Tools & Platforms
SAS’s Unconventional AI Playbook for Productionizing Prototypes

Data science and AI teams are all familiar with the paradox that enterprise AI currently faces: impressive prototypes and experiments but little tangible return on their substantial investments. This has led many CEOs to lament failed implementations, regulatory compliance nightmares, and a widening gap in turning proof-of-concepts into production reality behind closed doors. They realize that GenAI alone cannot solve complex enterprise data challenges.
Established players like SAS see this POC-to-production crisis as an unexpected opportunity. The 49-year analytics veteran is leveraging strategic acquisitions, investments in emerging technologies like quantum computing and digital twins, and a renewed focus on multi-cloud flexibility. The question is whether it’s repositioning as the anti-hype alternative will resonate in a market tired of hyperbole.
The right technology for the right problem
Research shows the global market for agentic AI will reach over USD93 billion by 2032, with many organizations already integrating AI agents into their workflows. Yet, beneath these promising statistics lies a troubling disconnect between AI investment and measurable outcomes.
Speaking at the sidelines of SAS Innovate on tour 2025 in Singapore, Gavin Day, SAS’s executive vice president and chief operating officer, acknowledges that many customers have spent “significant amounts of money prototyping and doing cool stuff” with GenAI, but they struggle to “make the leap from what you’re doing in the back of the room… into something that generates value”.
SAS is zeroing in on this production gap by emphasizing a core principle: using the right AI technology for the right problem. This means recognizing that there is a time and place for traditional machine learning and statistical methods, a time for GenAI, and a time for new approaches like agentic AI. The goal is to move beyond the buzzwords and deliver solutions that are reliable, compliant, and scalable for enterprise deployment.
Agentic AI: SAS’s answer to GenAI limitations
SAS is positioning agentic AI — AI systems that can operate with varying degrees of human oversight — as the next evolution beyond simple GenAI models. As senior vice president of global marketing, Patrick Xhonneux explained in his opening keynote, SAS defines this as a spectrum between “human out of the loop” for autonomous decisions and “human in the loop” for flagged interventions requiring human review.
In a mortgage lending scenario, an intelligent agent analyzes irregular transactions, calculates risk, and compiles a summary for human review. The key differentiator, according to Xhonneux, is not just the agent but the transparency and explainability it provides. The platform offers “model cards” that function like a “nutrition label” for the model, providing details on usage, data summary, performance, and fairness. For a data scientist, the platform also provides a “decision logic flow” that gives a transparent look into how each applicant moves through multiple decision points in the workflow. This approach uses a deterministic model to make the decision while using probabilistic LLMs to provide the explanation.
This focus on explainability directly addresses a critical pain point: systemic bias. A recent study found that large language models recommended “more denials and higher interest rates for black applicants” compared to white applicants with identical profiles. The discrepancy was found “across all language models, including OpenAI, Anthropic and Meta”. SAS’s model governance technology, which has been developed over decades, is now adapted to monitor for drift and bias in newer technologies, running “model tournaments” to ensure models are performing as expected.
Why synthetic data matters to enterprise AI analytics
SAS’s acquisition strategy is less about buying revenue or customers, but more about acquiring “pieces of technology that complement either gaps that we have or to accelerate time to market,” said Day. The acquisition of Hazy, a synthetic data specialist, exemplifies this. The purchase directly addresses training data limitations in regulated industries where “the data training needs exceeded what they could generate and exceeded what they have”.
The synthetic data play serves dual purposes. It enables innovation in data-starved environments and provides a cost and productivity benefit. As Riad Gydien, executive vice president and chief sales officer, noted, in a regulated industry, you cannot make sensitive data “generally available to analysts everywhere to go and innovate”. Synthetic data reduces the cost and complexity of innovation, allowing analysts to work with “almost freely available data” before a model moves into production, where real data is used for inferencing.
Reimagining analytics gaming engines and quantum AI
Perhaps SAS’s most ambitious AI integration involves partnering with Epic Games to bring Fortnite’s Unreal Engine into industrial analytics. The collaboration with Georgia-Pacific demonstrates this approach, where SAS optimized manufacturing plant operations using photorealistic digital twins.
The results were counterintuitive: “Adding extra AGVs (automated guided vehicles) actually is going to slow down your operation” due to traffic jams, requiring “to decrease the fleet side by three vehicles” to improve average mission time by 8%. This type of complex optimization problem, involving 400-meter-long facilities “larger than four football fields,” showcases how game engines can surface insights impossible to visualize through traditional dashboards, said Xhonneux.
