German data protection official Meike Kamp has filed a formal request that Apple and Google remove the DeepSeek app from their respective app stores for the illegal transfer of users’ personal data to China, in violation of European Union law.
Meike Kamp, the Commissioner for Data Protection and Freedom of Information, previously requested in May that DeepSeek voluntarily comply with the legal requirements for data transfer to other countries, stop the transfer of data altogether, or remove their app from the Apple and Google app stores.
Failure to respond to those requests resulted in the official taking the next step of filing a report of illegal content to both Apple and Google who will then examine and decide DeepSeek’s future on their platforms.
“The transfer of user data by DeepSeek to China is unlawful. DeepSeek has not been able to convincingly prove to my authority that data from German users:
Inside China is protected at a level equivalent to that of the European Union.
Chinese authorities have extensive access rights to personal data within the sphere of influence of Chinese companies.
In addition, DeepSeek users in China do not have enforceable rights and effective remedies guaranteed in the European Union.
I have therefore informed Google and Apple, as operators of the largest app platforms, about the violations and expect a blocking to be checked as soon as possible.”
Takeaways
Enforcement of Data Privacy Laws Germany is taking formal steps to enforce EU data privacy regulations by targeting app distribution channels (Apple and Google).
International Data Transfer Violations DeepSeek is accused of transferring personal user data to China without ensuring protections as required by EU standards.
China’s Data Access The lack of enforceable user rights and legal remedies in China is a central concern, due to the government’s extensive access rights over data held by Chinese companies.
Escalation of Regulatory Action A report of illegal content was sent to Apple and Google after DeepSeek ignored a voluntary compliance request.
Decision Pending At Apple And Google Apple and Google will assess the reported violation and have the option to block the DeepSeek app in Germany.
Germany’s data protection official has formally requested that Apple and Google remove the DeepSeek app from their app stores due to illegal data transfers of German users’ personal information to China. The request follows concerns over Chinese government access to sensitive user data, after DeepSeek failed to comply with EU data protection standards.
Google has rolled out a new version of Search Console Insights, now integrated directly into the main Search Console interface. This update ends the standalone beta experience.
The new report aims to make it easier to understand your site’s search performance without requiring advanced analytics skills.
What’s New?
Previously accessible through a separate interface, Search Console Insights now lives within the primary Search Console dashboard.
Google describes this as a more “cohesive experience,” bringing insights closer to the tools you already rely on.
The update is designed with non-technical users in mind, including bloggers, small business owners, and content creators seeking to understand how their content performs on Google Search.
Here’s an example of what the integrated experience looks like:
Screenshot from: developers.google.com/search/blog/2025/06/search-console-insights, June 2025.
Highlights From the Updated Report
1. Performance Overview
You can view total clicks and impressions from Google Search, along with comparisons to previous periods.
2. Page Performance
The report identifies which pages are getting the most clicks, along with “trending up” and “trending down” pages, offering insight into what’s working and what may need updating.
3. Achievements Feature Retained
Google is continuing the “Achievements” feature, which celebrates milestones like reaching new click thresholds.
While you can still access past achievements via email links, Google says direct sidebar access will be available in the next few weeks.
4. Search Query Trends
You can see top-performing queries and spot rising trends, which Google suggests can serve as inspiration for new content. Queries with declining performance are also highlighted.
Here’s an example of what this report looks like:
Screenshot from: developers.google.com/search/blog/2025/06/search-console-insights, June 2025.
Gradual Rollout In Progress
The new Insights experience is being rolled out gradually. If you don’t see it immediately, it will likely appear over the coming weeks.
This phased approach allows Google to monitor system performance and incorporate early feedback before releasing the feature to everyone.
How This Helps
By integrating simplified reporting into the main dashboard, Google is bridging the gap between entry-level insights and more advanced analytics.
If you found the existing Performance report overwhelming, this update could offer a more approachable alternative.
For agencies and consultants, the simplified view may also serve as a communication tool for clients less familiar with technical metrics.
Google announced a new multi-vector retrieval algorithm called MUVERA that speeds up retrieval and ranking, and improves accuracy. The algorithm can be used for search, recommender systems (like YouTube), and for natural language processing (NLP).
Although the announcement did not explicitly say that it is being used in search, the research paper makes it clear that MUVERA enables efficient multi-vector retrieval at web scale, particularly by making it compatible with existing infrastructure (via MIPS) and reducing latency and memory footprint.
Vector Embedding In Search
Vector embedding is a multidimensional representation of the relationships between words, topics and phrases. It enables machines to understand similarity through patterns such as words that appear within the same context or phrases that mean the same things. Words and phrases that are related occupy spaces that are closer to each other.
The words “King Lear” will be close to the phrase “Shakespeare tragedy.”
The words “A Midsummer Night’s Dream” will occupy a space close to “Shakespeare comedy.”
Both “King Lear” and “A Midsummer Night’s Dream” will be located in a space close to Shakespeare.
The distances between words, phrases and concepts (technically a mathematical similarity measure) define how closely related each one is to the other. These patterns enable a machine to infer similarities between them.
MUVERA Solves Inherent Problem Of Multi-Vector Embeddings
The MUVERA research paper states that neural embeddings have been a feature of information retrieval for ten years and cites the ColBERT multi-vector model research paper from 2020 as a breakthrough but that says that it suffers from a bottleneck that makes it less than ideal.
“Recently, beginning with the landmark ColBERT paper, multi-vector models, which produce a set of embedding per data point, have achieved markedly superior performance for IR tasks. Unfortunately, using these models for IR is computationally expensive due to the increased complexity of multi-vector retrieval and scoring.”
Google’s announcement of MUVERA echoes those downsides:
“… recent advances, particularly the introduction of multi-vector models like ColBERT, have demonstrated significantly improved performance in IR tasks. While this multi-vector approach boosts accuracy and enables retrieving more relevant documents, it introduces substantial computational challenges. In particular, the increased number of embeddings and the complexity of multi-vector similarity scoring make retrieval significantly more expensive.”
Could Be A Successor To Google’s RankEmbed Technology?
The United States Department of Justice (DOJ) antitrust lawsuit resulted in testimony that revealed that one of the signals used to create the search engine results pages (SERPs) is called RankEmbed, which was described like this:
“RankEmbed is a dual encoder model that embeds both query and document into embedding space. Embedding space considers semantic properties of query and document in addition to other signals. Retrieval and ranking are then a dot product (distance measure in the embedding space)… Extremely fast; high quality on common queries but can perform poorly for tail queries…”
MUVERA is a technical advancement that addresses the performance and scaling limitations of multi-vector systems, which themselves are a step beyond dual-encoder models (like RankEmbed), providing greater semantic depth and handling of tail query performance.
The breakthrough is a technique called Fixed Dimensional Encoding (FDE), which divides the embedding space into sections and combines the vectors that fall into each section to create a single, fixed-length vector, making it faster to search than comparing multiple vectors. This allows multi-vector models to be used efficiently at scale, improving retrieval speed without sacrificing the accuracy that comes from richer semantic representation.
According to the announcement:
“Unlike single-vector embeddings, multi-vector models represent each data point with a set of embeddings, and leverage more sophisticated similarity functions that can capture richer relationships between datapoints.
While this multi-vector approach boosts accuracy and enables retrieving more relevant documents, it introduces substantial computational challenges. In particular, the increased number of embeddings and the complexity of multi-vector similarity scoring make retrieval significantly more expensive.
In ‘MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings’, we introduce a novel multi-vector retrieval algorithm designed to bridge the efficiency gap between single- and multi-vector retrieval.
…This new approach allows us to leverage the highly-optimized MIPS algorithms to retrieve an initial set of candidates that can then be re-ranked with the exact multi-vector similarity, thereby enabling efficient multi-vector retrieval without sacrificing accuracy.”
