人工智能法律年度回顧：2025年重大法律案件及其對2026年的意義

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We can confidently say that artificial intelligence law stopped being “emerging” in 2025. This was the year the courts, regulators, and legislators around the world started drawing real lines in the sand on copyright, data use, AI-washing, and high-risk systems—with obligations that will fully bite in 2026 and beyond. For in-house teams, founders, and boards, this year was less about theoretical risk and more about the following issues: what, exactly, is now illegal, what must we document, and how do we keep launching AI products without stepping on a legal landmine?
我們可以自信地說，人工智能法在2025年不再是“新興”領(lǐng)域。這一年，世界各地的法院、監(jiān)管機構(gòu)和立法者開始在版權(quán)、數(shù)據(jù)使用、人工智能洗白和高風(fēng)險系統(tǒng)等方面劃定明確界限，相關(guān)義務(wù)將在2026年及以后全面生效。對于內(nèi)部團隊、創(chuàng)始人及董事會而言，今年的重點較少涉及理論風(fēng)險，更多在于以下問題：確切地說，現(xiàn)在哪些行為是非法的，我們必須記錄哪些內(nèi)容，以及如何在不觸碰法律雷區(qū)的情況下繼續(xù)推出人工智能產(chǎn)品？  Copyright & IP: The “Fair Use Triangle” Takes Shape
版權(quán)與知識產(chǎn)權(quán)：“合理使用三角”的形成
This year gave us the first real cluster of U.S. decisions on whether using copyrighted works to train AI is fair use. The answer so far: it depends heavily on how you got the data and what you do with it.
今年，我們首次看到美國就使用受版權(quán)保護的作品訓(xùn)練人工智能是否屬于合理使用做出了一系列真正意義上的判決。到目前為止，答案是：這在很大程度上取決于你如何獲取數(shù)據(jù)以及用這些數(shù)據(jù)做什么。
 
Thomson Reuters v. ROSS (D. Del.) – “Headnotes are not a free training set”
湯姆森路透訴ROSS案（特拉華州地區(qū)法院）——“標(biāo)題注釋并非免費訓(xùn)練集”
 
In February 2025, a Delaware federal court issued one of the first major training-data decisions in Thomson Reuters Enterprise Centre GmbH v. ROSS Intelligence Inc. Thomson Reuters, owner of Westlaw, accused ROSS of using Westlaw headnotes to train a competing AI-driven legal research tool. The court rejected ROSS’s fair-use defense at summary judgment and found infringement, emphasizing the commercial, competitive use and the creative value of the curated headnotes.
2025年2月，特拉華州聯(lián)邦法院在《湯姆森路透企業(yè)中心有限公司訴ROSS智能公司》一案中作出了首批重大訓(xùn)練數(shù)據(jù)判決之一。Westlaw的所有者湯姆森路透指控ROSS使用Westlaw的標(biāo)題注釋來訓(xùn)練一款具有競爭力的人工智能法律研究工具。法院在即決判決中駁回了ROSS的合理使用抗辯，認(rèn)定其構(gòu)成侵權(quán)，并強調(diào)了這種精心編輯的標(biāo)題注釋的商業(yè)性、競爭性用途及創(chuàng)作價值。
 
Takeaway: Scraping proprietary, value-added content from a competitor to build a directly competing AI product is a high-risk strategy.
要點：從競爭對手那里抓取專有、增值內(nèi)容來構(gòu)建直接競爭的人工智能產(chǎn)品，是一種高風(fēng)險策略。
 
Bartz v. Anthropic (N.D. Cal.) – Lawful copies vs. pirated “central library”
巴茨訴Anthropic案（加利福尼亞州北區(qū)）——合法復(fù)制與盜版“中央圖書館”的對決
 
In June 2025, Judge William Alsup issued a pivotal summary-judgment ruling in Bartz v. Anthropic:
2025年6月，威廉·阿爾蘇普法官在巴茨訴Anthropic案中作出了一項關(guān)鍵的即決判決：
 
Training on lawfully acquired books was “quintessentially transformative” and fair use.
使用合法獲取的書籍進行訓(xùn)練具有“典型的轉(zhuǎn)化性”，屬于合理使用。
But creating and retaining a “central library” of pirated books raised serious infringement concerns, and fair use was denied for those works.
但創(chuàng)建并保留一個“盜版書籍中央圖書館”引發(fā)了嚴(yán)重的侵權(quán)問題，這些作品也不適用合理使用原則。
The case later settled on the eve of trial in September 2025 for a reported $1.5 billion, underscoring the stakes of training-data decisions. So, the courts are increasingly drawing a line between lawfully acquired corpora (more defensible) and pirated or unauthorized data.
該案后來在2025年9月庭審前夕以據(jù)報道15億美元的金額達(dá)成和解，這凸顯了訓(xùn)練數(shù)據(jù)決策的風(fēng)險。因此，法院正日益在合法獲取的語料庫（更具可辯護性）與盜版或未經(jīng)授權(quán)的數(shù)據(jù)之間劃清界限。
 
Kadrey v. Meta & other N.D. Cal. cases – More nuance on fair use
卡德里訴Meta及其他北加利福尼亞地區(qū)法院案件——關(guān)于合理使用的更多細(xì)微差別
 
Companion cases out of the Northern District of California (including Kadrey v. Meta) produced additional rulings that, on their face, are more favorable to AI developers, finding fair use in some training scenarios involving lawfully sourced content.
加利福尼亞州北區(qū)的關(guān)聯(lián)案件（包括Kadrey訴Meta案）產(chǎn)生了其他裁決，這些裁決表面上對人工智能開發(fā)者更有利，認(rèn)定在某些涉及合法來源內(nèi)容的訓(xùn)練場景中存在合理使用。
 
Collectively, practitioners talk about a “fair use triangle”:
從業(yè)者們共同討論著一個“合理使用三角”：
 
Delaware (Thomson Reuters) – highly skeptical when AI is trained on proprietary, curated content to build a direct competitor.
特拉華州（湯森路透）—— 當(dāng)人工智能通過專有、精心策劃的內(nèi)容進行訓(xùn)練以打造直接競爭對手時，人們對此持高度懷疑態(tài)度。
N.D. Cal. (Anthropic / Meta) – more open to fair use where content is lawfully acquired and the AI model is considered transformative, but not when developers hoard pirated content.
美國加利福尼亞北區(qū)聯(lián)邦地區(qū)法院（Anthropic/元宇宙公司案）——對于合法獲取內(nèi)容且人工智能模型具有變革性的情況，更傾向于認(rèn)定為合理使用，但對于開發(fā)者囤積盜版內(nèi)容的情況則不適用。
Media & music: NYT v. OpenAI, Disney/Universal v. Midjourney, and Suno/Udio
媒體與音樂：《紐約時報》訴OpenAI、迪士尼/環(huán)球訴Midjourney以及Suno/Udio
 
Meanwhile, The New York Times v. OpenAI / Microsoft continued as one of the most closely watched AI cases. In 2025, the court issued a sweeping preservation order requiring OpenAI to retain and segregate ChatGPT and API output logs, then later allowed OpenAI to resume normal deletion after the order expired in September. In November, Magistrate Judge Ona Wang ordered OpenAI to produce some 20 million ChatGPT logs, a stark reminder that product logs can become discoverable evidence in AI litigation.
與此同時，《紐約時報》訴OpenAI/微軟案仍是最受關(guān)注的人工智能案件之一。2025年，法院發(fā)布了一項全面的保全令，要求OpenAI保留并隔離ChatGPT和API的輸出日志，隨后在該命令于9月到期后，允許OpenAI恢復(fù)正常的刪除操作。11月，地方法官奧娜·王下令OpenAI提供約2000萬條ChatGPT日志，這鮮明地提醒我們，產(chǎn)品日志可能會成為人工智能訴訟中可被發(fā)現(xiàn)的證據(jù)。
 