The digital twin strategy extends beyond manufacturing into employee safety, where “we can add digital humans…test different scenarios to identify potential dangerous situations without causing risk to employees in the real world.”
SAS is also exploring quantum computing as an optimization accelerator, positioning QPUs alongside CPUs and GPUs in hybrid architectures. Early results are promising: a recent implementation for “a very large CPG organization” achieved “3% improvement in results and a 97% reduction in time of computation,” said Xhonneux.
The company’s quantum strategy emphasizes seamless integration: “SAS software will automatically select which portion of your problem should use the CPU, the GPU or the QPU,” making quantum acceleration transparent to end users.
Breaking down the “walled garden”
SAS is making a calculated bet against the “walled garden” approach adopted by some competitors. The company’s Viya platform supports multiple programming languages (Python, R, SAS) and deployment models (on-premises, hybrid, multi-cloud). “SAS is not a walled garden,” Day stated definitively. “The days of monolithic software vendors are over”. This architectural flexibility addresses a critical enterprise reality where customers need to use a “best of breed” approach and integrate with various vendors.
The strategy also addresses the challenges of data movement and sovereignty. SAS has engineered its technology to “bring the analytics to the data” rather than moving the data to the analytic engine, said Day. By placing the SAS container next to a Snowflake or other containers, analytics can run right next to the data, reducing data movement costs and improving performance.
The challenges of a 49-year legacy
SAS’s long track record is both an asset and a challenge. Day acknowledged that the company grew organically, which led to multiple financial systems and self-contained business units in various countries that “don’t scale”. The company has undergone a significant infrastructure modernization journey, centralizing finance and HR and consolidating financial systems into Oracle Fusion in preparation for potential public markets.
Gydien also noted that while SAS has a “global install base of hundreds of thousands of sites,” many of these customers “do more than one thing with us out of the entire portfolio we have”. This suggests that while new customer acquisition is essential, a significant opportunity lies in expanding their footprint within existing accounts. This is a “much more nuanced go-to-market approach” than simply focusing on new logo acquisition, Gydien added.
Shaping the future of enterprise AI analytics
As the analytics landscape evolves with AI, SAS is betting that enterprises will ultimately prioritize governance, explainability, and production reliability over experimental capabilities. This approach is informed by the company’s multi-decade perspective on technology hype cycles, which helps them “look and prioritize our investments”.
For data scientists and machine learning engineers, a critical shift is underway: the competitive edge in enterprise AI is no longer about experimental capabilities but about production-ready, governed systems that deliver measurable ROI. The conversations at SAS Innovate on tour 2025 in Singapore confirm that this change couldn’t have come a moment too soon, signaling that SAS is listening closely to the market pulse.
It also means that the real disruption isn’t just happening in Silicon Valley startups. Instead, it’s occurring in the unglamorous but essential work of making AI systems reliable, compliant, and scalable for enterprise deployment. And based on SAS’s moves, that is where the real battle for mindshare is occurring.
Image credit: iStockphoto/IvelinRadkov
Tools & Platforms
The Most Popular Apps According to AI

By Richard D. Harroch and Dominique A. Harroch
Apps have become an integral part of our lives, simplifying daily tasks and enhancing how we interact with technology. They address various needs, including communication, social networking, productivity, and entertainment. Whether on a smartphone, tablet, or computer, these tools provide convenient solutions for staying organized and connected.
These apps have amassed significant followings because of their intuitive design, usefulness, and the value they offer users. This article showcases 10 of the most popular apps, examining their standout features, benefits, and the reasons they resonate with so many. From social media to productivity aids, these apps play vital roles in our day-to-day routines.
Let’s explore these popular apps, supported by insights from AI, to understand how they’ve shaped the way we communicate, work, and entertain ourselves.
Popular Apps
1. WhatsApp
WhatsApp is a messaging app that allows users to send text messages, voice messages, images, and videos over the internet. It uses end-to-end encryption, ensuring privacy for all communication between users. With its widespread international use, WhatsApp has become one of the most reliable communication tools for both personal and professional purposes. The app is available on multiple platforms, including iOS, Android, and desktop.
Additional Insights:
- Cross-platform functionality: WhatsApp works seamlessly across iOS, Android, and desktop, keeping users connected at all times.
- Voice and video calls: In addition to messaging, WhatsApp allows users to make high-quality voice and video calls.
- Group chats: Organize group conversations with up to 256 participants for work or social purposes.
- Media sharing: Share photos, videos, documents, and voice messages directly within the chat.
- Status updates: Users can share temporary status updates, similar to Instagram Stories, that disappear after 24 hours.
- Business communication: WhatsApp Business is designed for companies to connect with their customers, offering quick replies and automated messages.
2. Instagram
Instagram is a popular social media platform centered around sharing photos, videos, and stories. Launched in 2010, it was quickly adopted by millions of users worldwide and is now owned by Facebook (Meta). Instagram provides a visually-driven experience with creative tools, filters, and effects, making it one of the most engaging apps for both personal and business use. It has also evolved to include features like Reels and IGTV, adding more ways to interact and create content.
Additional Insights:
- Photo and video sharing: Instagram allows users to post images and videos to their profiles, which can be liked and commented on by followers.
- Stories: Share temporary posts that disappear after 24 hours, offering a casual way to connect with followers.
- Reels: Short-form video content similar to TikTok, providing users with tools to create engaging videos.
- Shopping: Businesses can set up shops directly on Instagram to sell products through the platform.
- IGTV: A feature for posting longer video content, ideal for tutorials, performances, or interviews.
- Hashtags: Using hashtags allows users to discover content related to specific topics or trends.
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3. TikTok
TikTok is a short-form video app that has rapidly gained global popularity. It allows users to create and share videos, typically 15 to 60 seconds long, with music, effects, and filters. TikTok’s algorithm curates a personalized feed for each user, making it easy to discover content based on interests. The app has given rise to viral trends, memes, and challenges, creating a unique cultural phenomenon.
Additional Insights:
- Video creation: TikTok offers a variety of effects, filters, and music options to enhance video creation.
- Viral challenges: Users can participate in viral challenges, often driven by popular trends or dances.
- For You page: TikTok’s algorithm delivers personalized content based on your previous interactions and interests.
- Live streaming: Creators can engage with their audience in real-time through live broadcasts.
- Influencers: Many influencers have risen to prominence due to their creative and viral TikTok content.
- E-commerce: TikTok has partnered with e-commerce platforms, allowing businesses to sell products directly through the app.
4. YouTube
YouTube is a huge video-sharing platform, offering a vast range of content, from educational videos to entertainment, vlogs, and music. YouTube allows users to upload, share, and watch videos, with a comment and subscription system to engage with creators. While a free platform, YouTube also has a paid premium version that offers ad-free viewing, offline downloads, and YouTube Music. It’s a go-to destination for content creators and viewers alike.
Additional Insights:
- Video uploads: Anyone with a Google account can upload and share videos, making it a hub for user-generated content.
- Monetization: YouTubers can earn money through ads, sponsorships, and YouTube’s Partner Program.
- Live streaming: Creators can live stream events, performances, or casual Q&A sessions to engage with their audience.
- Playlists: Users can create and share playlists of their favorite videos.
- YouTube Premium: A paid subscription service that removes ads and offers additional features like YouTube Music.
- Community features: The platform allows users to comment, like, share, and interact with content creators.
5. Facebook
Facebook (owned by Meta) is one of the largest social networking sites in the world, allowing users to connect with friends, family, and communities. It enables individuals to share updates, photos, and videos, and stay updated on events. Facebook also offers tools for businesses to promote products, create advertisements, and communicate with customers. With over 2.8 billion active users, it remains one of the most popular apps for social interaction and digital marketing.
Additional Insights:
- Profile creation: Users can create personalized profiles to share life updates and interact with friends.
- Groups and events: Facebook allows users to join groups based on shared interests or create events to invite people.
- Marketplace: A feature for buying and selling items locally, which has become a popular alternative to traditional classified ads.
- Facebook Ads: Businesses can target users with ads based on demographics, interests, and behaviors.
- Messenger: A separate app for Facebook’s messaging service, allowing users to chat privately or in groups.
- Video content: Facebook supports video uploads, live streaming, and the ability to watch content shared by friends or pages.
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6. Spotify
Spotify is a music streaming app that offers access to millions of songs, podcasts, and playlists. The app allows users to create custom playlists, explore curated content, and discover new music based on preferences. Spotify also offers a premium version, providing ad-free listening, offline playback, and enhanced audio quality. It has become one of the top music streaming platforms globally, with both free and paid options.
