Customers are more demanding than ever. Human-machine understanding will help deliver hyper-personalized experiences to help your business stand out.
A great user experience (UX) is critical to the success of technology. However great the potential of hardware and software, a poorly designed UX will curtail its usefulness. In an age of hyper-personalization, the focus on UX will be even more central, and that’s where human-machine understanding (HMU) plays an enabling role.
Hyper-personalization uses real-time data, artificial intelligence (AI), and machine learning to deliver highly tailored customer experiences. These data-led innovations are helping technology companies and big-name businesses to boost user experiences.
Think, for example, of the preponderance of devices, from phones and smart watches to rings and associated applications that continuously monitor our health to deliver tailored well-being advice proactively. Some modern wearables can even detect subtle signs of illness early or identify critical health events like loss of pulse. Then think of a bank developing AI-enabled services that understand your financial situation and requirements, suggesting personalized products, including loans, mortgages, and investments.
These pioneering developments provide adaptive experiences tailored to users’ unique needs and preferences. Yet we are only witnessing the start of the hyper-personalization revolution. The next stage will see businesses harness HMU to gain deeper insights into customer requirements and develop technology that interacts meaningfully.
Going one step further
Gen AI tools are already helping pioneering companies personalize interactions at scale. From enabling marketers to create tailored content for customers to developing AI-powered chatbots that understand queries and offer solutions, more organizations are using Gen AI to create tailored experiences. Chatbot adoption for customer support has risen dramatically — from 36% in 2023 to 43% in 2024, reflecting this growing trend.
However, going one step further and creating systems that can adapt to user preferences and their changing mental states and situations can help set a product or service apart from the rest. With HMU, companies can embrace these adaptations and develop deeper experiences that boost customer engagement and loyalty.
Just as a skilled entertainer observes their audience to gauge reactions and adapt their performance in real time, an HMU-enabled system can interpret user responses and adjust accordingly, delivering interactions that feel more intuitive, relevant, and human.
These developments can span everything from modelling individual preferences during an interaction to inferring internal states, such as attention, mood, or engagement, that influence what users take away from an experience. An HMU-enabled system can interpret these responses and adjust accordingly to deliver intuitive responses.
The consumer sector offers the most visible example of people and technology working together to create hyper-personalized user experiences. Let’s find out more.
Unlocking personalization: Lessons from the consumer sector
Advances in large language model-powered tools are supporting the shift to more personalized experiences. Evidence suggests almost 25% of consumers now use generative AI for shopping[1]. These AI-enabled developments are changing how humans and machines collaborate and influence each other’s decisions and actions.
Leading consumer applications demonstrate how understanding user interactions — from movements to expressions to behavior patterns — creates more natural experiences. This is evident in modern gaming experiences that respond to player emotions, theme park attractions that adapt to visitor reactions, and mental health apps that adjust their support based on user behavior patterns.
Other emerging technologies, such as virtual and mixed reality, are also being used to develop new customer experiences. Vision-based multimodal interfaces enhance context awareness, allowing systems to understand deeper levels of user intent. From virtual try-ons in retail environments to health apps that offer support based on user behavior, integrating data and technology with human interactions helps firms develop innovative and rich user experiences.
However, building user trust through transparent AI-enabled products and services and maintaining smooth customer experiences remains a delicate balance. Consumer businesses must maintain core functionality while focusing on sophisticated engineering techniques and user-centered design that delivers hyper-personalization
Achieving this balance is tough because the consumer sector’s technical requirements change constantly. Yesterday’s cutting-edge feature is today’s expectation. HMU-enabled solutions must be agile, adaptable, and capable of incorporating new customer interaction methods as they emerge.
What hyper-personalization means for your business
A new generation of applications is emerging. Whether it’s a travel service providing dynamic recommendations that adapt in real-time or social listening tools anticipating needs across multiple platforms, these AI-enabled systems are increasingly capable of understanding deeper levels of human intent and context.
Adaptive experiences will be the key differentiator in competitive markets. Whatever sector of operation, your business can’t afford to leave its customers behind. Creating systems capable of adapting not only to user preferences but also to their changing mental states and situations can set your product apart from competitors. The human/machine relationship needs to be at the heart of the user experience. With HMU, products can move beyond basic personalization to create dynamic, adaptive experiences that drive deeper engagement and loyalty, becoming indispensable to their users. Embrace HMU and get ahead in the age of hyper-personalization
[1] Capgemini Research Institute. “What matters to today’s consumer: 2025 consumer behavior tracker for the consumer product and retail industries”. 2025
Meet the authors
Michelle is a behavioral scientist specializing in the intersection of psychology, AI and digital systems. She applies an evidence-driven and technology-centric approach to understanding and influencing human behavior. She works with companies to use technology to create engagement and delight, within applications in a wide range of sectors.
Emma is a researcher and engineer working at the intersection of affective computing, cognitive science and human-centered AI. Her work explores how emotion-adaptive models, cognitively aware systems and multimodal approaches can improve human-machine interaction and support more intuitive, empathetic technologies.
James is a frontend engineer with expertise in XR and WebXR technologies, progressive web apps, and native applications. At Cambridge Consultants, he has contributed to a broad range of forward-looking client projects, collaborating with multidisciplinary teams to transform complex technical data into intuitive and engaging user interfaces.
Alexandre leads a global team of experts who explore emerging tech trends and devise at-scale solutioning across various horizons, sectors and geographies, with a focus on asset creation, IP, patents and go-to market strategies. Alexandre specializes in exploring and advising C-suite executives and their organizations on the transformative impact of emerging digital tech trends. He is passionate about improving the operational efficiency of organizations across all industries, as well as enhancing the customer and employee digital experience. He focuses on how the most advanced technologies, such as embodied AI, physical AI, AI robotics, polyfunctional robots & humanoids, digital twin, real time 3D, spatial computing, XR, IoT can drive business value, empower people, and contribute to sustainability by increasing autonomy and enhancing human-machine interaction.
Ali leads a team of specialists in AI, psychology, cognitive and behavioral sciences to create next generation technologies that can truly understand and support users in dynamic, strenuous environments. Ali holds a PhD in Robotics with focus on human-robot interaction and has more than 12 years experience in research and development for human-machine interaction.
