The landscape of physical devices has undergone a dramatic transformation. What once were simple, connected tools that synced data and enabled remote control have now evolved into a sophisticated, intelligent ecosystem driven by generative AI (Gen AI). This evolution is revolutionizing how physical devices interact with the world around them, transforming them from basic utilities into dynamic, responsive entities that reshape our interactions and experiences.
The Evolution of Smart Devices
Figure 1: Evolution timeline of smart devices
Gen AI has revolutionized smart devices by enabling them to create new content and experiences rather than just processing data. These devices are more context aware to understand and respond to complex queries in a business context. For instance, a Gen AI voice assistant supports an investment manager with data analysis in a financial services firm. When asked, “What are the performance metrics for our top 10 portfolios this quarter, and how do they compare to market benchmarks?” the assistant analyzes vast amounts of financial data, retrieves relevant performance metrics, compares them to market benchmarks, and identifies trends. It then provides a summary report with insights on underperforming portfolios and recommends strategic adjustments.
The transformative shift from deterministic AI to Gen AI will enable smart devices to offer more dynamic and personalized interactions, vastly enhancing user experience and capabilities. In terms of enterprise applications, these cutting-edge Gen AI-backed devices are emerging in three primary categories:
- Advanced physical assistants: Devices like rabbitr1 and Humane Ai Pin can streamline business operations, acting as intelligent personal aides that go far beyond the capabilities of traditional AI by leveraging Gen AI for more complex and nuanced tasks.
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- Predictive inventory and maintenance: In a complex supply chain scenario, these devices can identify patterns in usage rates, seasonal demands, and supplier lead times. For example, in a global logistics company, the rabbitr1 device can predict a shortage of critical parts weeks in advance by analyzing supply trends and machine performance data from multiple locations. This proactive approach allows for adjusting orders and maintenance schedules, reducing downtime, and optimizing operational efficiency, a level of foresight and precision that traditional AI struggles to achieve.
- Personalized customer engagement: In retail, AI-powered assistants can analyze customer data and browsing habits to offer tailored product recommendations and support in real time. An AI pin can give a sales associate instant insights into a customer’s preferences and purchase history, enabling personalized suggestions and enriching the customer journey.
- Laptops: The emergence of Gen AI features in new-age laptops brings a paradigm shift in productivity and performance. Microsoft’s Copilot+PCs, for instance, provides AI chatbots accessible via a Copilot button in the device, revolutionizing workflow efficiency while optimizing power usage based on user habits and tasks. Meanwhile, ASUS Zenbook Pro 17 leverages Gen AI to perform complex tasks such as image recognition and object detection on the device.
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- Enterprise AI workload acceleration: Gen AI laptops, equipped with dedicated Gen AI processors such as Qualcomm’s Hexagon NPU, can run Gen AI workloads up to 98% faster and with 40% less power, empowering businesses to tackle demanding AI workloads such as financial modeling and complex simulations.
- Advanced cybersecurity threat detection: Gen AI laptops seamlessly integrate with enterprise-grade security frameworks, ushering in an automated data governance and risk management era. These devices can identify unusual patterns and potential breaches faster than traditional systems. This proactive approach helps safeguard sensitive data and maintain the integrity of enterprise systems.
- Wearables: Innovative Gen AI wearables are redefining the digital workplace. Zepp’s Gen AI watches track employee stress for well-being, while Google AI glasses offer real-time info overlay for efficient tasks, boosting safety and efficiency.
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- Predictive performance and risk mitigation: Gen AI-powered smartwatches, like Zepp, can be used in an enterprise setting to analyze employee data to predict potential fatigue or injury risks. This can enable businesses to proactively manage employee well-being, prevent downtime, and boost workforce productivity by offering AI-driven coaching and health insights.
- Enhanced efficiency and quality control: In manufacturing, smart glasses equipped with Gen AI utilize real-time data to guide workers, identify defective components, and predict maintenance needs. This application fosters efficient workflows, minimizes errors, and optimizes production quality.
What’s Next?
In the next 12 months, significant simplification is expected in AI-related form factors. Many current devices may not keep pace with the rapid evolution of AI. For example, the demand for physical assistants is declining as advanced voice assistants from Google, Apple, and OpenAI increasingly address the same use cases these devices were originally designed. Rather than new gadgets, customers now seek software solutions integrated into existing devices like smartphones, watches, and glasses. This trend is evident as only 5,000 out of 100,000 RabbitR1 buyers still use the device daily, just five months post-launch. Similarly, the Humane AI Pin saw high product returns and order cancellations. These examples highlight a clear user preference for simplifying AI and Generative AI usage through existing devices.
From a capability standpoint, as the emotional intelligence, reasoning capabilities, and context length of LLMs continue to evolve—exemplified by GPT-4o’s advancements in emotional intelligence, Google Astra’s superior reasoning abilities, Gemini’s anticipated context length of 10 million tokens by 2025, and a new human-computer interaction paradigm as displayed by Meta’s Orion AI glasses—their applications will expand to encompass more complex decision-making and recommendation-based use cases across various industries. This evolution will profoundly transform the role of intelligent devices such as laptops, wearables, and voice assistants. Laptops will handle highly complex tasks and process enormous parameters directly on the device, eliminating the need for cloud-based computations while enhancing security and speed. Voice assistants will empower employees and customers with real-time data insights and actionable instructions, revolutionizing customer service and operational efficiency. Wearables will transcend current functionalities, visualizing complex scenarios and aiding decision-making through real-time data simulations.
Figure 2: Gen AI-driven smart device use cases across sectors
As these devices become smarter with advanced LLM capabilities, they will seamlessly integrate into enterprise workflows, driving innovation and efficiency across industries. The future promises a dramatic shift where technology not only supports but anticipates business needs, enabling a new era of intelligent, interconnected systems that redefine operational processes and enhance decision-making in the digital world.
By Chandrika Dutt, Associate Research Director, Avasant, and Abhisekh Satapathy, Lead Analyst, Avasant
