Since this is an emerging category of technologies, there’s always new innovations and trends of which to keep track. My colleagues and I got together to create a list of the most important trends to follow across edge and IoT. We unpacked them in our recent report, The Top 10 Trends In Edge Computing And IoT, 2023. Here is a preview of four of my favorites:
- Processor sophistication increasingly varies by use case. Digitalization and increased connectivity extend opportunities to power products and IT/OT systems with processors. But the wrong processor may eliminate cost-efficiencies or fail to deliver experiences in the time required. Some firms are pushing for specialized low-power microcontrollers for IoT devices or powerful NVIDIA H100 AI GPUs to handle AI workloads. Others are looking for a common architecture, such as that from Arm, that makes it easier to build chips and address customized design requirements.
- Expanded IoT deployment in smart buildings enhances efficiency and sustainability. Facility managers can use IoT-enabled building systems to enhance efficiency, increase critical building system automation, and provide actionable insight into critical building operations. Many firms initially focus on energy management and HVAC system monitoring to address sustainability goals (e.g., reducing Scope 1 and Scope 2 greenhouse gas emissions) or to monitor environmental conditions. Proactive firms should extend their smart building initiatives to address security by integrating surveillance systems and access control protocols to protect occupants from potential threats or emergencies.
- Edge computing powers genAI experiences and content personalization. Edge computing distributes compute, storage, processing power, and workloads for generative AI (genAI) models at the relevant edge devices. GenAI model training and data analysis are performed directly on edge devices to create personalized recommendations and experiences addressing specific use cases (e.g., predictive maintenance on medical equipment, industrial quality inspection, enhanced real-time decision-making). Coca-Cola, for instance, is using OpenAI’s ChatGPT and DALL·E systems to generate personalized ad copy and images at scale. Benefits of this approach include reduced latency, minimized strain on centralized cloud infrastructure, and optimized bandwidth usage.
- Developers fragment to tackle engagement edge applications. Proactive enterprises are turning to edge development platforms to abstract away the complexity of shipping code into distributed points of presence at the engagement edge. There’s a confusing landscape of tools available from public cloud and specialized edge providers and a fragmented array of edge development platform vendors. Some offer a full stack of capabilities (e.g., underlying infrastructure for general-purpose workloads), while others (e.g., Cloudflare, Fastly, StackPath) address specific use cases (e.g., IoT, e-commerce). Developers deploying AI/ML workloads should focus on edge platforms supporting WebAssembly to enable these computationally intensive tasks with code that is fast to decode, compile, and execute.
To help you navigate the edge and IoT markets, here are a few steps that you can take:
- If you are a Forrester client and want to learn more about this topic, please schedule a guidance session with me, Michele Pelino, principal analyst.
- Explore the links to related research included below.
- Not a Forrester client? Please contact the Forrester account team.
Here’s a few more of my latest reports: