Weekly Industry Trends: AI in Publishing, Surging Defense Output, IT Services Disruption, and Moonshot's Kimi Adoption

Weekly Industry Trends: AI in Publishing, Surging Defense Output, IT Services Disruption, and Moonshot's Kimi Adoption This week's roundup examines the influx of AI text into self-published books, a secular surge in defense orders and manufacturing capacity, valuation adjustments in the IT services sector, and rapid user growth for Moonshot's Kimi K3 model. A multi-university study finds books with detectable AI text capture approximately 40% of observed self-published sales, driving catalog size up nearly 40x while total revenue rose about 9x. Census data indicates defense orders and shipments have increased roughly 60% since 2020, driven by items like ships, missiles, and ordnance alongside five billion dollars in munitions capacity investments. IT services consensus forward earnings multiples have dropped to about one-third of their early 2025 levels as client budgets pivot toward AI. Moonshot's Kimi app saw downloads nearly quintuple and daily active users jump roughly 40% following the K3 release, alongside a shift to spending over 60% of its ad budget on LinkedIn. Generative AI and Self-Publishing Market Dilution Research from Stony Brook, Columbia, Michigan, and the MIT Initiative on the Digital Economy highlights that self-published titles with detectable AI text now represent around 40% of observed sales, holding at least a 10% share of top-25 titles across all genres and roughly 40% in sci-fi, adventure, and dystopian categories. The low-cost volume strategy has increased the self-published catalog by nearly 40x since 2023, while total self-published revenue has expanded by nearly 9x over three years. Defense Sector Demand and Manufacturing Renaissance Rising defense backlogs, expanding manufacturing PMI for seven consecutive months, and a 60% climb in defense orders and shipments since 2020 point to a sustained industrial expansion. While unfilled orders rose by approximately $20 billion, accelerated shipments led to an estimated 20% reduction in average backlog duration, aided by a $5 billion investment in munitions production capacity and broader international demand. IT Services Repricing and Structural Evolution Consulting and IT services firms, including Accenture, have faced downward earnings repricing as enterprise technology spending shifts toward AI, bringing consensus multiples to roughly a third of their early 2025 marks. The dynamic mirrors the historic transition to cloud computing, which pressured growth before firms adapted by reskilling staff to manage implementation and integration. Moonshot Kimi K3 Global Uptake and Ad Spend Pivot Following the release of its K3 model, Moonshot experienced an immediate surge in app activity, with downloads almost quintupling and daily active users increasing by about 40%, largely driven by users outside the United States. Furthermore, SensorTower data reveals a marketing realignment for 2026, with Moonshot moving away from YouTube to allocate more than 60% of its advertising budget to LinkedIn.

本周图表：AI重塑图书市场与IT服务、国防制造繁荣及Kimi用户激增 本周图表汇总了多个维度的商业与科技动态：生成式AI凭借低成本与海量输出在自出版图书中占据可观销售份额；国防承包商订单与发货规模双双激增展现工业复苏势头；IT服务行业遭遇AI估值挤压并面临转型重塑；中国大模型初创企业月之暗面发布Kimi K3后迎来用户飙升并调整海外营销策略。 学术研究显示含有AI生成文本的图书已占据约40%的观测销量，自出版目录规模增长近40倍，整体收入增长约9倍。 自2020年以来美国国防订单与出货量均增长约60%，未交付订单增加约200亿美元，制造业PMI连续7个月扩张。 IT服务行业的一致预期估值乘数已跌至2025年初的三分之一左右，企业需重塑价值主张并面临员工再培训考验。 SensorTower数据显示月之暗面Kimi在K3发布后下载量增长近5倍且DAU增长约40%，其2026年营销预算超60%转向领英平台。 AI图书以量取胜并重塑自出版市场 来自石溪大学、哥伦比亚大学、密歇根大学和麻省理工学院数字经济实验室的研究指出，生成式AI正充斥并稀释图书市场。自2023年以来，自出版新书目录增长近40倍，但实际收入仅增长约9倍，每本书的平均收入在下降。然而，含有AI文本的图书已占据观测销量的约40%，且在各流派Top 25中至少占据10%份额（科幻/冒险/反乌托邦品类达约40%）。尽管AI图书靠低成本规模取胜挤压了人类作者，但自出版市场整体收入在3年内扩大近9倍，也在一定程度上扩张了市场总盘子。 国防工业积压订单与产出能力同步爆发 大型国防承包商收入积压自去年初起持续攀升。美国人口普查局数据显示，自2020年以来国防订单和出货量增长约60%，其中增幅主要发生在过去1.5年，以舰船、导弹和轻武器/弹药为代表的非航空通讯类装备增长最为显著。虽然未交付国防订单增加约200亿美元，但由于月度出货量加速更快，估算积压周期下降约20%。结合制造业PMI连续7个月处于扩张区间及2022年以来50亿美元产能投资，欧洲国防预算提升、美国出口增长以及装备自主化趋势共同驱动了这一长期需求脉冲。 IT服务业受AI冲击步入估值重塑期 埃森哲等IT服务巨头近期遭遇预期调整，行业一致预期盈利乘数降至2025年初的三分之一。AI并未直接消灭该行业，而是倒逼其进化与再培训。这一调整类似当年云计算对传统IT服务业的冲击：在云端转型初期，本地部署服务受挫导致增长预期崩盘，但历经3至4年的技能适应与业务转型，咨询机构凭借云迁移和实施服务重新迎来加速期。AI浪潮预计也将经历类似角色演变过程。 月之暗面Kimi模型发布带动全球增长与广告转型 月之暗面发布Kimi K3模型两周后，SensorTower数据显示其应用下载量几乎翻了五倍，日活跃用户增长约40%。该应用的影响力主要集中在美国以外地区，其全球应用内购收入规模达美国的6至7倍，并在7月份出现垂直式翻倍增长。此外，月之暗面的获客渠道在2026年发生剧烈改变，从此前在YouTube大额投入转变为将超60%的广告预算投放于领英，显示出AI应用向专业平台及企业级市场拓展的趋势。

[America](https://www.a16z.news/t/america) | [Tech](https://www.a16z.news/t/technology) | [Opinion](https://www.a16z.news/t/opinion) | [Culture](https://www.a16z.news/t/culture) | [Charts](https://www.a16z.news/t/charts) We have some more data to consider with respect to [AI’s impact on publishing](https://www.a16z.news/i/196786311/the-slop-surplus)—this time a paper from researchers at Stony Brook, Columbia, Michigan and the MIT Initiative on the Digital Economy, called “Generative AI floods and dilutes the market for books.” It’s not the friendliest title, but the gist of it is pretty straightforward: AI-generated books (either substantially or somewhat) are proliferating in the self-published categories . . . and people seem to like them? Well, whether people *like* the book slop or not, they’re definitely buying it: Books with at least some detectable AI text are now capturing \~40% of observed sales. That’s a fairly striking figure, but it’s even more striking when you consider just how easy it is to self-publish an AI book, and how many AI-ish books have come to market. Since 2023, self-published new books have proliferated *far* more quickly than either of the number of books that sell, or book sales and revenue: While the total catalogue has increased nearly 40x, actual revenues have only increased \~9x. And while non-AI books still earn the most per book, the gap has closed substantially. In other words, AI-authorship is taking a volume approach: lower-cost output has scaled the self-published catalogue massively, but since the hit-rate is lower, revenue has grown, but not by nearly as much. Hence the paper’s title: *Gen AI floods and dilutes the market for books.* Still, with enough shots on goal, eventually bookslop finds the right combination of m-dashes and ‘not this it’s that’ to attract paying customers—sometimes, a lot of paying customers (relative to the field). Again, the barriers to entry are low, which means the entries are high, which means that AI-generated/assisted books can be a chart-topper in basically any genre: Books with substantial AI text have at least a 10% share of the Top 25 across all genres, including \~40% of Sci-Fi/Adventure/Dystopian category. Flood the zone, win the zone. Sounds bad. Now, let’s take a step back for moment, though. Assuming that AI text detection actually works, the point that the authors of the study are trying to make is that AI-Books are flooding the market, winning share with volume over quality. Revenue per book is falling basically across the board, and real human writers are getting squeezed—rather than a passing fancy, “low-quality, cheap books can still reshape a market,” but really the authors are saying ‘…*will* reshape a market.’ Maybe so, but there’s a pretty obvious silver lining here. One can’t help but notice that self-published revenues by the author’s own calculations still increased *nearly 9x in just three years.* That’s perhaps a big increase off a small base, but that’s still a very big increase. If bookslop is, in fact, flooding the market, but it’s also growing the market much more quickly than it otherwise would (to the benefit of human authors), is it necessarily a bad thing that it’s capturing a larger share of revenue? Everyone knows about the cloud revenue backlog, which is generally considered a strong indicator of AI-driven demand: If Hyperscalers are spending more on compute, then they better be seeing more demand for compute, and so they are. Well, the cloud backlog is cool and all, but have you heard of the defense contractor backlog? That one is pretty impressive too: Revenue backlogs for some of the largest defense contractors have inflected upwards since the beginning of last year (although, to be fair, General Dynamics and RTX include some commercial orders, as well). It’s not quite the same parabolic curve as demand for compute, but the pull on the defense industry is definitely real. Outside of the specific defense earnings releases, the surge of defense-demand and output is showing up in the macro-picture, as well. According to Census data, both defense orders and shipments have increased \~60% since 2020, with the lion’s share of that increase occurring over the past 1.5 years: All categories of defense production have ramped up, but the biggest ramp is in the “other” category, i.e. defense orders that aren’t aircraft, search, and comms (represented by the top three layers in the stacks above). While Census doesn’t offer a more granular breakdown of “Other,” a different, more detailed series from the BEA leaves some clues. If you apply the BEA’s category mix to the Census figures, then a rough estimate suggests that ships, missiles, and small arms/ordnance are driving most of the increase in demand for defense-related production. Another interesting thing is that all this fresh defense spending has unsurprisingly led to a surge in production—yes, orders have increased, but throughput has increased even more: “Unfilled defense orders” have jumped by \~$20B, even as the estimated backlog has dropped by \~20%. This backlog is really an imperfect proxy because it’s just the quotient of the dollar value of defense orders divided by the dollar value of monthly defense shipments, and it doesn’t take into account whether it’s a mortar round or jet engine. In other words, one shouldn’t conclude that the backlog or lead time for all types of defense orders has compressed, but the aggregate picture appears that it has. But, the implication is that even as demand has ramped up substantially, the sheer volume of monthly defense shipments has accelerated more so. That follows various government reports highlighting the need for much higher defense industrial capacity (and [lengthening lead-times](https://www.gao.gov/products/gao-24-106649) for key defense orders), as well as [investment and progress](https://www.defense.gov/News/Releases/Release/Article/4026238/fact-sheet-on-efforts-of-ukraine-defense-contact-group-national-armaments-direc/) towards that end: $5B of investment in capacity has substantially increased munitions capacity since 2022, although the DOW acknowledges that target capacity is higher still. It turns out, you can, in fact, just build things, even things that have historically been built at a slow n’ steady pace. Bigger picture, you can add defense manufacturing to the [growing pile of evidence that an industrial renaissance](https://www.a16z.news/i/209134812/moar-machines) is most-definitely underway (even [if, again, there’s still a ways to go](https://www.a16z.news/i/201607529/making-the-stuff-that-makes-the-stuff)). That’s seven straight months of expansion for the manufacturing PMI, where every indicator is on the rise (except for prices paid). In terms of what’s happening, part of it is likely the ongoing conflicts with Iran and Russia, but bigger structural changes are also afoot. Outside of the US, European countries are allocating more to their defense budgets, and America’s role as a net-exporter of defense goods has only grown: Perhaps more importantly than just increased defense budgets, key battlefield components are evolving, particularly with a shift towards autonomy, and that has created urgency to evolve the industrial base, as well (with investment to match). The point being that the defense industry is undergoing more than just a seasonal glow-up and/or resupply. By all accounts, this is a secular demand impulse that isn’t going anywhere anytime soon. Charts has mused [on the ever-shifting landscape of perceived AI-winners and losers](https://www.a16z.news/i/209134812/moar-machines). We’ve [flagged Accenture](https://www.a16z.news/i/203608554/ai-enabled-or-ai-enabled), the IT services giant, as an example of a company that was at one point considered a likely beneficiary of AI implementation efforts, but has more recently become a likely loser of shifting IT budgets away from IT services, and towards AI. Unsurprisingly, Accenture is not alone amongst its peers, as IT services more generally has experienced a dramatic repricing of forward earnings: Consensus multiples for IT services are now about a third of what they were in the beginning of 2025. That’s interesting so far as it goes, but the more interesting question is less whether ‘has AI has doomed IT Services?’ so much as ‘well, what is IT Services gonna do about it?’ No one knows the future, of course, but this seems like a perfect example [of rather than AI eliminating a function, AI is forcing it to evolve.](https://www.a16z.news/i/196544663/augmentation-substitution-and-the-jobs-that-dont-yet-exist) Consulting firms are going to have to invest the time and effort to adapt and improve their value proposition (and perhaps even their business models) in response to this brave new world. Some part of that is “reskilling,” an effort that is likely already reflected in the broader premium for more senior talent (possessing the required skills to be AI-useful right now). Reskilling tends to take some time, and it wouldn’t make sense to hire a brand new cohort of young consultants, before you know what they’re being hired to do (and how they’re going to be trained to do it). On the bright side, this sort of bust-to-boom transition has happened to IT services before. The shift to cloud *also* put a major damper on IT services (as they were), and *also* forced the industry to adapt and evolve—which it did: It took 3-4 years from the collapse of cloud-driven growth expectations for IT services to recover, but eventually the threat became an opportunity. On-prem services were disrupted by the shift to off-prem—and the pain for consultants was real—until they adapted their skills and offerings to become the experts in lift n’ shift (and everything else that entailed). Once again, the good times rolled for IT Services. Not for everyone, of course. The consultants that didn’t or couldn’t adapt continued to languish, but for the ones who did, tech disruption became a massive accelerant. Change was not painless, but it was net-good. There’s no reason to think that AI will have a dissimilar effect. Roles will evolve, and some will become obsolete, but for others still, AI will be a force-multiplier. It feels like ages, but it was really only two weeks ago that Moonshot released its Kimi K3 model, leading to a total timeline takeover for the open v. closed debate. Obviously all that attention meant that lots of people wanted to know what all the fuss was about, and so they decided to see for themselves: According to data from SensorTower, Kimi app downloads and daily active users both surged practically overnight. Downloads nearly quintupled, and DAUs jumped by \~40%. For now, at least, K3’s coming out party, is more than just hype—people are definitely giving the model a spin. As an aside, it does seem like the vast majority of Kimi’s impact happened outside the US: SensorTower’s estimates of in-app weekly purchasing volume definitely increased in the US (off a relatively small baseline), but the global leap was far more pronounced. Kimi’s global revenue reach has apparently been increasing since the beginning of the year—already 6-7 times higher than in the US—but gross in-app purchase revenue went vertical in July, and basically doubled in just a week. In other words, for all the hype, Kimi is still much more of a global (and Chinese) phenomenon than a US one. Interestingly, SensorTower also provides some evidence that Moonshot is trying to change that, however—not just by shifting its geographic focus, but potentially by making a move on a different vertical: Moonshot’s 2026 marketing strategy looks nothing like its 2025 marketing strategy. The Chinese lab went from spending big money on YouTube to directing more than 60% of its advertising fire on LinkedIn (while YT has become an afterthought). Now, putting advertising dollars to work on LinkedIn doesn’t necessarily mean that Moonshot is making an enterprise play, but it might mean that. Nor is Moonshot the only one who advertises on LinkedIn—data from earlier this year suggested [that LinkedIn was the favored advertising channel for AI apps, in general.](https://www.a16z.news/i/186910818/4-ai-coming-for-search-traffic) In all events, LinkedIn is now apparently the place to get your AI slop from all ends…AI-generated career poasting with a steady supply of AI ads to help you pick your weapon of choice. *This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. Furthermore, this content is not investment advice, nor is it intended for use by any investors or prospective investors in any a16z funds. This newsletter may link to other websites or contain other information obtained from third-party sources - a16z has not independently verified nor makes any representations about the current or enduring accuracy of such information. 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