In the media space, Disney and Universal sued Midjourney this year for alleged copyright infringement related to image training, marking the first major visual-media plaintiffs in the AI space.
在媒體領(lǐng)域，迪士尼和環(huán)球影業(yè)今年起訴了Midjourney，指控其在圖像訓(xùn)練方面存在版權(quán)侵權(quán)行為，這是人工智能領(lǐng)域首次出現(xiàn)主要的視覺媒體原告。
 
Music labels likewise intensified litigation against AI music generators like Suno and Udio; by late 2025, Warner Music had settled and pivoted into a licensing partnership with Suno, allowing licensed AI models and artist opt-ins. This signals a likely future: litigation leading to structured licensing deals instead of pure prohibition.
唱片公司同樣加大了對Suno和Udio等人工智能音樂生成器的訴訟力度；到2025年底，華納音樂已達(dá)成和解，并轉(zhuǎn)而與Suno建立了授權(quán)合作關(guān)系，允許獲得授權(quán)的人工智能模型以及藝術(shù)家自主選擇參與。這預(yù)示著一種可能的未來：訴訟將促成結(jié)構(gòu)化的授權(quán)協(xié)議，而非單純的禁令。
 
Emerging frontiers: Trade secrets, trademarks, and data promises
新興前沿：商業(yè)秘密、商標(biāo)和數(shù)據(jù)前景
 
This year, we also saw new angles:
今年，我們還看到了新的角度：
 
A proposed class action against Figma alleges the company used customers’ design files to train AI without consent, focusing on misappropriation of confidential information and broken data promises rather than pure copyright.
一項針對Figma的擬議集體訴訟指控該公司未經(jīng)同意使用客戶的設(shè)計文件來訓(xùn)練人工智能，訴訟焦點在于對機密信息的侵占以及數(shù)據(jù)承諾的違背，而非單純的版權(quán)問題。
OverDrive v. OpenAI accuses OpenAI of trademark infringement for naming its video model “Sora” in a way that allegedly conflicts with OverDrive’s existing “Sora” library app.
OverDrive訴OpenAI指控OpenAI將其視頻模型命名為“Sora”，涉嫌侵犯商標(biāo)權(quán)，稱這與OverDrive現(xiàn)有的“Sora”圖書館應(yīng)用存在沖突。
Strategic IP lesson for 2026: Build a documented data-provenance strategy. Track what data is used, how it was obtained, and under what license; wall off dubious sources (pirated sites, competitor headnotes, confidential customer content) and revisit your public promises about “never” using certain data for training.
2026年的戰(zhàn)略性知識產(chǎn)權(quán)教訓(xùn)：制定一套有記錄的數(shù)據(jù)來源策略。追蹤使用了哪些數(shù)據(jù)、數(shù)據(jù)是如何獲取的以及依據(jù)何種許可；隔離可疑來源（盜版網(wǎng)站、競爭對手的批注、客戶的機密內(nèi)容），并重新審視你關(guān)于“絕不”使用某些數(shù)據(jù)進行訓(xùn)練的公開承諾。
 
Enforcement: FTC’s “AI-Washing” Crackdown and Agentic AI Claims
執(zhí)法：聯(lián)邦貿(mào)易委員會對“人工智能洗白”的打擊及智能體人工智能宣稱
On the enforcement front, the Federal Trade Commission (FTC) made clear that there is no AI exemption from existing consumer-protection laws.
在執(zhí)法方面，聯(lián)邦貿(mào)易委員會（FTC）明確表示，現(xiàn)有的消費者保護法不適用于人工智能豁免。
 
Operation AI Comply and “AI-washing”
AI合規(guī)行動與“人工智能洗白”
 