Multi-vector models can provide more accurate answers than dual-encoder models but this accuracy comes at the cost of intensive compute demands. MUVERA solves the complexity issues of multi-vector models, thereby creating a way to achieve greater accuracy of multi-vector approaches without the the high computing demands.
What Does This Mean For SEO?
MUVERA shows how modern search ranking increasingly depends on similarity judgments rather than old-fashioned keyword signals that SEO tools and SEOs are often focused on. SEOs and publishers may wish to shift their attention from exact phrase matching toward aligning with the overall context and intent of the query. For example, when someone searches for “corduroy jackets men’s medium,” a system using MUVERA-like retrieval is more likely to rank pages that actually offer those products, not pages that simply mention “corduroy jackets” and include the word “medium” in an attempt to match the query.
YouTube is rolling out two AI-driven features designed to enhance content discovery and deepen user engagement.
The experimental tools include an AI-powered search results carousel for Premium users and a conversational AI assistant now expanding to some non-Premium accounts in the U.S.
AI Search Results Carousel (Premium Only)
Premium subscribers in the U.S. can now access an AI-generated search results carousel for select query types.
The carousel surfaces curated video suggestions along with brief topic descriptions, helping users explore subjects more efficiently.
For example, searching for “best noise canceling headphones” might trigger a carousel like the one you see below:
Screenshot from: YouTube, June 2025.
This experimental feature:
Supports English-language videos
Focuses on shopping, travel, and local activities
Is available on iOS and Android
Will run through July 30
Conversational AI Assistant Expands
YouTube’s conversational AI tool, previously available only to Premium users, is now being tested with select non-Premium accounts in the U.S.
The tool allows users to:
Ask questions about the video they’re watching
Get recommendations
Quiz themselves on key concepts in educational videos
Screenshot from: YouTube, June 2025.
Implications for Creators and Marketers
Videos related to shopping, travel, or local activities may benefit from prominent placement in AI-curated carousels.
The focus on commercially relevant search types aligns with content that often drives conversions, making this a potentially valuable for affiliate marketers and small businesses.
While promising, both tools are being deployed with restrictions. The carousel is exclusive to Premium members and only supports a narrow range of queries. The conversational tool remains in limited testing with no timeline for wider release.
These limitations suggest that YouTube is still in the data-gathering phase, evaluating how users interact with AI-generated suggestions and whether these tools improve search satisfaction.
Looking Ahead
As YouTube experiments with AI in discovery and learning, creators should focus on producing content that is topically rich and well-structured, especially in categories such as shopping and travel.
Expect further refinements as YouTube incorporates user feedback ahead of potential broader adoption.
Google is testing a new feature that allows you to customize the Top Stories section in search results by selecting preferred news sources.
Currently available through Search Labs in the U.S. and India, the experiment gives people more influence over which publishers appear in their news-related queries.
How It Works
Those who opt into the experiment will see a new starred icon in the Top Stories carousel. Tapping it opens a menu where you can choose preferred publications.
Articles from selected sources will be more likely to appear in Top Stories when relevant. These entries will be marked with a star icon next to the site name, but they won’t replace Google’s algorithmic selections entirely.
Google may also display a secondary “From your sources” carousel beneath the main Top Stories section.
A Broader Shift Toward Personalization
The Preferred Sources feature builds on Google’s existing personalization tools, including the ability to highlight content users have frequently visited or show updates since their last search.
A “Try without personalization” option remains available at the bottom of search results, maintaining transparency and user control.
What This Means
For publishers, this change could offer increased visibility, especially for those with loyal audiences who choose them as preferred sources.
However, smaller or newer outlets may struggle to compete with established brands if user selections skew toward familiar names.
The experiment highlights the growing importance of brand recognition, direct audience relationships, and consistent content freshness.
