AI inferencing is headed for the network edge
Processing IoT/OT data as close as possible to the source has been a longstanding goal for IT leaders.
Processing IoT/OT data as close as possible to the source has been a longstanding goal for IT leaders.
The short version
- Recent technological advances are now making it possible to perform full-blown AI inferencing at the network edge , opening the door for game-changing applications that can respond autonomously to sensor data in real time.
- “The combined rapid growth of edge data and the imperative that businesses now have to leverage AI capabilities for business value are leading inevitably toward significant edge AI growth,” says Gartner analyst Thomas Bittman .
- By 2028, more than two-thirds of enterprise-managed data will be created and processed outside the data center or cloud, Gartner predicts, and more than two-thirds of all enterprises globally will deploy edge AI by 2029, up from 10% in 2025.
What happened
Likewise, IDC expects that half of all enterprise AI inference workloads will run on endpoints or edge nodes by 2030, according to the firm’s 2026 FutureScape IT predictions . “Enterprises are increasing edge IT investments to support genAI/AI inference, with strong momentum in healthcare, finance, and manufacturing,” says Olga Yashkova , IDC’s research manager for edge AI strategies.
Why it matters
A variety of factors are coming together to make edge AI a high priority for IT executives.
Summary by Nerd News Network. Read the full article at Network World via the links above and below.