Building on a 2024 announcement that “using AI tools to trick, mislead, or defraud people is illegal,” the FTC has now brought at least a dozen “AI-washing” cases, targeting companies that overstate what their AI does or mislead consumers about AI-powered earnings and performance claims. In August 2025, the FTC sued Air AI, alleging deceptive claims that its agentic AI could fully replace human sales reps and deliver unrealistic business results, while also raising concerns about exaggerated “AI-powered” marketing around a business opportunity scheme.
美國聯(lián)邦貿(mào)易委員會（FTC）在2024年宣布“使用人工智能工具欺騙、誤導(dǎo)或欺詐他人是非法的”，在此基礎(chǔ)上，該機構(gòu)目前已提起至少12起“人工智能洗白”案件，目標(biāo)直指那些夸大其人工智能功能，或在人工智能驅(qū)動的收益和性能宣稱方面誤導(dǎo)消費者的公司。2025年8月，聯(lián)邦貿(mào)易委員會起訴了Air AI，指控其進行虛假宣傳，稱其智能體人工智能可完全取代人類銷售代表并帶來不切實際的商業(yè)成果，同時還對圍繞一項商業(yè)機會計劃進行的夸大“人工智能驅(qū)動”營銷表示擔(dān)憂。
 
Key themes: 核心主題：
 
Claiming “full automation” or “no humans needed” without proof is risky.
在沒有證據(jù)的情況下宣稱“完全自動化”或“無需人工”是有風(fēng)險的。
Exaggerated ROI/earnings tied to “AI” are classic unsubstantiated claims.
與“人工智能”相關(guān)的夸大投資回報率/收益是典型的未經(jīng)證實的說法。
Labeling something as “AI-powered” when it’s not meaningfully different from a standard SaaS tool can be deceptive.
當(dāng)某樣?xùn)|西與標(biāo)準(zhǔn)的SaaS工具并無顯著差異時，卻將其標(biāo)榜為“人工智能驅(qū)動”，這可能具有欺騙性。
Strategic enforcement lesson for 2026:
2026年的戰(zhàn)略執(zhí)行教訓(xùn)：
 
Run all AI product and marketing copy through a truth-in-advertising filter:
通過廣告真實性過濾器審核所有人工智能產(chǎn)品和營銷文案：
 
Can we prove this claim with competent evidence?
我們能用充分的證據(jù)證明這一說法嗎？
Are we implying capabilities (e.g., “human-level,” “guaranteed replacement of employees”) we can’t substantiate?
我們是否在暗示一些我們無法證實的能力（例如，“人類水平”、“保證取代員工”）？
Are we clear about limitations, guardrails, and human oversight?
我們是否清楚其局限性、防護措施和人工監(jiān)督？
New Statutes & Regulatory Frameworks: EU AI Act, Colorado, and State Patchwork
新法規(guī)與監(jiān)管框架：歐盟人工智能法案、科羅拉多州及各州拼湊式監(jiān)管
EU AI Act: Obligations start phasing in
歐盟人工智能法案：義務(wù)開始逐步實施
 
The EU Artificial Intelligence Act formally entered into force on August 1, 2024, but 2025 is when the first obligations started to bite.
《歐盟人工智能法案》于2024年8月1日正式生效，但從2025年起，首批義務(wù)開始生效。
 
Key 2025–2026 milestones: 2025-2026年的關(guān)鍵里程碑：
 
Feb 2, 2025 – Ban on “unacceptable-risk” AI systems (e.g., social scoring, certain manipulative systems) and AI literacy obligations.
2025年2月2日——禁止“具有不可接受風(fēng)險”的人工智能系統(tǒng)（例如社會評分、某些操縱性系統(tǒng)），并規(guī)定人工智能素養(yǎng)義務(wù)。
Aug 2, 2025 – Governance rules and obligations for general-purpose AI (GPAI) providers take effect, including documentation, transparency and some risk-management obligations.
2025年8月2日——通用人工智能（GPAI）提供商的治理規(guī)則和義務(wù)生效，包括文件記錄、透明度以及一些風(fēng)險管理義務(wù)。
Aug 2, 2026–27 – The full high-risk framework for AI embedded into regulated products, sectoral compliance, and national AI sandboxes come online.
2026年8月2日至27日——適用于嵌入受監(jiān)管產(chǎn)品、行業(yè)合規(guī)以及國家人工智能沙盒的完整高風(fēng)險人工智能框架投入使用。
If you build or deploy AI in the EU (or serve EU users), 2025 was the year to start classifying use cases and mapping them to future obligations.
如果你在歐盟構(gòu)建或部署人工智能（或為歐盟用戶提供服務(wù)），那么2025年就是開始對用例進行分類并將其與未來義務(wù)相對應(yīng)的一年。
 
Colorado AI Act: The first comprehensive U.S. AI statute
科羅拉多州人工智能法案：美國首部全面的人工智能法規(guī)
 
Colorado’s SB 24-205 (Colorado Artificial Intelligence Act / CAIA), signed in 2024, has been under intense scrutiny in 2025 but remains on track to take effect February 1, 2026.
科羅拉多州的《SB 24-205法案》（《科羅拉多州人工智能法案》/ CAIA）于2024年簽署，2025年受到了嚴(yán)格審查，但仍計劃于2026年2月1日生效。
 
Key features: 主要特點：
 
Risk-based approach similar to the EU AI Act.
基于風(fēng)險的方法，類似于《歐盟人工智能法案》。
Focus on preventing algorithmic discrimination by “high-risk” AI systems. (NAAG)
重點關(guān)注防止“高風(fēng)險”人工智能系統(tǒng)的算法歧視。（美國總檢察長協(xié)會）
Obligations for both developers and deployers, including risk assessments, notice to consumers, and documentation.
開發(fā)者和部署者雙方的義務(wù)，包括風(fēng)險評估、向消費者發(fā)出通知以及提供文檔。
This is the first broad, state-level AI framework in the U.S.—and it’s influencing drafts in other states.
這是美國首個廣泛的州級人工智能框架，并且正在影響其他州的草案。
 
California & other states: Deepfakes, elections, and transparency
加利福尼亞州及其他州：深度偽造、選舉與透明度
 
California and other states continued to enact narrower, issue-specific AI laws, often around election integrity and deepfakes:
加利福尼亞州和其他州繼續(xù)頒布范圍更窄、針對特定問題的人工智能法律，這些法律往往圍繞選舉誠信和深度偽造展開：
 
California has laws requiring disclosures on AI-generated political ads and manipulated media used in campaign communications.
加利福尼亞州有法律要求披露人工智能生成的政治廣告以及競選宣傳中使用的被篡改媒體。
Additional bills (like AB 2839 and AB 2655) target election-related deepfake disinformation and require platforms to block or label deceptive AI-generated political content during sensitive pre-election periods.
其他法案（如AB 2839和AB 2655）針對與選舉相關(guān)的深度偽造虛假信息，并要求平臺在敏感的選舉前時期屏蔽或標(biāo)記具有欺騙性的人工智能生成的政治內(nèi)容。
California also advanced an AI Transparency Act aimed at labeling or watermarking AI content and addressing harms from non-consensual sexual deepfakes.
加利福尼亞州還推進了一項《人工智能透明度法案》，旨在為人工智能生成內(nèi)容添加標(biāo)簽或水印，并解決未經(jīng)同意的性深度偽造所帶來的危害。
In November 2025, a bipartisan group of 35 state attorneys general urged Congress not to preempt state AI laws, highlighting state-level momentum around AI harms such as chatbots causing injuries, discrimination, and deepfake abuse.
2025年11月，由35名州檢察長組成的跨黨派團體敦促國會不要取代各州的人工智能法律，強調(diào)各州在應(yīng)對人工智能危害方面的勢頭，例如聊天機器人造成傷害、歧視和深度偽造濫用等問題。
 