Additional Insights:
- Personalized playlists: Spotify creates custom playlists like “Discover Weekly” based on listening habits.
- Podcast integration: Offers a large library of podcasts, from news to entertainment and educational content.
- Offline listening: Premium users can download songs and listen offline.
- Collaborative playlists: Share playlists with friends and collaborate in real-time.
- Social sharing: Share what you’re listening to on social media or with friends within the app.
- Cross-platform use: Spotify is available on smartphones, tablets, desktops, smart speakers, and other devices.
7. Snapchat
Snapchat is a multimedia messaging app known for its unique feature: photos and videos that disappear after being viewed. The app includes fun filters, lenses, and effects to enhance photos and videos. Snapchat has become especially popular among younger generations, offering a more casual, fast-paced way to communicate. Features like Stories, Snap Map, and Discover make Snapchat a dynamic platform for both personal and brand use.
Additional Insights:
- Ephemeral content: Messages and images disappear after they’ve been viewed, encouraging spontaneous communication.
- Filters and lenses: Snapchat offers numerous creative tools to modify photos and videos.
- Snap Map: See where your friends are located and view local stories in your area.
- Stories: Share your day through temporary posts that last for 24 hours.
- Discover feature: View content from celebrities, influencers, and brands within the app.
- Bitmoji integration: Create a personalized emoji character for use in chats and messages.
8. X (Formerly Twitter)
X is a social media platform known for short-form posts (previously called tweets), limited to 280 characters. It allows users to follow individuals, brands, and organizations to stay updated with news, trends, and conversations. X has become a hub for real-time communication and is used by businesses, politicians, and celebrities to engage with the public. The platform’s simplicity and immediacy make it useful for sharing updates and opinions quickly.
Additional Insights:
- Trending topics: Twitter highlights current trends based on global conversations.
- Hashtags: Use hashtags to categorize posts and increase visibility on specific topics.
- Retweets: Share others’ posts with your followers to amplify content.
- Verified accounts: Twitter’s blue check mark signifies authenticity for public figures and organizations.
- Direct messaging: Private messaging is allowed for one-on-one communication between users.
- Polls and surveys: X allows users to conduct polls to gauge public opinion.
- Elon Musk. X was acquired by a group led by Elon Musk.
9. Google Maps
Google Maps is a navigation app that helps users find their way to destinations, offering real-time traffic updates, walking, driving, and public transport directions. It also offers features like location sharing, restaurant reviews, and business hours. Google Maps has become an essential tool for navigating both familiar and unfamiliar places, providing detailed maps, satellite imagery, and 3D views of locations. It’s also integrated with Google Street View, which allows users to explore destinations virtually.
Additional Insights:
- Turn-by-turn navigation: Provides detailed, real-time directions for driving, walking, and biking.
- Traffic updates: Get live traffic information and alerts to avoid delays.
- Street View: Explore neighborhoods and businesses through interactive 360-degree images.
- Business information: View reviews, photos, hours, and contact details for local businesses.
- Offline maps: Save maps for offline use in case of poor network coverage.
- Location sharing: Share your live location with friends or family for real-time updates.
10. Uber
Uber is a ride-sharing app that has transformed how people commute in cities around the world. With a simple and user-friendly interface, Uber allows users to request rides, track their driver’s location in real-time, and pay for services seamlessly through the app. It offers various ride options, including standard rides, carpooling (UberPOOL), and luxury vehicles (UberBlack), providing flexibility based on the user’s needs and budget. Uber also provides additional services like food delivery through Uber Eats, making it a versatile and widely used app for both transportation and food ordering.
Additional Insights:
- Global availability: Uber operates in over 900 metropolitan areas across more than 60 countries.
- Ride tracking: Users can track their driver’s location and estimated time of arrival in real time.
- Multiple ride options: Choose from economy, premium, and shared rides based on your preferences and budget.
- Cashless payment: Pay for rides through the app using your linked credit or debit card.
- Uber Eats: In addition to rides, Uber offers food delivery from local restaurants through Uber Eats.
- Driver ratings: After each ride, both drivers and passengers rate each other to ensure a safe and pleasant experience.
