the 21st Century, imagined a world where “the most profound technologies are those that disappear.” In his vision, computing would fade into the background, becoming part of the environment itself.
But Ambient AI isn’t just about making life easier. It changes how we experience space and even how we think. When we move through homes, cars, or workflows that seem to “know” us, we’re not just using smart tools; we’re living inside an environment that’s intelligent on its own. Philosopher Gregory Bateson described the idea of an “ecology of mind”, a system where thought, feedback, and action are shared between people and their surroundings. Ambient AI extends this idea into the digital world, creating environments where intelligence emerges from the interaction between humans and technology.
Moreover, our own intelligence begins to reorganize. Theories of distributed cognition (Hutchins) and extended mind (Clark & Chalmers) help us see that tools, especially cognitive tools, do not merely assist thought, they transform it. When your smart assistant finishes your sentence, anticipates your question, or edits your calendar, your mind is no longer bounded by your skull. You are already thinking with the machine.
Then, if we are increasingly co-thinking with ambient AI, are we still choosing the direction of thought or simply being nudged along the most efficient path?
A mind shared with machines
As artificial intelligence blends more deeply into the spaces we live and work in, it does more than simply assist our thinking, it begins to shape the way we think. The questions we pose, the options we perceive, and the paths we follow are increasingly influenced by adaptive systems that learn from our behaviors and, in turn, guide our choices.
To understand this shift, philosophy offers valuable frameworks. Pierre Teilhard de Chardin introduced the concept of the Noosphere: a global “thinking layer” enveloping the planet, marking an evolutionary leap where consciousness becomes collective and planetary. In his spiritual vision, this convergence of thought pointed toward an Omega Point, a final unity of meaning. Today, ambient AI can be seen as a secular counterpart: a digitally mediated noosphere, where billions of minds, streams of data, and autonomous algorithms are intertwined in a shared cognitive ecosystem. Yet this new noosphere is not a neutral space. It is constructed, regulated, and commercialized.
Philosopher Luciano Floridi describes the “infosphere,” a semantic environment where humans and non-human informational agents “inforgs” coexist and interact. Here, decisions are encoded, data becomes infrastructure, and every interaction is logged and traceable. Unlike air or water, the infosphere is designed and that design embodies specific values and priorities.
At this intersection, the work of Bruno Latour is also interesting. His theory of socio-technical networks reveals that technology is not a passive tool but an active participant: it delegates, frames, and shapes action. In the context of ambient AI, this agency is pervasive yet often invisible. Recommendation engines, prioritization algorithms, and digital twin simulations do not only assist us; they pre-structure the field of possible actions and outcomes.
In this way, ambient AI becomes more than a technological backdrop, it becomes a philosophical environment, one that not only surrounds us but actively formats our experience of reality.
Take for example the latest announcements from OpenAI and Google, which illustrate just how rapidly ambient AI is moving from theory to lived reality. OpenAI, following its acquisition of Jony Ive’s design studio and the AI hardware startup io, has unveiled plans for a new generation of AI-powered devices that break away from screens altogether. These upcoming devices, expected to be pocket-sized, screenless, and contextually aware, are designed to gather information from their surroundings through built-in microphones and cameras, enabling them to act as truly ambient companions. OpenAI’s vision, as described by its COO Brad Lightcap, is to build an “ambient computer layer” that operates in the background of daily life, offering personalized assistance without the need for direct interaction with a display.
Meanwhile, Google’s recent I/O 2025 event showcased how deeply AI is being woven into its ecosystem. The new Gemini 2.5 model, equipped with “Deep Think” mode, now powers an “AI Mode” in Google Search, transforming the experience from keyword queries to natural, conversational exchanges that deliver AI-generated summaries and insights. Project Astra, another highlight, aims to turn smartphones and future wearable devices into multimodal AI assistants capable of understanding images, sounds, and context in real time, offering proactive help that feels intuitive and ever-present. Across Android 15 and Google’s suite of services, Gemini now acts as an overlay, ready to assist users contextually on any screen or app.
These developments signal an accelerated shift: AI is no longer just a tool we use, but an intelligent layer that shapes, anticipates, and responds to our needs as we move through the world.
This is the silent revolution: the transformation of thought itself into a function of ambient computation.
Beyond cognition: the ambient ecology of sensation, affect, and identity
We often speak of AI as if it interacted only with our reasoning minds, a partner in thought, not in feeling. But ambient AI is becoming increasingly “affective”, “sensorial”, even “intimate”. It doesn’t just process what we say; it reads our moods, anticipates our gestures, follows our gaze, senses our stress.