Looking Ahead
This initiative is part of Google’s effort to balance algorithmic discovery with user-driven customization.
While it’s still an experiment, the move suggests Google is exploring ways to give users more say in how information surfaces, without fully abandoning its ranking systems.
If rolled out more broadly, the Preferred Sources feature could reshape strategies for publishers and marketers seeking consistent visibility in Google Search.
Google has launched Offerwall, a new feature in Google Ad Manager designed to help publishers diversify their revenue beyond traditional ads.
The tool, now generally available after testing with over 1,000 publishers, allows audiences to choose how they access content, including watching short ads, completing surveys, or making micro payments.
According to Google, early adopters of Offerwall have seen an average revenue increase of 9%
A Response to Changing Publisher Needs
Peentoo Patel, Product Director at Google Ad Manager, says in an announcement:
“For years, our publishing partners have asked for more and different ways to monetize their content beyond traditional ads.”
Offerwall gives audiences more control over how they engage with content, while providing publishers with additional monetization paths.
Key Capabilities of Offerwall
Offerwall includes several features aimed at helping publishers implement flexible monetization strategies:
Multiple Access Options: Audiences can access content by choosing from short ads, micro payments, interest-based surveys, or other publisher-defined methods.
Custom Integrations: Publishers can add their own access models, such as newsletter sign-ups or subscription trials.
Rewarded Ads: A familiar model for users who prefer to watch an ad in exchange for content access.
Survey Access: Completing a survey grants access while providing publishers with valuable audience insights.
Supertab Payment Integration (Beta): Enables single-use payments or subscriptions.
Optimize (AI-Driven Timing): Uses AI to determine the ideal moment to present the Offerwall, aiming to maximize engagement and revenue.
Here’s an example of what you might see on a publisher’s site when they use Offerwall:
Screenshot from: blog.google/products/ads-commerce/offerwall-gives-publishers-more-options-audiences-more-control/, June 2025.
Focus On Small Publishers
Google highlighted Offerwall’s potential benefits for smaller publishers, who may lack the development resources to build custom paywalls or alternative monetization systems.
Offerwall provides these tools with minimal setup, integrated directly into Google Ad Manager.
This could help close the resource gap between large and small media businesses by making diversified monetization models more accessible.
Implementation & Strategy
For publishers already using Google Ad Manager, Offerwall can be integrated with existing workflows.
The tool’s flexibility allows for gradual experimentation. You can start with basic rewarded ads or surveys and expand into micro payments or subscriptions as user behavior data accumulates.
The Optimize feature may also reduce friction in testing by automating decision-making about when to present monetization options.
Looking Ahead
The introduction of Offerwall underscores a broader shift in digital publishing. As privacy regulations evolve and traditional ad models face pressure, publishers are exploring new ways to monetize their content without compromising the user experience.
Marketers working with publisher partners may need to adapt to new engagement patterns and evaluate how Offerwall could affect campaign performance and analytics.
Offerwall is now available to all publishers through Google Ad Manager.
Google’s srsltid parameter, originally meant for product tracking, is now showing on blog pages and homepages, creating confusion among SEO pros.
Per a recent Reddit thread, people are seeing the parameter attached not just to product pages, but also to blog posts, category listings, and homepages.
Google Search Advocate John Mueller responded saying, “it doesn’t cause any problems for search.” However, it may still raise more questions than it answers.
Here’s what you need to know.
What Is the srsltid Parameter Supposed to Do?
The srsltid parameter is part of Merchant Center auto-tagging. It’s designed to help merchants track conversions from organic listings connected to their product feeds.
When enabled, the parameter is appended to URLs shown in search results, allowing for better attribution of downstream behavior.
A post on Google’s Search Central community forum clarifies that these URLs aren’t indexed.
As Product Expert Barry Hunter (not affiliated with Google) explained:
“The URLs with srsltid are NOT really indexed. The param is added dynamically at runtime. That’s why they don’t show as indexed in Search Console… but they may appear in search results.”
