This article is part of an ongoing series about the future of artificial intelligence, drawing insights from LIFT Labs’ AI portfolio.
TL;DR
- Contextual AI is redefining personalization by making it more effective and less reliant on personally identifiable information (PII).
- AI is shifting away from demographic-based targeting and toward real-time, engagement-driven personalization.
- Two LIFT Labs startups are helping to define the future of AI-powered personalization.
What if AI could give you personalized and relevant recommendations—without ever knowing your name, age, or location?
For years, there’s been a truism in tech: personalization comes at the expense of privacy. Consumers want tailored experiences— including relevant product recommendations, curated streaming suggestions, and marketing that aligns with their interests. Older playbooks in tech meant extracting and analyzing personal data to get there, but especially today, personalization doesn’t have to mean privacy tradeoffs. With the rise of collaborative AI—where human insight and machine intelligence work in tandem—we’re entering a new era where context, not identity, is driving innovation.
Context Over Cookies: A Paradigm Shift in Personalization
Thanks to contextual AI—a more nuanced, adaptive approach to data that relies on engagement signals in the moment, not static identifiers from the past—companies have a new way to deliver personalized experiences. These applications can help analyze real-time engagement to deliver more responsive, relevant experiences, prioritize temporal and spatial context instead of identity, and reduce reliance on personally identifiable information (PII) while still driving conversions.
The implications are massive. Contextual AI not only simplifies compliance and enhances security—it can help build trust. And in an age of heightened data awareness, trust is currency.
Two LIFT Labs startups, in particular, are leading the charge within this space.
Zenapse: Emotions Drive Action
Zenapse is redefining personalization by adding an emotional layer to data-driven decisions. The company’s Large Emotion Model analyzes emotions, beliefs, and sentiment from interactions with 175 million consumers across more than 4.5 billion data points. Instead of relying on demographics or personal identifiers, Zenapse focuses on emotional signals—helping brands understand what moves their audiences at a deeper level.
With this model, companies gain precise insights into which offers, imagery, messaging, and calls to action are most likely to resonate with different audience segments. That results in smarter, more effective marketing that speaks to people’s motivations—without needing to know who they are.
Archetype AI: The Future of Personalization Is Physical
Archetype AI’s Newton, is a foundational AI model for the physical world. It analyzes real-time data from a mix of sensors—temperature, sound, motion, radar—and makes sense of it – hink ChatGPT, but for the real world.
The company envisions use cases across construction, manufacturing, and logistics, from predicting equipment failures to reducing workplace injuries. And unlike legacy AI models that struggle with messy, unstructured sensor data, Newton was built for this complexity from day one. Part of the LIFT Labs Fall 2024 Accelerator, Archetype is exploring how this additional context might inform truly unique home experiences.
From Identity to Interaction: A Shift in AI Thinking
The next wave of AI isn’t just smarter. It’s more personal, more responsive, and more rooted in the real world. As startups like Zenapse and Archetype AI demonstrate, personalization no longer has to mean collecting identifiers and analyzing user activity. Instead, AI can focus on what truly matters: real-time engagement, contextual cues, and physical signals that tell a more accurate—and less invasive—story.