As philosopher Don Ihde suggests, technologies don’t sit apart from us, they mediate how we see, feel, and move through the world. They shape what we notice, what feels close, what stands out. Ambient AI in smart glasses, voice interfaces, biometric sensors, can become a prosthesis of perception. Sometimes, a filter of the self.
Take Meta’s Aria Gen 2 glasses: equipped with advanced sensors, they track your gaze and respond to your voice, allowing for smooth, hands-free interaction. But they don’t just display information, they begin to interpret your surroundings, offering real-time insights based on where you look and what you say. In that sense, they’re not just tools but perceptual partners. Seeing becomes something shared, a kind of co-seeing, where what you notice is subtly shaped by both your own attention and the AI embedded in the device.
And that sensory coupling has emotional weight. As theorist Brian Massumi writes, affect often comes before thought, in the subtle charge of a moment, before we name it. When ambient systems trigger lights, sounds, music, or suggestions based on these signals, they don’t just respond to our feelings, they help shape them.
Think of Spotify’s mood-driven playlists, looping back what we want to hear. Another example is The For You page on TikTok that uses granular behavioral signals, like watch time, scrolling speed, and replays to infer our interests. It functions not just as a recommendation engine, but as a dynamic feedback system that learns from and subtly shapes our emotional engagement.
Meanwhile, ambient AI edges into intimacy. Tools like Replika, Character.AI, or GPT-based personas offer responsive agents that some treat as friends, therapists, even digital versions of themselves.
Ambient AI in the enterprise and the factory
If ambient AI transforms our perception and attention in everyday life, it redefines the nature of work in the corporate and industrial world. No longer confined to back-end analytics or task automation, AI now permeates the very fabric of decision-making, team collaboration, and operational flow.
From assistant to co-worker: Ambient AI in the corporate stack
Enterprise tools are rapidly shifting from passive platforms to active cognitive environments. Consider Microsoft’s Copilot, an ever-present assistant in Teams, Outlook, and Word. It drafts your emails, summarizes your meetings, proposes actions. You no longer “use” it, you work in parallel with it.
Similarly, Salesforce’s Agentforce deploys ambient agents that orchestrate CRM workflows, autonomously trigger processes, and initiate customer interactions. The user is still there, but often after the system has begun thinking.
The shift is functional and ontological. Work is becoming a space shared with algorithmic agents, each with a form of delegated judgment. These agents are context-aware, data-rich, invisible and increasingly proactive.
Another example is Microsoft’s Dragon Ambient eXperience (DAX) in healthcare: a voice-based ambient AI system that listens to doctor-patient conversations, fills out medical records in real time, and offers contextual suggestions. Doctors are relieved from bureaucracy but also guided in how they structure their interactions.
Similarly, LLM’s integrated with browsers and productivity tools enables a form of continuous, multimodal collaboration. They read, summarize, and act within documents, emails, or research threads. The line between agent and colleague is blurred.
These developments raise interesting questions: Who decides what the AI notices? Who designs its behavioral models? How do we train users to coexist with invisible co-workers?
Ambient intelligence in industry: the cognitive factory
In industrial settings, ambient AI takes a more embodied, infrastructural form. Smart factories, edge AI, digital twins, and predictive maintenance systems form a sensing, learning, self-correcting environment.
Take BMW’s collaboration with NVIDIA Omniverse, which enables the design and simulation of entire factories in real-time 3D environments. Workers are trained, flows are optimized, issues are preemptively resolved often before a single bolt is turned in the real world.
Or consider robotic systems in bakeries like Priestley’s, where autonomous vehicles deliver materials, adjust routes, and communicate with human workers via ambient signals. The environment thinks with them, not just for them.
Ambient industrial intelligence also manifests in AR interfaces, where workers are guided by spatial overlays, real-time diagnostics, and gesture-controlled assistants.
The result is a new kind of human-machine symbiosis where intelligence is not located in the head, nor in the tool, but in the field of interaction itself.
In both office and factory, ambient AI is changing not only what we do, but how we perceive action, where agency resides, and what kind of attention we cultivate.
Are we shaping ambient intelligence or is ambient intelligence shaping the human within the system of work?
Governance, autonomy, and the ethics of cognitive milieus
As AI becomes ambient, its ethical footprint becomes ambient too: diffuse, pervasive, and often invisible. When decision-making is shared with non-human agents, when our perceptions are nudged by imperceptible feedback loops, the question of governance becomes both urgent and elusive.
