This article is co-authored by Gerardo Morales and Tony Gonzalez.

The largest U.S. electric utilities alone are planning to invest close to $1.2 trillion over the next several years.

That figure reflects a bottom-up aggregation of publicly announced capital plans across the industry’s largest players, including several investor-owned and public power entities. It does not represent the full universe of utilities, suggesting that total industry investment is likely even higher.

On an annualized basis, this translates to roughly $250 billion per year being deployed across the largest utilities alone. That level of sustained investment has few precedents in the industry. Most of the conversation to date has focused on the scale of that investment. The more important question is whether utilities are prepared to deliver it.

While some utilities are prepared, many are still adapting. 

Across the industry, utilities are running into the same constraints. Supply chains for critical equipment remain tight. Contractor capacity is limited. Internal teams are stretched across an increasing number of large, complex projects. These pressures are not temporary. They are structural, and they are intensifying as more utilities ramp up spending at the same time.

What makes this cycle different is not just the scale of investment, but the level of coordination required to deliver it. Projects are more interconnected, timelines are more compressed, and dependencies across internal teams and external partners are greater than in prior cycles.

Yet many utilities are still operating with execution models designed for a different environment.

Planning, resource allocation, and project delivery are often managed in silos. Visibility into performance is fragmented. Decision-making processes are not always aligned with the scale and complexity of current capital programs. These gaps create risk, not at the approval stage, but during execution.

This is where the real exposure lies.

Regulators and stakeholders are also raising expectations. It is no longer sufficient to justify capital investments at a high level. Utilities are being asked to demonstrate that projects are prioritized effectively, that risks are actively managed, and that outcomes are delivered as expected.

The implication is clear. Success in this investment cycle will not be defined by how much capital is approved or deployed. It will be defined by how effectively utilities can execute.

That requires a shift toward a more structured capital deployment model, one that integrates planning, prioritization, resource management, and execution oversight. Utilities that build this capability will be better positioned to manage constraints, adapt to changing conditions, and deliver results at scale.

Based on work with utilities facing similar challenges, one pattern is clear: execution at this scale does not improve through incremental change. It requires strengthening a few core capabilities.

Execution at this scale requires strengthening a few core capabilities to name a few:

• Capital planning must become more disciplined and coordinated, with clear prioritization, trade-off evaluation, and sequencing aligned to system needs and resource constraints. 

• Centralized oversight is increasingly important, as fragmented execution limits visibility and increases risk, making coordinated project delivery models essential. 

• Resource planning is under pressure, requiring earlier alignment of workforce and contractor strategies to meet growing demand across engineering, procurement, and construction. 

• Procurement and supply chain management are becoming more strategic, with proactive management of long-lead materials and supplier relationships directly impacting timelines. 

• Stronger systems and processes are needed to provide visibility into cost, schedule, and risk and support better decision-making across complex portfolios. 

Taken together, these are not new concepts, but at this scale, they become essential.

The industry is no longer constrained by its willingness to invest. It is constrained by its ability to deliver.

And in this cycle, execution will define the winners. Those that do not focus on a more integrated execution find that the greatest risk is not underinvestment, but underestimating the difficulty of execution.

If you are interested in how these investment trends vary across individual utilities, including their capital plans, large-load exposure, and what it will take to execute at this scale, the full report is available here.

Part I: From Blueprint to Reality – How ScottMadden Helped Develop a Fleetwide Model for Nuclear Generation

By Luke Martin (Partner), Brian Szews (Director), Morgan Schadegg (Director), Alex Tylecote (Manager)
ScottMadden, Inc.

From "Why Modernize?" to "How Do We Transform?"

The U.S. commercial nuclear industry has reached an inflection point. After decades of stagnation, cost pressures, aging technology, and talent attrition, the sector now faces substantial growth opportunities driven by rising power prices, increasing electricity demand, and bipartisan policy support for nuclear generation.

Yet progress remains fragmented across utility fleets. Despite pilot investments in sensors, AI, and advanced maintenance tools, few nuclear utilities have achieved progress at the enterprise level. Individual plants may have seen piecemeal improvements, but utilities struggle to scale these benefits across their fleets. This pattern reveals a fundamental truth: successful transformation requires more than deploying new technologies. It demands rethinking how nuclear utilities operate as a single integrated fleet rather than a collection of independent plants.

Why Transformation Stalls 

Until recently, three interrelated challenges have constrained the nuclear industry. First, plants operate aging analog systems that have grown increasingly expensive to maintain while being unable to leverage modern digital capabilities. Second, high operating costs have historically disadvantaged nuclear plants against other generation sources (although market conditions have recently improved). Third, experienced workers have been retiring faster than the sector has been able to replace them, while competition for skilled trades has intensified across all energy sectors.

Yet the real barriers are much deeper. Nuclear operators favor proven approaches over first-of-a-kind implementations, a conservatism that supports safety and reliability but can sometimes slow innovation. Past experiences with unsuccessful technology deployments reinforce this caution. Additionally, modernization initiatives compete for limited capital against immediate operational needs, with individual plants bearing implementation risks and regulatory uncertainties. This combination of cultural resistance, resource constraints, and structural barriers creates organizational inertia that favors incremental improvements over the comprehensive transformation needed to address fundamental operational challenges.

Integrated Operations in Norwegian Oil and Gas

Even before the recent surge in demand for electricity generation, the U.S. Department of Energy's Light Water Reactor Sustainability Program (LWRS) at the Idaho National Laboratory (INL) recognized the industry's need for comprehensive transformation of the commercial nuclear industry. LWRS partnered with the energy consulting firm, ScottMadden, Inc., to develop the Integrated Operations for Nuclear (ION) framework. ION adapts proven transformation strategies from the Norwegian oil and gas sector, where operators faced remarkably similar challenges in the early 2000s: unsustainable operational costs, aging infrastructure, workforce retirements, and increasingly complex maintenance requirements.

Norwegian operators developed Integrated Operations (IO) as a radical reimagining of offshore platform management. Rather than treating each platform as an isolated asset with dedicated support functions, IO consolidated these capabilities into centralized onshore centers serving multiple platforms simultaneously. This transition required standardizing processes across the fleet, integrating real-time data systems, and fundamentally shifting from platform-centric to fleet-wide thinking. Despite significant challenges, including platform heterogeneity and organizational resistance, the approach delivered impressive results: 20-30% reduction in operations and maintenance costs, significant decreases in offshore staffing requirements, and measurable learning effects that improved with each implementation.

ION: A Pathway for Nuclear Transformation 

The ION framework directly addresses the nuclear industry's transformation barriers. By adapting Norwegian oil and gas success to nuclear realities, ION provides a pathway that has been missing. Critically, ION shifts the transformation from a plant-by-plant challenge to a fleet-wide opportunity. ION enables coordinated approaches where early adopters validate solutions for subsequent sites. Centralized support functions replace duplicated efforts across plants. Standardized processes reduce complexity while respecting site-specific needs. This evolution from plant-centric to fleet-centric operations represents the same fundamental shift that enabled Norwegian operators to transform their cost structure and operational resilience.

The figure above illustrates how ION translates these principles into an integrated operating model for nuclear. The framework aligns four critical domains: core technologies (digital I&C, mobile tools, advanced monitoring), data infrastructure and analytics, workforce capabilities, and governance structures. These elements work together to enable the shift from isolated plant operations to fleet-wide optimization. Technologies provide the foundation, but sustainable transformation only occurs when workforce capabilities and governance evolve in parallel. This integrated approach gives nuclear operators both the vision and practical roadmap to move beyond incremental improvements toward comprehensive modernization.

ScottMadden's Role: Making ION Work for Industry

While ION provided the proven framework nuclear operators needed, implementation required bridging the gap between Norwegian success stories and nuclear regulatory realities, ScottMadden's partnership with INL has been essential in making this translation practical and actionable for U.S. nuclear utilities.

Working directly with INL and utility partners, ScottMadden addressed the industry's risk aversion by developing concrete, field-tested implementations. We demonstrated measurable ROI from digital tools like AI-supported diagnostics and mobile-enabled maintenance, providing the proof points that conservative operators require. Our team navigated regulatory complexities by aligning ION pathways with NRC licensing requirements, cybersecurity mandates, and rate case filings, removing uncertainty from the transformation process.

Most importantly, our team helped utilities overcome the plant-by-plant implementation trap. We developed fleet-wide business case methodologies that capture shared benefits and distributed risks. Our implementation roadmaps show how to sequence deployments across sites, building momentum through early wins while managing resource constraints. By grounding every recommendation in operational realities and regulatory requirements, we give utilities confidence to move beyond incremental changes toward the comprehensive transformation that ION enables.

Stay tuned for part II, where we provide a detailed overview of how we translate ION principles into practical implementation.

The nuclear industry is entering a new era defined by capacity expansion, life extensions, restarts, and the push for advanced reactors.

Realizing this growth depends on a modernized operating model that bridges legacy systems with digital, AI-enabled capabilities. Developed through a multi-year collaboration between ScottMadden and Idaho National Laboratory under DOE’s LWRS program, the Integrated Operations for Nuclear (ION) framework offers a practical, scalable approach to improving performance today while preparing fleets and developers for tomorrow’s buildout.

In this webinar, experts from ScottMadden shared lessons learned from modernization pilots, outlined the ongoing evolution toward ION-AI, and discussed how these principles apply to both the existing nuclear fleet and next-generation SMR and advanced reactor programs. Viewers gained a clear perspective on how integrated operations connect modernization investments, federal incentives, digital readiness, and long-term fleet sustainability.

During the session, attendees learned how to:

• Understand why modernization is foundational to sustaining today’s nuclear fleet and enabling future capacity expansion, including how policy and incentives are reshaping investment decisions

• Identify the highest-value opportunities for integrated operations, based on real-world lessons from ION pilots and work reduction studies with utilities and national labs

• Recognize the capabilities required for digital and AI-enabled operations, including data readiness, governance, and phased maturity planning under the ION-AI framework

• Apply ION principles to SMR and advanced reactor programs by embedding integrated governance, digital systems, and workforce models early in the design and deployment lifecycle

The nuclear industry is entering a new era, defined by capacity expansion, life extensions, restarts, and the push for advanced reactors. But realizing this growth depends on a modernized operating model that can bridge legacy systems with digital, AI-enabled capabilities.

Developed through a multi-year collaboration between ScottMadden and Idaho National Laboratory under DOE’s LWRS program, the Integrated Operations for Nuclear (ION) framework provides a practical, scalable approach to improving performance today while preparing fleets and developers for tomorrow’s buildout.

In this webinar, experts from ScottMadden will share lessons learned from modernization pilots, share the ongoing evolution toward ION-AI, and discuss how these principles apply to both the existing fleet and next-generation SMR and advanced reactor programs. Participants will gain a clear view of how integrated operations link modernization investments, federal incentives, digital readiness, and long-term fleet sustainability.

Learning Objectives

By the end of this session, participants will be able to:

• Understand why modernization is foundational to sustaining today’s nuclear fleet and enabling future capacity expansion, including how policy and incentives are reshaping investment decisions.

• Identify the highest-value opportunities for integrated operations, based on real-world lessons from ION pilots and work reduction studies with utilities and national labs.

• Recognize the capabilities required for digital and AI-enabled operations, including data readiness, governance, and phased maturity planning under the ION-AI framework.

• Apply ION principles to SMR and advanced reactor programs, embedding integrated governance, digital systems, and workforce models early in the design and deployment lifecycle.

Speakers

• Luke Martin, Webinar Lead, Partner – Nuclear Modernization 

• Brian Szews, Director – I&C Modernization and Market Strategy

• Morgan Schadegg, Director – Operations Strategy and Transformation

• Alex Tylecote, Manager – Digital Transformation & AI Readiness

By Luke Martin – Partner and Safety COI Lead, ScottMadden; co-written by Alex Tylecote and Matt Reed

The Problem: Field Safety Is Largely Reactive

For decades, utilities have measured safety performance primarily through lagging indicators, most notably the Total Recordable Incident Rate (TRIR). While TRIR is required for compliance and remains a visible benchmark for executives and regulators, it is a backward-looking measure. It tells us what has already happened but fails to capture the conditions that predict future incidents.

Research from the Construction Safety Research Alliance (CSRA) has revealed the scope of this problem: because serious incidents are statistically rare, TRIR calculations swing widely with even small changes in recordables. A utility with two incidents in one year and three the next might see its TRIR spike by 50%, creating a misleading perception of worsening safety performance. However, with such small numbers of incidents for a single utility, TRIR is often statistically insignificant. Focusing on TRIR for compliance purposes may distract utilities from the fundamental drivers of risk.

This matters. Serious injuries and fatalities (SIFs) often stem from precursors that differ entirely from those behind minor injuries. Lack of planning, missing controls, or overlooked hazards are potentially relevant signals, but they remain largely invisible or ignored. As a result, even as utilities digitize more safety data, serious incidents have not declined proportionally.

Two barriers explain the gap between data collection and improved outcomes:

· Siloed information: Paper-based systems, personal notes, and informal communications prevent a full view of risk. Even where digitization has occurred, much of the most valuable information remains locked away in narrative fields or PDF attachments.

· Analytical limits: Traditional systems can tabulate incident counts or calculate rates, but they cannot process unstructured data or connect disparate signals into a meaningful risk picture.

To truly advance safety, utilities must look beyond compliance metrics and adopt approaches that surface leading indicators before harm occurs.

The Shift: How AI Makes Safety Predictive

Artificial intelligence offers a path forward. Unlike traditional analytics, which require structured datasets, large language models (LLMs) and other AI methods can process the messy, real-world inputs where SIF precursors often hide: handwritten field observations, free-text incident narratives, transcribed toolbox talks, and even voice recordings.

By analyzing this data holistically, AI can:

· Identify high-risk work conditions, such as jobs involving heights, electricity, or confined spaces, especially when proper controls are missing.

· Recognize risk patterns, like frequent overtime combined with hazardous tasks.

· Detect subtle but predictive signals, such as persistent ergonomic discomfort, that may escalate into recordable injuries.

For example, a recent benchmarking study showed that when an employee reported discomfort lasting more than 72 hours, the likelihood of a recordable injury increased to 75%. AI enables safety teams to act on these kinds of signals early, preventing harm rather than responding after the fact.

The shift is profound: LLMs enable utilities to broaden their scope, capturing a more comprehensive picture of field conditions and transforming disparate data into actionable insights. Instead of asking "What went wrong?" utilities can begin asking “Where are we most at risk, and how can we prevent it?”

On the Frontlines: Emerging Tools in Action

Utilities are beginning to pilot LLM tools across safety contexts. While most deployments are still early stage, these examples show the breadth of possibilities:

· Immersive Training & AI Risk Assessment: A leading battery manufacturer piloted immersive, video-based training “dojos” and AI-driven risk scoring tools. These systems highlighted hazards before work began and reinforced safer practices. In early results, participants demonstrated stronger hazard recall and greater confidence in applying controls in the field.

· AI-Enhanced Field Training: Our NXT GEN® Training platform has shown how virtual simulations of high-risk scenarios, combined with AI monitoring, can strengthen safety behaviors. For example, electrical workers practiced lockout/tagout procedures in a virtual environment, while AI can track common errors and flag areas for coaching.

· Visual Analytics at Scale: Transmission and distribution utilities are using AI to process drone footage, field photos, and vehicle camera feeds to identify equipment damage, vegetation encroachment, PPE adherence, or unsafe practices. One utility reported that AI-assisted drone inspections reduced manual review time by 70%, while also identifying potential hazards that were previously missed in traditional walkthroughs.

· Predictive Job Planning: Some utilities are piloting AI systems that score each upcoming job's risk level. Supervisors then decide whether to proceed, pause, or add additional controls. In one

pilot, supervisors received automated prompts when job risk scores exceeded a threshold, helping them reprioritize work schedules to lower exposure.

· Voice-Enabled Safety Assistants: AI-powered assistants allow field crews to query procedures hands-free, improving access to guidance during high-risk work. Imagine a lineworker about to enter a confined space asking, "What are the top three controls I need in place?" and receiving immediate, accurate guidance.

These tools are not intended to replace human judgment. Instead, they extend and augment it by providing frontline crews and managers with richer, real-time insights that enable smarter, safer decisions.

Predictive Safety in Practice: Dashboards and Metrics

Forward-looking utilities are pairing AI with new safety KPIs that emphasize leading indicators. These dashboards provide managers with a dynamic view of risk across crews, sites, and various time horizons.

Lagging Indicators (Traditional)

· TRIR (Total Recordable Incident Rate)

· Lost Time Incident Rate

· Serious Injuries & Fatalities (SIFs)

· OSHA-reportable incidents

· DART (Days Away, Restricted, or Transferred)

Leading Indicators (Predictive)

· Near misses reported

· Ergonomic flags raised

· Safety observations submitted

· Supervisor-led field coaching sessions

· Leadership safety walks

· Job briefs with AI risk alerts

By analyzing both types of data together, utilities can see patterns they would otherwise miss. For example, an uptick in near misses, combined with increased overtime hours, might predict an elevated SIF risk in a particular division. AI-powered dashboards make these connections visible in time to act.

The shift toward leading indicators is also reshaping culture. Instead of waiting for incidents to measure progress, utilities are rewarding proactive behaviors, such as reporting near misses, raising ergonomic concerns, and conducting peer coaching. These actions, amplified by AI insights, are redefining what constitutes "good safety performance.”

The Organizational Challenge: Beyond the Technology

AI's potential in safety is real, but adoption requires more than technology. Utilities must:

· Digitize data sources - Make handwritten notes, paper forms, and fragmented systems accessible for analysis.

· Foster leadership buy-in - Encourage decision-makers to trust and act on AI-generated insights.

· Manage change - Ensure crews see AI as a tool that supports, not replaces, their expertise.

· Balance imperfect data - Recognize that perfect data is not required to begin; rapid prototyping can validate AI concepts even with incomplete information.

Cultural readiness may be the most significant barrier to effective communication. Crews need to trust that AI is not about surveillance, but about protection. Leaders must be willing to act on AI insights, even when they challenge traditional assumptions. Building that trust requires transparency, training, and consistent communication.

Utilities with strong safety cultures and innovative mindsets are already moving forward. Those waiting for flawless digital infrastructure risk falling behind.

A Roadmap for Utilities

Based on industry pilots and lessons learned, utilities can approach AI adoption in three phases:

1. Discover and Prioritize - Identify high-value safety use cases, assess data readiness, and quantify potential impact. For example, start with jobs known to involve high-energy hazards and evaluate how AI might surface early warning signs.

2. Pilot and Learn - Launch small-scale pilots to validate AI's effectiveness in specific contexts, building stakeholder confidence through demonstrated results. Early pilots might focus on a single hazard category, such as ergonomic strain, or a specific operational area, like substation maintenance.

3. Scale and Sustain - Develop enterprise-wide roadmaps, embed AI into processes, and establish governance to ensure responsible, long-term use. Success requires not only technology but also training, change management, and leadership alignment.

This phased approach enables organizations to transition from exploration to impact without overcommitting resources too early. It also creates space to adapt via learning from pilots, refining models, and scaling what works.

The Broader Impact: Why This Matters

The benefits of predictive safety extend beyond injury prevention:

· Operational resilience - By reducing incidents, utilities minimize unplanned outages and disruptions.

· Workforce engagement - Crews see leadership investing in tools that keep them safer, strengthening trust and morale.

· Regulatory alignment - As regulators increasingly emphasize leading indicators, AI-powered safety programs can help utilities stay ahead of compliance trends.

· Reputation and recruitment – Companies with strong safety cultures are more attractive to prospective employees, especially as the industry faces workforce transitions.

What's Next

The shift to predictive safety is happening now. Early adopters are already seeing results, and their successes will soon become industry benchmarks. Utilities adopting AI-enabled safety analytics are setting the standards that others will quickly follow. Those that remain reliant on lagging indicators risk falling behind in both performance and reputation.

Importantly, AI amplifies human expertise. A safety manager who once spent hours reading reports can now receive AI alerts highlighting emerging risks. Supervisors can tailor safety briefings to real-time conditions. Crews can access guidance in the field when they need it most. The combination of human judgment and AI insight makes safety systems stronger, not weaker.

The next step is clear: utilities should experiment, pilot, and share lessons. Together, the industry can define how predictive analytics reshape field safety for the better.

We invite utility leaders to contribute their experiences, share their insights, and join the conversation as we move from reactive to predictive safety.