AI Virtual Assistants for Personalizing User Experience

⚡ AI Health Agents: One Size Doesn't Fit All ⚡ What Demographics Shape AI Adoption? 👇 📋 New Research in JMIR reveals critical insights into personalizing AI Agent modality for maximum benefit. This scoping review examined 43 studies investigating AI-powered conversational agents as virtual health assistants for chronic disease management. 🤖 Avatar-Based Systems: - Digital avatars showed higher user acceptance and compliance compared to text-only chatbots - Face-to-face conversation format strongly preferred - Anthropomorphic features increased social closeness and trust 🗣️ Voice-Based Systems: - Excelled with older adults through hands-free operation - More accessible in low-bandwidth areas - Faced challenges with speech recognition accuracy 📱 Text-Based Chatbots: - Better dialogue capabilities and empathy support - Simple interfaces but lacked emotional personalization 👥 User Subgroup Benefits: 🧓 Older Adults: - Preferred voice communication - Found avatars engaging and trustworthy - Benefited from hands-free interaction 📚 Limited Digital Literacy Users: - Voice systems reduced usability barriers - Anthropomorphic interfaces boosted engagement 🏥 Chronic Condition Patients: - Avatar systems excelled in:   - Diabetes management   - Cardiovascular monitoring   - Mental health support 🔑 Success Factors: 🤝 Anthropomorphic Features increased: - Trust - Compliance - Social closeness - User acceptance 🔄 Multimodal Interaction: - Combined text, voice, and visual elements showed highest engagement - Flexible interaction methods improved accessibility 💡 Key Takeaway: Success in AI healthcare requires tailoring the agent modality to individual user characteristics and needs. One size does not fit all. #HealthTech #AI #DigitalHealth #Telehealth #aiagent #agenticai #GenAI #healthcareai

👀 That moment when “one-size-fits-all” just doesn’t cut it anymore… and you’re all eyes on "personalized" By strategically combining AI and behavioral science, you can create the kind of impact that drops jaws 😮 That’s exactly what Amy Bucher and her team are doing at Lirio with precision nudging: hyper-personalized communications crafted from the fusion of AI tech and behavioral science expertise. So, what’s in their secret sauce for hyper-personalization? 1️⃣ *Behavioral Science Foundations* Lirio’s team builds interventions from both top-down and bottom-up research. They start with behavior change models and existing literature to pinpoint the key drivers of target behaviors. Then they blend in on-the-ground insights from stakeholders and partners to create an initial framework, or logic model. 2️⃣ *Precision Content Design* They identify behavior change techniques (BCTs) and translate these into content assets — bites and visuals that combine into engaging, targeted messages. 3️⃣ *AI Training & Iteration* Here, Lirio’s AI team steps in. They train AI “agents” with specialized jobs to determine the best content, timing, and channels for each person’s engagement. The AI agents work with a reward system that incentivizes various steps of the patient journey, from opening emails to scheduling and attending an appointment. Using contextual bandits (think of them as superhuman experimenters) and reinforcement learning (the aforementioned system of incentivizing behaviors), they continuously test different messages to maximize the target behavior (e.g., getting a mammogram). The result? Hyper-personalized messaging that respects each person’s unique context and helps them complete essential health tasks. 👋 Goodbye to the old days of one-size-fits-all interventions, and hello to personalized communications that address each user's unique situation. #AI #BehavioralScience #BehavioralDesign cc: Samuel Salzer Habit Weekly Nuance Behavior