While it’s true the URLs aren’t indexed, they’re showing up in indexed pages reported by third-party tools.
Why SEO Pros Are Confused
Despite Google’s assurances, the real-world impact of srsltid is causing confusion for these reasons:
Inflated URL counts: Tools often treat URLs with unique parameters as separate pages. This inflates site page counts and can obscure crawl reports or site audits.
Data fragmentation: Without filtering, analytics platforms like GA4 split traffic between canonical and parameterized URLs, making it harder to measure performance accurately.
Loss of visibility in Search Console: As documented in a study by Oncrawl, sites saw clicks and impressions for srsltid URLs drop to zero around September, even though those pages still appeared in search results.
Unexpected reach: The parameter is appearing on pages beyond product listings, including static pages, blogs, and category hubs.
Oncrawl’s analysis also found that Googlebot crawled 0.14% of pages with the srsltid parameter, suggesting minimal crawling impact.
Can Anything Be Done?
Google hasn’t indicated any rollback or revision to how srsltid works in organic results. But you do have a few options depending on how you’re affected.
Option 1: Disable Auto-Tagging
You can turn off Merchant Center auto-tagging by navigating to Tools and settings > Conversion settings > Automatic tagging. Switching to UTM parameters can provide greater control over traffic attribution.
Option 2: Keep Auto-Tagging, Filter Accordingly
If you need to keep auto-tagging active:
Ensure all affected pages have correct canonical tags.
Configure caching systems to ignore srsltid as a cache key.
Update your analytics filters to exclude or consolidate srsltid traffic.
Blocking the parameter in robots.txt won’t prevent the URLs from appearing in search results, as they’re added dynamically and not crawled directly.
What This Means
The srsltid parameter may not affect rankings, but its indirect impact on analytics and reporting is being felt.
When performance reporting shifts without explanation, SEO pros need to provide answers. Understanding how srsltid functions work, and how it doesn’t, helps mitigate confusion.
Staying informed, filtering correctly, and communicating with stakeholders are the best options for navigating this issue.
Jill Whalen, a true SEO pioneer, recently passed away. Although she has been retired for over ten years, her influence continues in the marketing-first SEO practices she advocated that are gradually gaining ground thirty years after she first championed that approach to ranking websites.
Contributions To SEO
As part of the first wave of SEO, her contribution to search marketing was to prove that a marketing-first approach was sustainable as a long-term strategy. While that style of SEO is described as white hat, that term has lost meaning as many of the SEOs with the biggest and whitest hats tended to be algorithm chasers jumping from strategy to strategy, something Whalen was not.
Many of the second-wave SEOs from my generation focused on testing the limits of search engine algorithms and reading research papers to better understand how search engines worked. Whalen remained steadily focused on creating the kind of content search engines were trying to rank and used responsible link building to promote it, which turned out to be a winning strategy.
Screenshot Of Jill Whalen On SEO Pioneers Show
Left to right: Jill Whalen, Shelley Walsh
Her approach may have felt old-fashioned to some in the industry at the time, but she recently observed in an interview on Shelley Walsh’s SEO Pioneers show that she felt vindicated after Google’s Panda and Penguin algorithms, which rocked the search marketing industry but left her clients’ top-ranked websites untouched. Indeed, the entire SEO industry is coming around to Jill’s approach to SEO.
Whalen retired in 2013 and turned her attention to subjects that mattered to her, but her influence has always been felt through the thousands of SEOs who learned from her and who continue to pass those traditions on.
How Jill Whalen Influenced Top SEOs
Christine Churchill
Christine Churchill (LinkedIn profile), a leading search marketer, explains how she met Jill Whalen and how she influenced her life and career.