Who shapes the infosphere?
The ambient AI environment is not self-regulating. It is architected, often by a handful of actors: Big Tech platforms, cloud providers, infrastructure designers. Philosopher Luciano Floridi has warned that the infosphere — the semantic space in which we now live — requires an informational ethics: one that doesn’t only concern data privacy, but the very design of interaction, influence, and intelligibility.
Yet today, that governance is opaque. Microsoft’s Model Leaderboard, ranking models not just by performance but by “safety,” implicitly defines what is considered trustworthy cognition but who sets the criteria? With what accountability?
As Ruha Benjamin and Shoshana Zuboff have shown, algorithmic infrastructures tend to reproduce existing asymmetries: of race, class, geography, access to literacy. When ambient AI becomes the norm, whose experience of the world is being encoded and whose is being flattened?
The infosphere is not just a layer of thought. It is a terrain of power.
Human agency in a world of intelligent agents
In ambient systems, agency is distributed, but not equally. Responsibility becomes hard to locate. If a smart assistant misguides a user, or a predictive system silently misrepresents a risk, who answers? The developer? The organization? The user?
Floridi and Verbeek argue for a shift from human control to human-centered mediation: recognizing that we don’t need to control every action, but we must remain capable of situational discernment and override.
This is especially crucial in settings like healthcare, education, and public infrastructure. Fei-Fei Li has insisted that explainability, contestability, and human dignity must remain core design criteria not post-hoc ethical patches.
The challenge is not only to keep “humans in the loop,” but to cultivate humans above the loop: individuals and societies capable of orienting themselves in increasingly intelligent environments. This requires:
Awareness: understanding how these systems function, and how they affect us.
Skill: the capacity to intervene, audit, or reject decisions.
Governance: institutions that monitor and arbitrate collective impact.
In the end, the ethical challenge of ambient AI is not whether it is good or bad. It is whether we are still capable of living lucidly within it, designing it to reflect our better angels.
Dwelling lucidly in the algorithmic atmosphere
Every environment carries a metaphysics. What surrounds us, shapes us. And the infosphere we are weaving, half-intentionally, half-mechanically, is not inert. It is predictive, persuasive, persistent. It learns faster than we do. It forgets nothing. And above all, it is designed.
If we are to remain human in such a space, not just biologically, but ontologically, we must learn to inhabit it consciously. Not just as users, but as stewards. Not just as beneficiaries, but as framers.
This means:
Rethinking education, not only in STEM (Science, Technology, Engineering, and Mathematics), but in ethics, perception, and systems thinking.
Reclaiming time and attention, resisting the passive drift of ambient guidance.
Redefining agency, not as control, but as the ability to shape direction amidst complexity.
Building governance architectures that mirror the ambient nature of the systems they regulate: decentralized, contextual, adaptive.
And above all, it means remembering that this “infosphere” is not air. It is not neutral, nor given. It is a constructed ecology and one that can be redesigned.
The human being, in its irreducible singularity, embodied, vulnerable, relational, symbolic , remains above the loop, not because of power, but because of meaning.
We can still choose the kind of air we want to breathe.
Personal Reflections on the Digital Age
This article is part of my series exploring the anthropological dimensions of our digital revolution. As both a digital transformation professional and someone fascinated by technology's impact on humanity, I examine the paradoxes shaping our relationship with digital tools.
I offer these reflections with humility, recognizing how challenging it is to analyze transformations we're still experiencing. Nevertheless, I believe those of us involved in technological change have a responsibility to consider its human consequences.
With limited time, I focus my energy on researching and developing key insights rather than perfecting prose. I use AI assistance for writing, particularly helpful since English isn't my native language, allowing me to share these ideas with an international audience.
My aim is to contribute thoughtfully to our understanding of what it means to be human in this unprecedented age of digital mediation, exploring both the opportunities and challenges of our evolving technological relationship.
Reading this felt like stepping into the exact tension I’ve been living inside, but seen through a wider, more articulate lens. I’ve been writing from a very different place, hands in the code, working alongside assistants, but the same questions keep surfacing: What happens to our attention when AI starts to think with us?
In my own work, I’ve been exploring what I call the "Cognitive Canvas", a way to stay close to the shape of my own thinking before engaging AI. Naming the friction, noticing the drift, protecting the parts of myself that still feel.
Thank you for writing this the way you did. It’s rare to see something so expansive hold such precision.
Bravo pour avoir su adresser ce sujet avec autant de facettes en un seul article profond !