Presented by ArmAI is no longer confined to the cloud or data centers. Increasingly, it’s running directly where data is created — in devices, sensors, and networks at the edge. This shift toward on-device intelligence is being driven by latency, privacy, and cost concerns that companies are confronting as they continue their investments in AI. For leadership teams, the opportunity is clear, says Chris Bergey, SVP and GM, of Arm’s Client Business: Invest in AI-first platforms that complement cloud usage, deliver real-time responsiveness, and protect sensitive data. “With the explosion of connected devices and the rise of IoT, edge AI provides a significant opportunity for organizations to gain a competitive edge through faster, more efficient AI,” Bergey explains. “Those who move first aren’t just improving efficiency, they’re redefining what customers expect. AI is becoming a differentiator in trust, responsiveness, and innovation. The sooner a business makes AI central to its workflows, the faster it compounds that advantage.” Use cases: Deploying AI where data livesEnterprises are discovering that edge AI isn’t just a performance boost — it’s a new operational model. Processing locally means less dependency on the cloud and faster, safer decision-making in real time. For instance, a factory floor can analyze equipment data instantly to prevent downtime, while a hospital can run diagnostic models securely on-site. Retailers are deploying in-store analytics using vision systems while logistic companies are using on-device AI to optimize fleet operations. Instead of sending vast data volumes to the cloud, organizations can analyze and act on insights …
