Data as a Service for Utility Grid Modernization with the Advent of AMI 2.0

Introduction and context

The utility industry is navigating a significant transition in grid operations and infrastructure. As distributed energy resources (DERs), electric vehicles (EVs), and bi-directional power flows reshape the grid, utilities are under pressure to modernize their aging infrastructure while maintaining reliability, safety and regulatory compliance. 

Advanced metering Infrastructure (AMI) 2.0 emerges as a critical enabler in this transformation offering the intelligence, flexibility and responsiveness that AMI 1.0 cannot deliver. More specifically, AMI 2.0 meters generate significantly more data than AMI 1.0 meters by increasing the sampling rate, processing power and edge computing capabilities. A single AMI 2.0 meter can produce orders of magnitude more data than a first-generation smart meter by sampling voltage and current waveforms at much higher frequencies.

To clarify the shift in capabilities, the table below outlines the key differences between AMI 1.0 and AMI 2.0 across core operational and data dimensions:

This shift is supported by advancements in edge computing, AI/ML and IoT connectivity, which allow for real-time data processing and grid-edge visibility. Regulatory momentum is also building, reinforcing the need to demonstrate measurable value from investment to ensure long-term resilience and customer satisfaction.

Utilities across North America are at different stages in their AMI journey, each facing distinct challenges and opportunities:

• First movers adopted AMI 1.0 early and are now approaching meter end-of-life. To meet growing customer expectations and manage increasing grid complexity, many are transitioning to AMI 2.0. For example, Hydro One is piloting high-resolution meter data with NET2GRID to enable advanced disaggregation and EV event detection.
• Greenfield deployers have not yet implemented AMI and can leap directly to AMI 2.0, avoiding legacy constraints. National Grid is deploying Landis+Gyr's Revelo platform for edge-based sensing and event detection.
• AMI 2.0 innovators are already leveraging advanced capabilities like edge computing and real-time analytics. Con Edison is strengthening cybersecurity with Zero Trust Architecture and real-time auditing to support secure, scalable operations.

Problem statement

While many utilities recognize the need to modernize and are eager to transition from AMI 1.0 to AMI 2.0, the path forward is often complex and challenging. The shift requires not only new technologies but also new ways of managing data, operations, infrastructure, and security.

Data management

The transition to AMI 2.0 introduces a dramatic increase in data volume and complexity. Utilities must move beyond collecting data and storing it in a data warehouse that is processed later to extracting actionable insights and enabling cross-functional collaboration in near real-time —something many legacy systems are not equipped to support.

Operational complexity

The growth in DERs and EVs demands real-time coordination and flexible grid control. However, limited visibility into phase identification and asset connectivity makes it difficult to detect faults, manage loads, and maintain situational awareness at the grid edge.

Technology and infrastructure

Utilities still reliant on centralized data processing face latency and bandwidth constraints that hinder timely decision-making. Connectivity issues — such as spotty cellular coverage — and vendor lock-in further limit flexibility and increase long-term costs.

Security and governance

As data becomes more distributed and accessible, many utilities lack the governance frameworks needed to share it securely. This increases exposure to cyber threats and complicates compliance with evolving regulatory requirements.

Acceleration opportunities

Data as a Service (DaaS) is a concept that will enable Utilities to modernize their grids and optimize operations. By streamlining data capture and transformation (often at the source), utilities can achieve real-time visualization of energy usage, monitor asset health, and scale their data architecture for accelerated adoption of new technologies. The primary benefits of DaaS are:

• Outage reduction: DaaS and advanced analytics can help utilities reduce outage durations by up to 30%.
• Predictive maintenance: Maintenance efficiency can be improved by approximately 20%, resulting in fewer equipment failures and lower costs.
• Incident response: Real-time monitoring and centralized visualization will enable field crews to respond to incidents up to 25% faster, improving grid uptime and customer satisfaction.
• Cost savings: Gas utilities have reported operational cost reductions of 10–15%, along with enhanced safety and compliance.
• Analytics focus: In the electricity sector, 67% of analytics applications address prediction, 14% market simulation, and 7% demand-side management, all contributing to measurable efficiency gains.
• Customer experience: Utilities will see customer satisfaction scores rise by 15–20%, driven by improved data transparency and faster service restoration.

At the enterprise level, DaaS will support unified data access, distributed edge analytics, and open APIs for partners, fostering continuous improvement and adaptability. These advancements can help utilities meet evolving regulatory requirements, integrate distributed energy resources, and deliver reliable, resilient service.

Solution architecture

The DaaS architecture is designed to support both data center and edge compute environments. 

In the data center, ingestion mechanisms such as change data capture (CDC), batch, API and streams feed into data processing interfaces for distillation and rationalization. A master data management (MDM) foundation and vector databases support unified analytics and visualization platforms, accessible via end-user web UIs and tools. Common infrastructure components include access controls, orchestration, event monitoring, DevOps, compute and storage. 

At the edge, the architecture incorporates stream processing, compute/storage and edge devices with load balancing, all connected to centralized data centers and MDM foundations. Visualization platforms and IoT devices enable real-time insights and control, while compliance and change management are integrated throughout the solution.

Conclusion

Modernizing the grid is a complex but essential journey. AMI 2.0 provides sensing and intelligence foundation, but Data as a Service (DaaS) turns data into operational value. It helps overcome longstanding barriers, accelerate innovation, and deliver enhanced value to customers and stakeholders. 

By adopting scalable DaaS architectures, leveraging edge computing and implementing strong governance and security frameworks, utilities can achieve real-time operational efficiency, regulatory compliance and sustainable growth.

As utilities advance along the data modernization roadmap, WWT is equipped to support every phase from foundational enablement and edge computing pilots to unified data access and AI-driven automation. Our expertise in delivering standardized data products, robust governance frameworks, and scalable analytics models can position utilities for continuous improvement and long-term success.