AI in Energy Statistics: Adoption Across Operations, Sales & Customer Service

of executives say AI will improve employee productivity.

of energy customers are more likely to choose utilities that use digital tools for personalized service.

of energy customers expect more proactive outage and restoration notifications via digital channels.

of utility customers say they would use an AI-enabled app to manage energy usage if it offers real savings.

US utilities reported that 55% of customers have used online portals or apps to manage their energy usage during 2023.

of electricity customers in the U.S. used demand response programs during 2023.

of U.S. residential electricity consumers reported using third-party energy management services in 2023.

of companies that use AI report that they have already achieved measurable business value.

of executives report that they are using AI in at least one business function.

of organizations say they are using AI to optimize supply chain and logistics.

of energy and utilities respondents say they are investing in AI to improve operational performance.

of companies using AI report that data quality is the most important factor for success.

of energy and utilities organizations report they have already scaled AI pilots into production.

of utilities identify data integration and interoperability as a top challenge for AI deployment.

of executives expect AI to reduce operational costs in the next 12 to 24 months.

of organizations report AI is being used to improve forecasting accuracy.

of organizations report AI is being used to reduce asset downtime.

of utilities executives say generative AI is part of their near-term AI roadmap.

of organizations have implemented AI governance frameworks.

of organizations say they have fully deployed AI with monitoring and retraining mechanisms.

of executives say they are using AI to automate manual processes.

Gartner predicts that by 2026, 75% of large enterprises will have deployed AI governance capabilities that are auditable.

of energy and utilities executives say AI will have a high impact on their industry over the next three years.

of energy and utilities organizations say AI deployment is already underway.

of energy and utilities executives cite cybersecurity risk as a key barrier to AI adoption.

of organizations report AI is being used for predictive maintenance.

of utilities executives expect AI will improve demand forecasting and grid operations.

of energy and utilities organizations are prioritizing AI projects related to grid management and reliability.

McKinsey reports that AI can reduce peak energy demand by 1% to 4% through improved forecasting and load optimization.

McKinsey estimates that AI could reduce energy trading losses by 10% to 15% via better predictions and anomaly detection.

of energy companies say they plan to increase budgets for AI-related initiatives in 2025.

of energy and utilities organizations expect AI spending to grow faster than their overall IT budget.

McKinsey estimates that generative AI could add $2.6 trillion to $4.4 trillion annually across the global economy by 2040.

is the projected annual value-at-stake for generative AI in the U.S. oil and gas sector by 2030 (model year).

IDC forecasts that worldwide spending on AI systems will reach $xxx.x billion in 2027, up from $xxx.x billion in 2024.

IDC projects that worldwide spending on AI will grow at a CAGR of about 20% through 2027.

2024 spend on AI software and services in the power and utilities sector is projected to reach $xxx million (per publisher estimate).

of executives believe AI will be central to customer experience improvements.

of utilities expect generative AI to help enhance customer engagement and service delivery.

of marketing leaders say generative AI will be included in their marketing technology stack within 12 months.

of marketers report they are already using generative AI for content creation.

of respondents say generative AI has replaced at least one content role in their organization.