Artificial intelligence (AI) has rapidly become the technical development with the most profound impact on how we work, play, live, and interact. Although AI has been around for decades, earlier generations of expert systems, knowledge systems, and decision-support systems pale in comparison to the capabilities of the AI of today…and tomorrow.
Generative AI, agentic AI, predictive AI, and many others still under development not only promise substantially more accurate, contextually aware, and responsible, but are actually delivering. Concepts such as intelligent model orchestration, agent core, and multi-agent collaboration—discussed at length at Lenovo TechWorld at CES in Las Vegas—are transforming AI development and delivery. And, at the heart of this transformation are end-user client solutions. These not only include traditional compute clients such as desktops, notebooks, thin clients, workstations, and peripherals, but also embody a wide range of devices not normally associated with computing, such as eyeglasses, video cameras, medical devices, and more.
This trend shows up in many ways, such as market research data that puts the 2025 global on-device AI market at more than $10 billion, surging to more than $75 billion by 2033. But these powerful AI technologies are doing more than simply enabling client solutions with onboard intelligence; they empower these devices (and those still about to emerge from R&D labs) to act as both autonomous and collaborative edge systems. The industry saw glimpses of these capabilities when GPUs and NPUs became standard features in personal computers, but the transformation of client solutions is just kicking off.
For instance:
- Intelligent model orchestration optimizes use of a wide range of AI models across different types of systems using different chip architectures, enabling functions that demand high performance, precise calculations, and extremely low latency. This helps conserve energy usage, protect sensitive data, and deliver cost-efficient AI inference without taxing enterprise computing resources.
- Multi-agent collaboration supports the use of different types of AI agents for unique, custom tasks, including computer vision, professional-quality video production, cybersecurity risk detection/prevention, and omnichannel customer service.
- Agent core, a cognitive “engine” for AI agent deployment and optimization, helps enterprises get the most from the growing number and diversity of agents interacting within and among applications for contextual understanding, autonomous reasoning. For instance, agent core helps the new breed of AI personal computers manage workflows, improve security, juggle meetings, and assign tasks—all based upon user intent.
This means that manufacturers of this new class of client solutions, such as Dell, have invested substantial resources to deliver new solutions that leverage transformational architectural improvements. These include such trends as standardized on-board GPUs and NPUs, improved memory bandwidth, AI intent priority, more intuitive user experiences, and local, contextual, adaptive intelligence using both large language models and small, lightweight AI models.
While traditional technical advances in memory, compute, storage, networking, and virtualization will continue to be important for still-to-come clients, these new systems will make the most of AI tools, models, and services to promote AI democratization that is customized for each user’s needs. Technologies from Dell incorporating AI from the ground up at all design phases turn these devices into the embodiment of “AI for and by everyone.”
