2025年人工智能基础设施状况报告

Table of contents Key findings 12 Section 1: The AI roadmap Section 2: Leadership influence 16 20 Section 3: The AI skills gap Section 4: Capacity challenges 23 28 Section 5: Networking and security concerns Section 6: Sustainability pressure INTRODUCTION Companies see the use of AI as essential to staying competitive, but have theybuilt the right systems and processes to manage the demands that come with it? AI is no longer a tentative or temporary experiment for most organizations. It hasbecome a fundamental part of business operations, shaping strategy, decision-making,and innovation. But while AI's presence is expanding, so are its complexities. For our second annual State of AI Infrastructure Report,we surveyed over 350 IT leadersat companieswith more than $100 million in annual revenue—including 100 respondents from organizations exceeding$2 billion—to understand how businesses are implementing AI and how it's affecting their IT infrastructure. What's clear is that companies are increasingly investing in AI technologies and expect to see measurablereturns in short order.Nine in 10 companies (90%) are deploying or planning to deploy generative AI, andmore thanhalf of respondents are using it for predictive analytics, cybersecurity, autonomous systems,computer vision, or natural language processing (NLP)-based applications [Fig. 1]. FIG. 1 What types of AI/ML use cases are you deploying or planning to deploy? FIG. 3 Which of the following best describes your attitudetoward the implementation of AI applications andinitiatives in your organization? Only 5% of organizations describe their AI adoption as nascent (down from10% a year ago), andoptimism about AI's use remains high—three-quarters(75%) of IT leaders express excitement about AI's role in their organizations[Fig. 2 and 3].However, the number of respondents feeling overwhelmed by AI'simplementation has more than doubled since last year, from 12% to 29% [Fig. 3]. FIG. 2 Which of the following best describes the state ofartificial intelligence (AI) at your organization? Overwhelmed In addition, planning ahead has become essential. Most organizations(62%) aremapping out their IT infrastructure and data center capacityneeds one to three years in advance, with another 17% looking threeto five years ahead. Despite the tight timelines and rising demands,94% of respondentsexpressed confidence in their planning process.Even among those with less than a one-year horizon, a surprising 70%saidthey feel well prepared to meet future infrastructure requirementsthough vacancy rates are at a record-low. Five biggest takeaways While organizations are bullish on AI andincreasing their supporting investments, they also: Clearly, while companies see AI's value, they are alsograpplingwith its demands—that show no sign of slowing—and will need toplan accordingly. Expect rapid financial returnson AI spending1 Struggle with infrastructure constraintsthat hinder expansion2 Face growing skills shortages in AIimplementation3 Rely on inadequate data centerplanning cycles4 Encounter network performanceand security issues that limit scalability5 Eight key findings of respondents said theC-suite isthe driving force behind theirorganization’s decisionto adoptAI-driven applications. At anincreaseof 28 percentage points, there isconsiderably more buy-in than a year ago. Confidence in organizations'ability to execute theirAI roadmapshas grownsignificantly,rising from 53%to 71%in one year. of respondents saidITinfrastructure constraintsare the greatest barrierto expanding theirorganization’s AI initiatives. of respondents reporteddevoting at least10% of theirorganization’s total IT budget toAI initiatives, including software,hardware, and networking. of respondents reportedplanningtheir IT infrastructure and datacenter capacity needsone tothree years in advance in responsetoincreased demandandlimitedimmediate availability. 61% of respondents haveencountered skills or staffinggapsin the managementofspecialized computinginfrastructure, upfrom 53% a year ago. of respondents said theirorganization’s AI governance policiesdon’t cover security protocols forAI systems and data, and nearlyhalf (48%) reported gaps in policiesaddressing bias detection andmitigation in AI models. of respondents areworried about acquiringor developing thespecialized talentneeded to meet AI goals. SECTION 1: THE AI ROADMAP C-suite leadership drives investment as AI becomes a core business strategy Still, senior executiveshesitate to commit to bold strategies without a proven returnoninvestment,industry validation, andrisk mitigation. High-profile AI implementationfailures, like infrastructure bottlenecks and latency issues, have made them wary,as have rogue behaviors and AI hallucinations. Meanwhile, issues like model bias,missteps in decision-making, and regulatory risksdemand strong oversight. However,as AI's business value becomes clearer, leadership is taking a mor