Senior Director

Shutterstock to pay $35 million over auto-renewal and cancellation practices. May 15, 2026 According to a complaint filed by the FTC, when the FTC filed a lawsuit against Adobe over its subscription practices in 2024, people at Shutterstock took notice. When an employee referenced the lawsuit in a Slack communication and worried that Shutterstock would "be next," a Senior Product Manager responded: "hopefully we can get away with it." Now Kelley Drye & Warren LLP know the answer. This week, the FTC announced a $35 million settlement with Shutterstock over alleged violations involving auto-renewals, disclosures, and cancellation. The complaint reflects the Commission's continued focus on "negative option" features and the ways in which companies present - and obtain consent for - recurring charges. According to the FTC, Shutterstock failed to clearly and conspicuously disclose key material terms, including that certain products would automatically renew and that consumers could incur cancellation fees. The Commission alleges that these terms were often buried in fine print or otherwise presented in a way that consumers were unlikely to notice before being charged. The FTC also focused on Shutterstock's marketing of certain "on-demand packs" as being suitable for a "one-time project" with "no commitment," while allegedly failing to adequately disclose that these products could trigger automatic renewals. As in other recent cases, the agency is scrutinizing the disconnect between headline claims and the underlying billing structure. In addition, the complaint alleges that Shutterstock failed to obtain consumers' express informed consent before charging their payment methods and made it difficult to cancel subscriptions. Consumers were allegedly required to navigate time-consuming customer support channels rather than using simple online cancellation methods. Under the proposed order, Shutterstock will pay $35 million and will be required to clearly disclose material terms, obtain express informed consent, and provide straightforward cancellation mechanisms. These requirements mirror the FTC's now-familiar framework for negative option cases. If you're reading this post, wondering whether your company will be next and whether you can get away with it, the answer is maybe. But getting it wrong can be very expensive.

As AI music copyright battles grow, companies are turning to licensed training data. May 13, 2026 3:39 PM As copyright disputes continue to grow around AI-generated music, Sonilo, the world's first professionally licensed video-to-music AI platform, has partnered with Shutterstock to train its models on licensed music catalogs. The agreement gives Sonilo access to Shutterstock's music library for AI model training. According to the companies, it is Shutterstock's first partnership with a video-to-music AI platform and the timing is significant. AI music companies are facing growing pressure over how their systems are trained. Artists and record labels have increasingly challenged the use of copyrighted music in AI datasets, especially when licensing agreements or compensation structures are unclear. That tension has created a divide across the industry. Some companies have continued building models around scraped or disputed data. Others are trying to position licensing as part of the product itself. Sonilo falls into the second group. The company says its models are trained only on licensed material where artists and rights holders have agreed to participate and receive compensation. The Shutterstock partnership strengthens that position while giving Sonilo access to a larger pool of commercially cleared music. The collaboration also points to a broader change happening inside generative AI. As AI tools move into commercial production, companies are being pushed to show not just what their models can generate, but also where their training data comes from. Sonilo's platform is built around video rather than text prompts. The system analyses footage directly, studies pacing and emotional tone, then generates an original soundtrack to match the content. The company says this removes the need for manual music searches, syncing or editing workflows. The generated tracks are cleared for commercial use across social media, branded content and broadcast production. Shawn Song, CEO of Sonilo, said: "Music has always been the last unsolved layer of video creation, and video has always carried its own soundtrack. We built Sonilo to hear it and compose from it, without a single text prompt. But how we build matters as much as what we build. While others have chosen to take artists' work without permission and charge creators for the privilege, we've chosen a different path - one where artists are compensated from day one. Partnering with Shutterstock reflects that standard. Every model we train meets a bar the music industry can stand behind, because the most innovative AI platforms don't have to come at the expense of the artists who make all of these possible." For Shutterstock, the deal expands the company's growing role in generative AI infrastructure. The company has increasingly focused on licensing content for AI systems across images, video and music. Jessica April, Vice President of Data Licensing & AI Services at Shutterstock, said: "AI innovation depends on access to high-quality, rights-cleared content and trusted licensing partnerships. Sonilo's approach reflects the growing demand for responsibly sourced training data and commercially safe AI workflows. We're pleased to support companies building generative AI products with licensed content and scalable data solutions that help accelerate innovation while respecting creators and rights holders." The partnership also comes as Sonilo expands into creator and developer ecosystems. Earlier this month, the company launched as a native node inside ComfyUI, an open-source AI workflow platform used by millions of creators. Sonilo also offers API access for integration into creator tools, video platforms, game engines and other AI systems. As AI-generated music becomes more common across advertising, creator platforms and digital media, the industry's focus is shifting beyond generation alone. Questions around licensing, ownership and compensation are increasingly shaping how AI music companies position themselves and build trust with creators. Hong Kong AI biotech startup METiS TechBio draws major investor demand in IPO. METiS TechBio's blockbuster IPO signals rising investor interest in AI startups focused on how drugs are delivered inside the body May 14, 2026 3:02 PM Investors are beginning to place bigger bets on AI startups focused on drug delivery infrastructure rather than drug discovery alone. That shift was on display this week after METiS TechBio, a Hong Kong tech-bio startup focused on AI-powered drug delivery systems, debuted on the Hong Kong Stock Exchange. The listing made METiS TechBio the world's first publicly traded AI-powered drug delivery startup and the first AI-powered large-molecule biopharmaceutical startup listed in Hong Kong. The startup raised more than HKD 2.1 billion through its IPO, making it the largest healthcare listing in Hong Kong so far in 2026. Investor demand was unusually strong. The Hong Kong public offering was oversubscribed by more than 6,900 times while the international tranche recorded 82 times oversubscription. More than 280 institutional investors participated in the international placing. The strong demand reflects a wider shift in AI biotech. Over the past few years, much of the sector's attention has focused on using AI to discover new drugs or molecules. METiS is taking a different approach. The startup focuses on how medicines are delivered inside the body after they are developed. That challenge is becoming harder to ignore in biotech. Designing a therapy is only one part of the process. Delivering it precisely to specific organs, tissues or cells remains a major hurdle, especially for newer therapies involving RNA, proteins and large-molecule drugs. METiS is trying to solve that problem through its proprietary NanoForge platform. The system uses AI to design and test nanodelivery systems that help medicines reach targeted areas inside the body more efficiently. The platform combines AI models, simulation systems and high-throughput screening tools to speed up formulation development and improve delivery precision. The startup says it has already achieved targeted delivery across eight organs and tissue systems including the liver, lungs, heart, muscles and central nervous system. One of its lead programs, MTS-004, became China's first AI-enabled formulation drug to complete a Phase III clinical trial. The drug is being developed for pseudobulbar affect, a neurological condition that affects emotional expression. According to the startup, AI tools helped reduce preclinical formulation development time from up to two years to less than three months. Investor interest in the IPO also came from some of the world's largest asset managers and healthcare funds. BlackRock led the cornerstone investments with a USD 50 million subscription. Other participating investors included UBS Asset Management Singapore, Mirae Asset, ORIX Corporation, Deerfield, RTW, Hillhouse Capital and IDG Capital. METiS is also building what it describes as a "platform collaboration + product partnership" business model. The startup currently works with more than 30 pharmaceutical and biotechnology partners globally, including large pharmaceutical companies and medical research institutions. The company reported RMB 105 million in revenue in 2025, largely tied to upfront payments connected to its MTS-004 partnership agreements. It also said some platform collaboration contracts could reach milestone values of up to USD 109 million. Chris Lai said: "The future of biomedicine will no longer be simply about 'taking medicine when one falls ill.' METiS TechBio's ambition is to harness AI to build nano-rockets that can navigate with precision through the inner space of the human body's 30 trillion cells, write the code of nucleic acids and proteins into cells, and reprogram diseased and aging cells into healthy cells. This was our founding aspiration, and it is the mission to which we will dedicate our lives. The IPO marks a new starting point for us to accelerate forward, and we will strive to live up to the support and trust we have received from all sectors." The IPO also highlights how Hong Kong is increasingly positioning itself as a hub for next-generation biotech and AI healthcare startups. While investor excitement around AI drug discovery has cooled in parts of the market, startups focused on delivery systems and biotech infrastructure are beginning to attract stronger institutional backing. For METiS, the challenge now will be turning that investor confidence into commercially viable therapies and long-term partnerships. But the listing suggests that AI-driven drug delivery is starting to emerge as a category investors are willing to treat as core biotech infrastructure rather than a niche research experiment.