Strategic regulatory lesson for 2026:
2026年的戰(zhàn)略性監(jiān)管教訓(xùn)：
 
You should assume a patchwork: 你應(yīng)當(dāng)設(shè)想一種拼湊的局面：
 
EU: horizontal, comprehensive AI Act.
歐盟：橫向、全面的人工智能法案。
U.S. states: sector- and harm-specific rules (discrimination, elections, deepfakes, consumer AI).
美國各州：針對特定行業(yè)和特定危害的規(guī)則（歧視、選舉、深度偽造、消費者人工智能）。
Vertical rules: financial, health, employment, housing, etc.
垂直規(guī)則：金融、健康、就業(yè)、住房等。
Building a single, global AI risk-management framework that can be tuned to local rules will be more sustainable than playing whack-a-mole with individual laws.
構(gòu)建一個單一的全球人工智能風(fēng)險管理框架，并使其能夠適應(yīng)當(dāng)?shù)匾?guī)則，這將比逐個應(yīng)對各項法律更具可持續(xù)性。
 
Strategy for 2026: Practical AI Compliance Priorities
2026年戰(zhàn)略：切實可行的人工智能合規(guī)重點
Given this 2025 landscape, here are concrete planning priorities for 2026.
鑒于2025年的這一局面，以下是2026年具體的規(guī)劃重點。
 
Build an AI inventory and risk map
構(gòu)建人工智能清單和風(fēng)險地圖
Catalogue all AI systems you develop or deploy (internal tools, customer-facing features, vendor models).
對您開發(fā)或部署的所有人工智能系統(tǒng)（內(nèi)部工具、面向客戶的功能、供應(yīng)商模型）進行分類編目。
Tag each system by jurisdiction, purpose, and risk (e.g., customer scoring, hiring, health, safety-critical, election content).
按管轄范圍、用途和風(fēng)險（例如，客戶評分、招聘、健康、安全關(guān)鍵、選舉內(nèi)容）為每個系統(tǒng)添加標(biāo)簽。
Map each category to obligations under the EU AI Act, Colorado AI Act, and relevant state deepfake / discrimination laws.
將每個類別與《歐盟人工智能法案》、《科羅拉多州人工智能法案》以及相關(guān)的州級深度偽造/歧視法律規(guī)定的義務(wù)相對應(yīng)。
Clean up your training data and contracts
清理你的訓(xùn)練數(shù)據(jù)和合同
Document sources and licenses for training corpora.
訓(xùn)練語料庫的文檔來源和許可。
Avoid or segregate pirated or obviously unauthorized content; it is now clearly litigated territory.
避免或隔離盜版或明顯未經(jīng)授權(quán)的內(nèi)容；這一領(lǐng)域現(xiàn)已存在明確的訴訟案例。
Update customer contracts and privacy notices to be explicit (and honest) about whether customer data will be used for training, and on what terms. Cases like the Figma lawsuit show how quickly this can become a trade secret and data-privacy problem.
更新客戶合同和隱私聲明，明確（且誠實地）說明客戶數(shù)據(jù)是否會用于訓(xùn)練以及使用條款。像Figma訴訟這樣的案例表明，這很快就可能演變成商業(yè)秘密和數(shù)據(jù)隱私問題。
Tighten AI marketing and sales claims
收緊人工智能營銷和銷售聲明
In light of the FTC’s “AI-washing” enforcement:
鑒于聯(lián)邦貿(mào)易委員會（FTC）對“人工智能洗白”的執(zhí)法行動：
 
Scrub your website, decks, and sales scripts for overblown AI claims (“fully autonomous,” “guaranteed 10x revenue,” “no human oversight needed”).
清理你的網(wǎng)站、演示文稿和銷售腳本中夸大的人工智能宣傳（“完全自主”“保證收入增長10倍”“無需人工監(jiān)督”）。
Document evidence for material claims, including benchmarks, A/B tests, or client case studies.
為重大聲明提供文件證據(jù)，包括基準(zhǔn)測試、A/B測試或客戶案例研究。
Train marketing and sales teams on what they can and cannot say about AI.
培訓(xùn)營銷和銷售團隊，讓他們知道關(guān)于人工智能可以說什么、不可以說什么。
Prepare for discovery in AI litigation
為人工智能訴訟中的證據(jù)開示做準(zhǔn)備
Cases like NYT v. OpenAI show that courts are willing to order production of massive volumes of logs and training records.
像《紐約時報》訴OpenAI案這樣的案例表明，法院愿意下令要求提供大量的日志和訓(xùn)練記錄。
 
Implement data-retention policies that balance privacy, storage cost, and anticipated litigation needs.
實施數(shù)據(jù)保留政策，在隱私、存儲成本和預(yù)期訴訟需求之間取得平衡。
Ensure your logging and observability systems avoid storing more personal data than necessary but still capture enough metadata to defend your systems (e.g., to show filtering, safety measures, and provenance).
確保你的日志記錄和可觀測性系統(tǒng)避免存儲過多不必要的個人數(shù)據(jù)，但仍要捕獲足夠的元數(shù)據(jù)以保護你的系統(tǒng)（例如，用于展示過濾、安全措施和來源）。
Stand up cross-functional AI governance
建立跨職能人工智能治理體系
For most organizations, AI is no longer “just an IT issue.” Consider:
對于大多數(shù)組織而言，人工智能不再“僅僅是一個信息技術(shù)問題”。想想看：
 
An AI Governance Committee with legal, security, product, and compliance represented.
一個由法律、安全、產(chǎn)品和合規(guī)部門代表組成的人工智能治理委員會。
A lightweight but formal AI impact assessment process for higher-risk deployments (hiring, lending, health, elections, safety-critical use).
一種針對高風(fēng)險部署（招聘、貸款、健康、選舉、安全關(guān)鍵型應(yīng)用）的輕量級但正式的人工智能影響評估流程。
Regular updates to the board on AI risk and opportunity, especially as EU and state laws phase in by 2026.
定期向董事會更新人工智能的風(fēng)險與機遇，尤其是在歐盟和各州法律將于2026年逐步實施的情況下。
What All of This Means for 2026 這一切對2026年意味著什么
If 2023–2024 were the years of AI experimentation, 2025 was the year courts and regulators began to tighten the frame. The pattern is clear:
如果說2023到2024年是人工智能的試驗之年，那么2025年就是法院和監(jiān)管機構(gòu)開始收緊框架的一年。這種模式很明顯：
 
Data provenance and licensing will decide many copyright disputes.
數(shù)據(jù)出處和許可將決定許多版權(quán)糾紛。
Truthfulness and transparency will drive enforcement around AI marketing and consumer protection.
真實性和透明度將推動圍繞人工智能營銷和消費者保護的執(zhí)法工作。
Risk-based frameworks (EU, Colorado, state laws) will reward organizations that can explain how their models work, what data they use, and what safeguards they put in place.
基于風(fēng)險的框架（歐盟、科羅拉多州、州法律）將獎勵那些能夠解釋其模型如何運作、使用何種數(shù)據(jù)以及采取了哪些保障措施的組織。
For companies building or deploying AI, 2026 is not the time to pause innovation—but it is the time to professionalize your AI compliance program. Please feel free to contact our law firm if you’d like help auditing your AI systems, updating your contracts and product claims, or building an AI governance framework tailored to your risk profile.
對于正在構(gòu)建或部署人工智能的公司而言，2026年并非暫停創(chuàng)新之時，但確實是讓人工智能合規(guī)計劃專業(yè)化的時機。如果您需要幫助審計人工智能系統(tǒng)、更新合同和產(chǎn)品聲明，或者構(gòu)建適合自身風(fēng)險狀況的人工智能治理框架，歡迎聯(lián)系我們的律師事務(wù)所。
December 29, 2025|by Law Offices of Salar Atrizadeh
發(fā)布日期：2025年12月29日 | 作者：薩拉爾·阿特里扎德律師事務(wù)所