Conclusion on Popular Apps
These 10 apps have earned their place among the most popular, shaping how we communicate, navigate, and entertain ourselves in the modern world. Each app offers something unique, whether it’s the ability to share photos with friends, shop for anything online, or discover new music—ensuring that there’s something for everyone. The widespread use of these apps shows just how important technology has become in our daily lives, influencing the way we work, socialize, and stay connected.
As technology continues to evolve, these apps are likely to introduce new features and capabilities to keep up with the changing needs of users. The future promises even more advanced versions of these tools, bringing more functionality and convenience to help users stay productive, entertained, and engaged. Whether you’re managing work, enjoying entertainment, or connecting with friends, these apps provide the tools needed for success and enjoyment in today’s digital age.
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About the Authors
Richard D. Harroch is a Senior Advisor to CEOs, management teams, and Boards of Directors. He is an expert on M&A, venture capital, startups, and business contracts. He was the Managing Director and Global Head of M&A at VantagePoint Capital Partners, a venture capital fund in the San Francisco area. His focus is on internet, digital media, AI and technology companies. He was the founder of several Internet companies. His articles have appeared online in Forbes, Fortune, MSN, Yahoo, Fox Business and AllBusiness.com. Richard is the author of several books on startups and entrepreneurship as well as the co-author of Poker for Dummies and a Wall Street Journal-bestselling book on small business. He is the co-author of a 1,500-page book published by Bloomberg on mergers and acquisitions of privately held companies. He was also a corporate and M&A partner at the international law firm of Orrick, Herrington & Sutcliffe. He has been involved in over 200 M&A transactions and 250 startup financings. He can be reached through LinkedIn.
Dominique Harroch is the Chief of Staff at AllBusiness.com. She has acted as a Chief of Staff or Operations Leader for multiple companies where she leveraged her extensive experience in operations management, strategic planning, and team leadership to drive organizational success. With a background that spans over two decades in operations leadership, event management at her own start-up and marketing at various financial and retail companies. Dominique is known for her ability to optimize processes, manage complex projects and lead high-performing teams. She holds a BA in English and Psychology from U.C. Berkeley and an MBA from the University of San Francisco. She can be reached via LinkedIn.
Copyright (c) by Richard D. Harroch. All Rights Reserved
Tools & Platforms
I Interned at Google, but Chose to Start My Career at an AI Startup

This as-told-to essay is based on a conversation with Advait Maybhate, a software engineer. The following has been edited for length and clarity. Business Insider has verified his employment and academic history.
When I graduated from the University of Waterloo with my bachelor’s degree in 2023, I had done about a dozen tech internships.
Internships are a big deal at Waterloo, and students usually do six during their time there. I started doing internships before I enrolled and took some gap semesters to squeeze in a couple more stints.
To me, internships meant exploring varied fields, from gaming to fintech. I also got to intern at companies of different scales, from early-stage startups to mature Big Tech companies.
The first summer internship I did at Waterloo was at Google. Interning there was an eye-opening experience. I got to work on Google Search, a product that billions of people, including myself, use every single day.
When I took up the internship, like any freshman, I just thought it would be cool to work at a big company and ship big products. I ended up interning at Google twice, first in the summer of 2019, and then during the following summer in 2020.
During my internships at Google, I learned a lot, particularly about operating as a software engineer on large-scale products. That included learning how to write unit tests and good technical design documents. Big companies are great at that.
That said, I didn’t enjoy the bureaucracy that came with working in a Big Tech company. If you are shipping something on Google Search, you cannot break Google Search. That is just one of the underlying rules.
I understand why things have to be slow at that scale. It’s just that for someone who wants to learn fast and try out different things, it can feel limiting.
Even for my internship projects, it took a few months just for the code to get shipped. Although the projects were technically done, we still had to conduct A/B testing experiments and get sign-offs before the code could be deployed.
Going from Big Tech to startups
That experience eventually set me on the path toward working at startups. I chose to focus on AI because I wanted to be at the edge of what technology can do.
I was initially an AI skeptic. I didn’t buy into the hype of how it could change everything. It was only when I started using AI on a day-to-day basis that I began to appreciate how it could usher in a fundamental shift in the way we work.
It also helps that working on AI is fun and exciting. There are new advancements in space every week, and the frontier of what we can do just keeps going further.
I ended up doing two internships at two AI startups before I graduated. The first one was at Warp, an AI agent platform for developers, and the second one was at Ramp, a fintech startup that uses AI to automate financial operations.
