The AI Opportunity in Automotive

February2025 一级市场创投专题报告” 进群导读 每个工作日分享最新30篇一二级市场创业、 投 资 、 融 资 、 行 业 分 析 、 商业 咨 询类报告，10950篇/年。适合进本群的 朋 友 从 事 的 行 业 是 ： 创 投基 金 、 产业 资 本 、 政 府 招 商 、 母 基金 、 精 品 投 行FA、 券 商 、 律 所 、 会计 师 事 务 所 、 咨 询 机 构 等 等 ， 大 家多 多 交 流合作。 扫一扫二维码 投资机构GP、CVC可添加右侧FA微信，获取股权融资项目 备注：投资机构获取项目BP A few key points This presentation has been developed in collaboration between the Strategy& team, PwC’s global strategy house, alongside ourPwCindustry and function experts. Together, we transform organizations by developing actionable strategies that deliver sustainableoutcomes. © 2025 PwC. All rights reserved. PwC refers to the PwC network and/or one or more of its member firms, each of which is a separate legalentity. Please see www.pwc.com/structure for further details. Strategy&The AI opportunity in Automotive AI allows auto players to strengthen top-andbottom line in turbulent times–if taken seriously Our hypotheses on AI in Automotive AI is coming inwavesand its impact is not as anticipatedAI capabilities are evolving from generative to agentic AI, yet realizing bottom-line impact is taking longer than optimists hadhoped1 AI will boostkeytransformation areasof the automotive and mobility sectorValue will be particularlycreatedin technology-driven fields of innovation such as software-defined, autonomous and electric vehicles2 AI use cases emerge across the value chain, but with different time horizonsHighest short-term impact is seen in customer assistance/experience, software development andselected corporatefunctions3 AI brings significant bottom-line opportunities, ifeffectivelycoordinated across the companyOur analysis suggests that a holistic AI transformation strategy can realize a potential margin uplift of 40-60% AI unleashes its potential at scale in partnerships that go beyond the traditional“build approach”Winners start with foundationalAI work, focus promptly on major cost/revenue categories, and scale efficiently with a partner ecosystem5 Strategy&The AI opportunity in Automotive Abbreviation: AI = Artificial IntelligenceSource: Strategy& analysis AI is moving from hype to reality, though the urgency to act remains high Evolution of expected AI impact RealisticAI evolutionscenarios requiring immediate actionbyCEOs •Fast developmenttoward agenticand physical AI•Wide AI adoptionfor products,business models and processes•Reshaping entire industriesincombinationwithothertechnologies AI strategy required for riskhedging and business continuity–with rapid acceleration of AI effortsto exploit window of opportunity •Regulation or cost hinderfurtherAIadvancements•Use cases scalingupinselectedhigh-valueareas•Overallimpact lags behindoverhypedexpectations AI strategy asaccelerator forefficiency gains–with upside potential to securedifferentiation and new value pools In Automotive, AI will boost all technology-driven innovation areas AI impact and company examples in automotive transformation areas AI use cases have value potential across the automotive value chain AI use case examples for the automotive industry Overall and support functions (e.g. strategy, planning, M&A, IT, finance, HR) Our analysis suggests potential40-60% margin uplift due to AI Estimation of AI impact across the automotive value chain(indexed operating margin in %) Tailored AI governance is key to effective scale-up across the company Data and AI governance options with zoom-in on the “Hub and spoke” model To succeed from start to scale, a holistic view on AI and data is crucialStrategy&proven data and AI framework Recalibrate existing data and AI activities to stay aheadRefine data strategyconsidering(Gen)AI, adjust use case target portfolio,andidentify implications foroverall digital/ITtransformation program Trusted AI is key to addressing ethicaland regulatory challengesEstablish and monitor comprehensive trust framework along AI use caseplanning, data, model, validation and deployment AI activities require collaboration with external partnersData/AI experts are in short supply and algorithms are complex–workwith partners for speed and efficiency,yet without creating dependencies Every use case may require a different AI setupAI is not one software suite, but a range of tools/vendors possessdifferent strengths–the entire AI player landscape should be utilized Culture is crucial in implementing AI successfullyAI is usually described in technical terms–but creating a culture thatencourages employees to learn and experiment with AI tools is vital Front-runners move quickly from AI foundation to the big-ticket items Data and AI development stages from start to scale Accelerate your AI journey now–contact our AI experts in Automotive JonasSeyfferthDirectorAI/technology-driveninnovation in mobility Assess your AI maturity withinitial recommendationsin a free online test CONTACTjonas.seyfferth@pwc.com Florian Stürmer JörgKrings Get inspired by our industry-specific AI use case library1)in an initial conversation2 Partn