New Analyst report

Growth in AI Agents Will Require an Edge Inferencing Strategy

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The rapid evolution of AI agents, from predictive models to autonomous systems, is transforming industries with unprecedented efficiency and innovation. Edge computing has emerged as a critical pillar for their effective deployment, by addressing critical needs such as latency reduction, bandwidth optimization and enhanced privacy. Unlocking the full potential of AI agents across industries demands a future-ready strategy: deploying AI inferencing capabilities at the edge to drive performance, innovation, and real-time impact.

Highlights:

  • Edge computing is critical for AI agents: It minimizes latency, optimizes bandwidth and enhances data privacy, ensuring real-time operational efficiency—even with intermittent cloud connectivity.
  • Data security at the edge: By processing sensitive data locally, private AI with edge computing balances regulatory compliance and privacy, reducing risks while creating a flexible AI ecosystem.
  • Metro edge: Strategic colocation facilities in major metropolitan areas, close to end users and data sources ensure high-density compute, advanced cooling and interconnection for AI workloads.
  • Future-ready synergy: AI agents operating effectively at the edge can transform industries with pervasive intelligence and automation—driving the next wave of innovation and competitive advantage.
Edge computing is not merely a technical option; it is a fundamental pillar of AI's future. It directly enables the real-time responsiveness, data privacy, and operational resilience that advanced AI agents demand.
Dave McCarthy
Research Vice President, Cloud and Edge Services, Worldwide Infrastructure Research, IDC
Edge Computing IDC Colocation Interconnection
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