Consumers increasingly expect smarter capabilities in their connected home devices, while maintaining an eye on price and security. Parks Associates, in collaboration with Silicon Labs, sheds light on the growing role of edge artificial intelligence (AI) in product development for the Internet of Things (IoT). With AI integration on the device itself, brands can address major adoption barriers, power more advanced features, and create new service opportunities. As smart home device ownership grows, the market shifts focus toward practical and affordable intelligence built into products. Concerns about privacy and monthly costs also steer many companies toward refining where and how AI operates in their product lines.
Unlike earlier studies, which emphasized rapid increases in smart home adoption and cloud-only solutions, the current research details a more mature landscape where nearly half of US internet households now own at least one connected device. The integration of edge-focused AI represents a shift from primarily cloud-reliant intelligence to a hybrid or device-centered computing model. Whereas past analyses highlighted cloud infrastructure as the foundation for connected services, the new findings indicate a move toward decentralized processing, with greater attention on cost control and user benefits. This marks a significant evolution in both consumer expectation and manufacturer response.
What Makes Edge AI Attractive in Smart Home Devices?
Edge AI, with its ability to process data directly on connected devices, addresses the dual goals of affordability and smart functionality. By running algorithms on-device—thanks to advances like on-chip AI accelerators from companies such as Silicon Labs—manufacturers can build products that perform tasks like voice detection and environmental awareness without the need for constant cloud access. According to Parks Associates VP, Jennifer Kent,
“Edge-based AI is a key enabler in reaching that two-pronged goal, supporting advanced behaviors such as presence awareness and audio/voice detection without incurring additional cloud fees.”
Where Do Consumers and Companies See the Most Value?
Surveys reveal that 52% of participants are open to paying monthly for intelligent home assistants, representing a potential market exceeding $12 billion annually for AI-enabled services. However, cost remains a concern for many households; 44% of non-owners perceive smart home products as overpriced, and 42% question their personal value. Device makers see edge AI as a path to enhance perceived value and reduce reliance on expensive cloud computing, which could make smart home technology more appealing and financially accessible.
How Are Hardware Choices Shaping AI in IoT?
Hardware innovations, especially system-on-chips (SoCs) with embedded AI capabilities, influence how effectively products can provide intelligent features at low power and cost. These advances make it feasible for brands to introduce functionalities—such as anomaly monitoring and health applications—that were once limited to cloud-based processing. Daniel Cooley, CTO at Silicon Labs, commented,
“The future of IoT is Connected Intelligence—where wireless connectivity and AI converge so devices don’t just connect, they decide and act.”
This shift in architecture not only facilitates new applications but also supports privacy by minimizing the transfer of sensitive data.
Product teams now face complex decisions about data handling, striking a balance between consumer experience and operational costs. Processing information at the edge can help reduce latency, improve data privacy, and lower dependency on ongoing cloud investments. Parks Associates emphasizes that as the AI landscape evolves, a mix of edge and cloud strategies is emerging, both for performance optimization and to address consumer hesitations surrounding value and transparency.
Edge AI is poised to significantly influence the direction of smart home solutions and IoT offerings. Manufacturers weighing the cost-value equation may benefit from exploring edge intelligence, especially as technology matures and becomes more standardized. Product managers should assess hardware choices carefully, as SoCs and accelerators present opportunities beyond just cost savings—such as improved privacy and new, locally processed features. The competitiveness of future smart devices will depend not only on novel features but also on effectively addressing user concerns over expense, utility, and data protection.