“Wow, this loss really stings! I first met Jill at a speakers’ gathering that I almost skipped because I was dreading feeling out of place. I told myself to just go for five minutes, and when I walked in, I spotted Jill right away – the only other woman there. She flashed me a warm smile, and I found my way over to the bar where she was sitting. I was so nervous, but I was completely taken aback when she mentioned she had seen me speak at an earlier conference and actually knew who I was!
We ended up chatting until the bar closed, and from that night on, we bonded instantly. Jill had this incredible gift of helping us believe in ourselves and encouraging us to shine. Because of her, I also met amazing people like Debra Mastaler, Scottie Claibourne, Karon Thackston, Kim Krause Berg and so many more kindred spirits. We all became friendly faces in the crowd, supporting each other in countless ways.
Jill truly changed my life, and I got to travel the world alongside her! Even when she retired and we didn’t see each other as much, I always knew that if I needed a friend, she’d be just a call away.
I still remember that one conference (I think it was in Pennsylvania) where we met this fascinating guy who talked to ghosts. We ended up staying at the bar yet again, discussing spirits and the signs our departed loved ones send us. It feels like Jill is with all of us now, saying goodbye and cheering us on to keep blooming.
Thank you, Jill, for your incredible friendship and support. I’ll cherish my memories of you forever!”
Debra Mastaler
My good friend Debra Mastaler (LinkedIn profile) was one of Whalen’s early collaborators, handling link building. Debra shares how Jill was instrumental in shaping her career in SEO:
“I’ve been involved with the SEO industry since 1999, I started by owning a directory of organic food and clothing. When I started to rank well for a large number of money terms, business owners advertising in my directory asked if I could I help them “optimize” their sites. I had no clue what that meant so I started looking around for information and met Jill.
Jill took the time to explain what I was doing was called link building and how important it was. One thing led to another and she hired me to do all her link work and got me on the speaking circuit. About a year later, I felt confident enough to work on my own and I launched Alliance-Link.
Over the years, we traveled together, went to conferences, ran an SEO forum, published content together, shared family vacations and spoke almost every day. We drifted after she left the SEO industry but her mark on my life has never faded.”
Left to right: Debra Mastaler, Christine Churchill, Jill Whalen
Michael Bonfils
Multilingual International SEO Michael Bonfils (LinkedIn profile), also an SEO pioneer himself, nce before SEO described who she was and how she influenced him.
“Twenty five years ago while attending one of the first SES (Search Engine Strategies) conferences in San Francisco, I noticed this incredibly enthusiastic lady who was leading a roundtable discussion about content. There were three things that struck me that I never forget.
First, she was one of the few women in a sea of nerdy dudes but as nerdy as she was, she fit perfectly in with everyone else.
Second, she was nervous about speaking, she didn’t say it, but I can see it. I could feel it. It made me happy to know that I wasn’t alone and it was that nervousness that drew me to be one of the first few that sat around her roundtable.
Third, she explained the power of content in SEO better than anyone else. While everyone was focused on tricking the search engines, she was focused on feeding the search engines exactly what they wanted (I was working for a search engine at the time, so this was important for me to hear.)
From the beginning of her career, I’ve had so much respect for Jill that her and I over the decades would often talk about the good old days when everyone and everything in SEO was so uncertain. When she retired, I told her how bummed I was and then I of course accused her of faking it.
I am really going to miss Jill and just broken hearted to learn of her passing. She was truly a legend.”
Duane Forrester
Duane Forrester (LinkedIn profile, formerly of Bing) described how Jill Whalen helped him understand how to explain complex ideas in ways that were understandable to a wide audience.
“Yeah, safe to say that Jill influenced my sense of direction. I mean, I knew it was about working for/with the algorithms, but there had to be a balance. Not just in terms of the work, but how we explained it. Jill helped set me, personally, on a path of trying to explain the complex in ways that everyday business people could understand and adapt to.
Jill was adept at looking through the complex and finding ways forward that not only worked, but were approachable by a wide variety of people with various skills and skill levels. She had a sharp mind and managed to recall volumes of relevant information seemingly effortlessly.
