Moody’s Warns Firms of Risks from Slow AI Adoption

Moody’s has issued a stark warning regarding the potential consequences of slow artificial intelligence (AI) adoption, indicating that companies lagging in this area could experience significant challenges, including structural margin erosion and loss of market share. In a report featuring insights from Charleyne Biondi, an Assistant Vice President and analyst at Moody’s Ratings, the firm emphasized that AI integration is increasingly becoming a critical factor in assessing creditworthiness, shifting the focus from a purely technological race to a matter of financial viability.

The report outlines two scenarios—conservative and optimistic—highlighting how the pace of AI adoption influences firms across various sectors. Companies that embrace AI early may benefit from structural efficiency improvements, while those that hesitate risk falling behind, particularly in industries where new AI-native competitors can emerge rapidly.

Understanding the Scenarios: Conservative vs. Optimistic

Moody’s developed two distinct scenarios to model the impact of AI on different sectors. The conservative scenario suggests a gradual integration of AI, leading to improved efficiency without fundamentally altering competitive dynamics. In contrast, the optimistic scenario predicts rapid advancements in AI capabilities, resulting in swift credit effects and heightened risk of competitive displacement for firms slow to adapt.

Biondi explained, “The main difference lies in AI capabilities, how quickly models and agents can scale to handle complex tasks. In the conservative scenario, capability gains plateau earlier, limiting productivity to incremental efficiency. In the optimistic scenario, capabilities compound faster, enabling broader workflow substitution and new revenue models.”

Sectoral Winners and Losers in AI Adoption

Certain sectors are poised to reap substantial benefits from AI deployment. According to Moody’s analysis, industries such as finance, healthcare, insurance, and logistics are likely to see significant gains due to their reliance on data and standardized processes. These sectors can automate repetitive tasks with AI, effectively reducing costs and enhancing efficiency.

For example, in finance, AI-driven fraud detection systems have successfully reduced false positives by over 50%, leading to lower compliance costs and improved loss ratios. Conversely, sectors like utilities, oil and gas, pharmaceuticals, and heavy manufacturing face challenges due to longstanding structural barriers, hindering rapid AI-driven transformation. Biondi noted that while AI could enhance planning and supply chain efficiency in these industries, it will not swiftly revolutionize core production processes.

Moody’s also identified disruption risk as a critical factor, defining it as the probability and severity of revenue displacement and margin compression as AI reshapes industry economics. Biondi stated, “In our Heatmap, the ‘lightning’ sign indicating disruption in certain sectors means that at least 10% of issuers in a given sector will face significant pressure from AI.”

Regional Disparities in AI Gains

The report further highlights that the benefits of AI adoption will not be evenly distributed worldwide. Regional differences in innovation ecosystems, energy costs, regulatory environments, and access to computing power will lead to varying credit outcomes. Biondi pointed out that jurisdictions mastering significant parts of the AI value chain—from chips to data—are best positioned to capitalize on long-term gains.

The United States currently leads in this regard, with a robust tech ecosystem that combines computing power, model leadership, capital markets, and scalability. Meanwhile, the European Union and the United Kingdom, though home to strong incumbents, face higher operational costs and tighter budgets. China has considerable size and policy support but is constrained by limited access to advanced chips. Gulf states are making significant investments and rapidly scaling their AI capabilities but remain dependent on foreign technology providers, which brings associated risks.

Boards and Investors Underestimating AI Risks

Despite the increasing awareness of AI’s importance, Moody’s cautions that many corporate boards and investors still underestimate the financial implications of slow AI adoption. “Awareness is still uneven. Many focus on compliance or reputational risks regarding AI but often overlook the opportunity cost of inaction,” Biondi stated.

An additional risk lies in the growing transfer of value to AI infrastructure providers. If autonomous AI systems evolve to automate entire workflows, this trend may concentrate bargaining power and credit exposure among a few infrastructure players, diminishing the share of value retained by companies implementing these systems.

Moody’s underscores the urgency of AI adoption as a material factor influencing long-term competitiveness and credit profiles. Firms that hesitate risk becoming obsolete in a rapidly evolving landscape where value is increasingly captured by those who develop, own, and scale AI infrastructure. As the industry approaches 2030, the margin for delay is shrinking; the pivotal question is no longer whether AI will transform industry economics, but how quickly it will happen and which firms will lead the charge.