I received full-time offers from both Warp and Ramp and chose to work at Warp. Both were great companies, but I wanted to work at Warp because I wanted to be part of a startup that was in a relatively early stage of development.
Ramp was at a much more mature stage than Warp at the time, and was focused on scaling up. Warp, on the other hand, was still trying to figure things out. On a personal level, I wanted to see how a startup goes through that process. I wanted to grapple with questions like, “How does pricing work? How does the business model work?”
That is harder to see at a mature startup, where all of these things have already been figured out and growth is the priority.
So far, working at Warp for the past two years has lived up to my expectations. We ship code every week. I could be working on something on Tuesday, and it gets shipped out on Thursday. I work maybe 60 to 70 hours a week. It’s a very different kind of velocity and cadence than at Big Tech.
In the near term, I want to continue to work on AI because it’s one of the most rapidly expanding areas in tech. Companies like Warp and its competitors, Cursor and Cognition, are all expanding very rapidly.
I am somewhat tempted to launch my own startup, but I think it’s difficult to gain market share in this hyper-competitive space. That’s something I will give serious thought about in the future.
Do you have a story to share about working at an AI startup? Contact this reporter at ktan@businessinsider.com.
Tools & Platforms
China’s top social media platforms take steps to comply with new AI content labeling rules

China’s top social media platforms, including ByteDance Ltd.’s TikTok clone Douying and Tencent Holdings’ WeChat, rolled out new features today to try to comply with a new law that mandates all artificial intelligence content is clearly labeled as such.
The new content labeling rules mandate that all AI-generated content posted on social media is tagged with explicit markings visible to users. It applies to AI-generated text, images, videos and audio, and also requires that implicit identifiers, such as digital watermarks, are embedded in the content’s metadata.
The law, which was first announced in March by the Cyberspace Administration of China, reflects Beijing’s increased scrutiny of AI at a time when concerns are rising about misinformation, online fraud and copyright infringement.
According to a report in the South China Morning Post, the law comes amid a broader push by Chinese authorities to increase oversight of AI, as illustrated by the CAC’s 2025 Qinglang campaign, which aims to clean up the Chinese language internet.
WeChat, one of the most popular messaging platforms in China, which boasts more than 1.4 billion monthly active users globally, has said that all creators using its platform must voluntarily declare any AI-generated content they publish. It’s also reminding users to “exercise their own judgement” for any content that has not been flagged as AI generated.
In a post today, WeChat said it “strictly prohibits” any attempts to delete, tamper with, forge or conceal AI labels added by its own automated tools, which are designed to pick up any AI-generated content that’s not flagged by users who upload it. It also reminded users against using AI to spread false information or for any other “illegal activities.”
Meanwhile Douyin, which has around 766 million monthly active users, said in a post today that it’s encouraging users to add clear labels to every AI-generated video they upload to its platform. It will also attempt to flag AI-generated content that isn’t flagged by users by checking its source via its metadata.
Several other popular social media platforms made similar announcements. For instance, the microblogging site Weibo, often known as China’s Twitter, said on Friday it’s adding tools for users to tag their own content, as well as a button for users to report “unlabeled AI content” posted by others.
RedNote, the e-commerce-based social media platform, issued its own statement on Friday, saying that it reserves the right to add explicit and implicit identifiers to any unidentified AI-generated content it detects on its platform.
Many of China’s best known AI tools are also moving to comply with the new law. For instance, Tencent’s AI chatbot Yuanbao said on Sunday it has created a new labeling system for any content it generates on behalf of users, adding explicit and implicit tags to text, videos and images. In its statement, it also advised users that they should not attempt to remove the labels it automatically adds to the content it creates.
When the CAC announced the law earlier this year, it said its main objectives were to implement robust AI content monitoring, enforce mandatory labeling and apply penalties to anyone who disseminates misinformation through AI or uses the technology to manipulate public opinion. It also pledged to crack down on deceptive marketing that uses AI, and strengthen online protections for underage users.
The European Union is set to implement its own AI content labeling requirements in August 2026, as part of the EU AI Act, which mandates that any content “significantly generated” by AI must be labeled to ensure transparency. The U.S. has not yet mandated AI content labels, but a number of social media platforms, such as Meta Platforms Inc., are implementing their own policies regarding the tagging of AI-generated media.
Photo: WeChat
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