Clicks, scrolls, and surveys once told brands what customers did, not how they felt. Now, AI promises a more intimate read. Synthetic personas to models that read stress in real time, a new wave of emotionally aware technology is reshaping marketing, CX, and content. FutureWeek asked five execs at AI companies how machines are learning to read the room, and what it means for brands navigating empathy at scale.
Brian Kenny, co-founder and CEO, Momntum
“AI is helping brands understand how customers feel not because machines are suddenly more empathetic, but because they’re exposing how little emotional intelligence has existed in customer experience all along. For years, businesses relied on surface-level feedback and scripted interactions. Customers saw through that and are fatigued of not being able to get real help that they need.
“Now, AI can analyse millions of signals, tone, context, sentiment and surface real patterns in how people feel, not just what they say, at scale. Emotional intelligence is no longer a soft skill but a data point. But that insight only matters if brands are willing to act on it. Detecting stress, urgency, even resignation is powerful, if it leads to meaningful response. If you’re not designing customer experience systems that act on those emotional signals in real time, customers will turn to the next brand who can.”
Dr. Nadine Kroher, Chief Scientific Officer and co-founder, Passion Lab
“Many LLM-driven synthetic personas sound convincing on the surface but emotionally fall flat. The real progress comes when these models are configured based on unfiltered audience data — things like customer complaints, comment sections or survey answers. That’s where the accuracy gains come from in terms of how well the synthetic persona anticipates the answers or opinions of the real audience. When built properly, they don’t just echo brand sentiment. They question creative choices, pick up on awkward phrasing, and offer stronger alternatives.
“It feels less like research and more like rehearsal with a brutally honest audience. Until now, most emotional insight arrived too late or too sanitised to be useful. This technology allows teams to test tone and content in the moment, with far greater nuance. Of course, it only works if the models are configured and validated carefully. Otherwise, the empathy is just an illusion. Done well, these systems act as early-warning signals for emotional missteps.”
Dr. Richard Blythman, co-founder and Chief Scientific Officer, Naptha.AI
“Older systems relied on shallow proxies like words per minute or speech cadence that couldn’t fully capture emotional nuance. They lacked context, and so tended to treat all inputs the same. With machine learning and multimodal models, we can now process text, voice, and behavioural signals together, making emotional understanding vastly more accurate. If the purpose of understanding emotion is to drive empathy, then recognising that someone is stressed or confused allows brands to offer the right type of support, rather than simply respond to explicit complaints.
“As for the implications, they can certainly go further. This technology can change how marketing is delivered, via a new kind of dialogue that is more ethical and responsive, ultimately driving customers’ trust and loyalty. Conversely, there is also the risk of crossing into manipulation. For example, if a chatbot attempts to “upsell” based on specific personal data, it can feel disingenuous because you know it’s simply running a revenue- maximising script. Striking the right tone and knowing when to dial it back is crucial.”
Marc Fernandez, Chief Strategy Officer, Neurologyca
“Traditional analytics track behaviour like clicks, views, and scrolls, but miss the why behind those actions. Human Context AI fills that gap by interpreting micro-expressions, gaze patterns, and subtle affective signals to infer attention, cognition, and emotion. We translate these cues into insights that reveal how content actually resonates with people, not just whether they consume it. This helps brands understand not just what worked, but why it worked, emotionally, cognitively, and contextually. Emotion is nuanced. It is not easily reduced to binary signals or basic sentiment. Previous systems relied on proxies like emoji reactions or keyword sentiment, which missed the complexity of real human response.
“We’ve built a system grounded in neuroscience and computer vision to decode genuine attention and emotion in real time, without needing surveys or staged feedback. That marks a significant shift from assumption to real understanding. Emotions reflect broader context including stress, attention fatigue, curiosity, or trust. When brands can detect these signals, they move beyond just optimising content. They gain insight into mindset and daily reality. This has implications across marketing, education, public service, and even mental health. Human Context AI brings us closer to emotionally aware systems that can adapt to how people actually feel, not just what they do.”
Dr. A.K. Pradeep, CEO and founder of Sensori.ai
“Emotions are powerful drivers of desire. The “cultural zeitgeist” is driven by primary feeds to the non-conscious mind, often amplified by events in world. Algorithmically understanding the emotions triggered by popular music, TV shows, and movies, and which of them are amplified by news and media enables brands to feel the emotional state of their audience. We collect this vast non-conscious data for 200 countries every week and are able to predict the dominant emotions and the nuances of them. We’ve created and curated a library of “Synthetic Humans”, “Digital Twins” if you may, that will react and experience emotions the way humans would.
“This neuroscience-enabled Digital Sapiens, can then react to products and messaging the way the natural consumer would – the world’s first Gen AI and neuroscience-powered Focus Group is here. It has been hard to do it in the past as the proper blend of Gen AI and Neuroscience was just unavailable. Dynamic simulation and interactions of Digital Sapiens was not possible because of compute restrictions. Now, we are able to simulate Digital Sapiens’ interactions. These capabilities provide brands the ability to deeply understand the nuances of daily life of customers and their implications to what messages, innovations, and promotions may speak to them. It also allows “mass personalisation” of messages and product features.”