It was always a highlight of any conference to cross paths with Jill. We lost a treasure and I, and I’m sure many, will miss her.”
Bill Hartzer
Bill Hartzer (LinkedIn profile), one of the sharpest technical SEOs I know, remembered her as a centering voice, one who brought balance back to SEO.
He shared:
“She definitely was an influence, as she was more the “voice of reason” so to speak, when I was always trying to test the limits, test that “fine line” between white hat SEO and gray hat SEO.
She consistently advocated for doing SEO “the right way,” which is with integrity, transparency, and a focus on long-term value. Her work through High Rankings became a trusted symbol of ethical search marketing, long before it became the norm.”
Brett Tabke
Brett Tabke (LinkedIn profile), one of the leading founders of modern SEO, remembered her as a positive influence.
“She was always so nice. Had a smile on her face 90% of the time you were with her. I can’t remember a time when she didn’t appear happy to be with her friends. Even when she was presenting, she always made you feel good about what we were doing.”
Watch The SEO Pioneers Interview With Jill Whalen
Featured Image/Screenshot from SEO Pioneers interview
OpenAI CEO Sam Altman says ChatGPT has moved beyond being a Google alternative. Instead, the platform is increasingly focused on helping users complete complex tasks and workflows.
“For a long time ChatGPT was like a Google replacement… it still felt like a more advanced version of search.”
Now, he said, users can ask the AI to perform complex work like a junior employee.
“You can really give a task to code interpreter for example or to deep research… and come back to you with like a proposal.”
This shift signals a new direction for ChatGPT that could affect how businesses and marketers use AI.
Not Just Search Anymore
Altman emphasized that ChatGPT is no longer just about retrieving information. The goal now is to help users get work done.
Altman said:
“It’s like a very junior employee that can work on something for like a short period of time.”
While the platform gets considerable traffic, Altman said ChatGPT.com is now the fifth most visited site in the world, he downplayed the idea that it’s competing with Google Search.
Instead, OpenAI is building a tool that can connect to user data, complete tasks, and act proactively.
Memory & Persistent AI Assistants
A step toward this vision is ChatGPT’s memory feature. Altman called it his favorite feature so far this year.
This lets the AI remember previous conversations and user preferences, acting more like a personal assistant than a chatbot.
“I think memory is the first time where people can sort of see that coming.”
Altman described a future where the assistant knows when to notify users and when to take action automatically.
Reasoning & Workflow Automation
New models like GPT-4o and O3 are designed to handle more complex reasoning and workflows.
“Right now we’re in an interesting time where the product overhang relative to what the models are capable of is here…”
Altman said the technology is moving faster than most businesses can adapt to it. He sees untapped potential in how AI could support work like marketing, data analysis, and content development.
Balancing the Vision
While Altman outlined an ambitious vision, there’s reason to be cautious.
Tools like ChatGPT face limitations like hallucinated outputs, lack of persistent memory across all contexts, and occasional reasoning failures. This is all detailed in OpenAI’s own reports.
That means, even with tools like Code Interpreter or GPT-4o, complex tasks still require hands-on oversight.
The shift away from search competition may also reflect the difficulty of challenging Google’s market dominance. Instead, OpenAI may be trying to define a new space for AI-powered task automation.
Looking Ahead
As AI tools like ChatGPT gain new features, they may change how marketers, developers, and everyday users complete tasks.
However, much of this vision depends on overcoming current limitations and delivering reliable performance across different use cases.
Altman shared that ChatGPT will soon support the Model Context Protocol (MCP). This allows it to pull data directly from tools and platforms businesses already use.
These integrations further support ChatGPT’s positioning as an assistant platform rather than a search engine alternative.
For now, marketers should focus on utilizing AI tools alongside, not instead of, traditional platforms like search engines. The two can serve different purposes in the same strategy.
Listen to the full interview with Sam Altman below:
