智慧能源：通过AI驱动转型创造价值的蓝图

A blueprint for creating value throughAI-driven transformation KPMG. Make the Difference. KPMG International Foreword Agentic AI offers a breakthrough. Thesesystems canautonomously manage entire workflows, complementingthe nuanced judgment of human experts and makingcomplex decisions without direct oversight, providingrecourse to a human expert if and when required. The levelof impact seems dramatic: One company, I heard presentat COP29, shared that by deploying AI agents, theyreduced a 21-day process to just 18 minutes. The pace of technological advancement isnothing short of extraordinary. If this report hadbeen written six months ago, its conclusionsmight already feel out of date. Six months fromnow, they may evolve again. That’s the realitywe now operate in — a world where innovationis not only constant but accelerating and wheretechnologies once thought of as futuristic, suchas quantum and agentic AI, are rapidly movinginto the strategic planning horizon of theenergy sector. For AI to truly scale and deliver value, energycompanies must rethink not just theirtechnology, but their entire operating model.Those that can align AI with business strategy,integrate data and technology and createa workforce ready to embrace AI-powereddecision-making will likely be the ones that leadin the next era of energy transformation. For energy companies, the cost of inaction is risingfast — those who delay risk being locked into outdatedinfrastructures, talent models, and operating assumptionsthat may be unfit for purpose by the end of the decade. In the near term, the industry leaders we speak withpoint to agentic AI as a transformative force. Althoughtraditional automation has delivered incrementalbenefits, its progress is increasingly constrained bythe need for expert human intervention — expertisethat is both scarce and diminishing. Scaling AI is about reimagining the enterprise and meetingthe energy trilemma head on, embedding intelligenceacross the value chain to secure supply, decarbonize andcontrol costs. This report provides guidance for navigatingthat future. Anish De— Global Head of EnergyKPMG International Contents 14 Building theintelligent energy company 18 02Foreword The first phase: Enabling AI to people 25 04At a glance The second phase: Embedding AI in the flow of work The third phase: Evolving your energy ecosystem 36Conclusion At a glanceAt a glanceAt a glance The industry is preparing for anAI future63% The duality of energycreation andenvironmental impact is a key consideration63% Energy companies are beginning toscale their AI pilots56% 64% 71% have invested in an automated datafabric or hybrid cloud, cross platform,data integration have been piloting AI but only 13 percentoperate an AI center of excellence struggle to balance AI use withsustainability goals operate an enterprise-wide cloud orhybrid-cloud IT infrastructure view sustainability as a moreimportant strategic goal than AI There are early successeshave seenefficiencyimprovements79% ROIs ofgreater than10 percent60% Experimentation for breakthroughs is a criticalinvestment area There are significant challengesto scaling applications 92%96% 58%38% have data issues with inconsistentformats impacting data quality believe that organizations that embraceAI will develop a competitive edge overthose that do not There is a twin focus on efficiency and growth65%74%EfficiencyRevenuegrowth are investing in future-focusedprojects without the expectation ofimmediate returns face ethics andregulatory issues Introduction For leaders in the energy industry, standingstill is nolonger an option. Customers, regulators and partners alikeexpect up-to-date, intelligent systems capable of deliveringaffordable, reliable and sustainable energy. The businessesof today will not look the same by 2030 — and the journeyfrom here to there requires flexibility, foresight and thecourage to act in uncertain times. AI in energy is about more than just adoptingnew technologies — it’s about transforminghow energy is generated, distributed, andintelligently managed to maximize efficiency,minimize waste, and respond dynamically toreal-time demand and system conditions. This report explores: •How to define AI-driven value creation in energy —Understanding how AI can enhance operational efficiency,improve grid stability, support sustainability goals and drivecommercial success. •How AI can address challenges around regulatorycompliance, cybersecurity and cross-functional integration. To understand how the sector is preparing, KPMGinterviewed and surveyed AI leaders across the energyindustry, including 163 senior executives from mid-tolarge-sized energy companies across eight countries(Australia, Canada, China, France, Germany, Japan, theUnited Kingdom and the United States). What emerged isa picture of the current state of AI adoption in the energysector; insights into how organizations are approaching AIstrategy, investment and i