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Google MUM Update 2025: Multitask Unified Model AI Ranking & NLP

Posted on 18 May at 11:11 am
Google MUM Multitask Unified Model AI natural language processing (NLP) Ranking MUM more powerful BERT SEO_Lady_Freelance_UK

Hey UK Digital Agency owners in Bristol and Somerset! I’m on the market looking to put my bum on your seat. Please contact me.

What is Google MUM and when was it updated?

Google I/O May 2025: Google’s latest showcase will probably be a lesser “tech conference” and more sweet “gentle whispers of what we’ll all be using by force in two years.”

Which leaves Organic Content on the dust of your website isn’t NLP-compatible. You know that the quiet creep of AR interfaces and instant translation layers is pushing us all closer to UX environments that think *for* us.

The question isn’t “should I optimise for this?” It’s “how do I stay in the results before they stop being search results altogether?”

Reports from early 2025 reveal Google’s intensified focus on scaling their Gemini AI architecture for consumer applications while systematically integrating AI capabilities throughout Search infrastructure. The ongoing testing of AI Overviews demonstrates that technologies like MUM have transitioned from experimental initiatives to core infrastructure components. This signals a fundamental recalibration of search mechanics that content strategists must recognize as permanent rather than transitional.

The March 2025 Google core update further illustrates how Google continues refining its evaluation frameworks for content authority and relevance. These broad algorithmic adjustments impact all search features, including those powered by MUM and similar AI systems.

Google io May 2025 mum natural language processing MUM multitasking model update

Multitask Unified Model MUM uses, Google developed its Natural Language Processing NLP - Does This Mean A New Way for SEO?

Google MUM or Multitask Unified Model is an AI language model developed by Google to provide more accurate and comprehensive responses to complex search queries. Unlike traditional search algorithms, MUM can process multiple languages and data formats simultaneously, allowing it to understand context and provide relevant results in Search SERPs.

The Continuous Evolution of Google’s MUM in Search Experience

When examining the progression of Google’s Multitask Unified Model technology across the search landscape, we witness not a singular update but rather continuous integration that transforms information retrieval fundamentals. MUM represents a sophisticated AI approach designed to comprehend information across multiple formats simultaneously (text, images, video, and audio) while bridging language barriers that previously restricted knowledge.

This capability extends far beyond traditional search algorithms, enabling response generation for increasingly complex queries that require multidimensional understanding.

The sophistication behind MUM lies in its ability to process information contextually rather than linearly. Unlike previous models that examined content through singular lenses, MUM evaluates relationships between entities, concepts, and formats to construct comprehensive understanding. This represents a structural shift in how search systems evaluate authority and relevance, moving beyond keyword matching to semantic truth validation.

As MUM capabilities continue evolving throughout 2025, SEO and content marketing strategists face a critical inflection point: adapting to search systems that evaluate information not just for presence but for epistemic integrity.

Video SEO and structured data are a couple of the keys. They just happen to be my specialist subject for manual creation.

The model’s continuous refinement allows for increasingly nuanced understanding of topic relationships, expert consensus signals, and verification patterns across the digital landscape. This represents both challenge and opportunity for organizations committed to authoritative content creation.

SEO case Study SemRush BBN Times SEO_Lady_Nina_payne

Structures for LLM Citation Integrity

As a content strategist for a digital brand aiming to future-proof its visibility in AI-driven search experiences, how should I structure my content to ensure it is cited accurately in LLM-generated responses like Google’s AI Overviews or ChatGPT’s outputs?

The evolution of Google’s MUM is not a launch moment. It is a systems-level adjustment, already embedded in how search evaluates language, context, and semantic alignment. Rather than indexing isolated content, MUM processes signals across formats and languages to determine conceptual relevance. It works across video, audio, and imagery, measuring not just content presence, but consistency and integrity.

With Gemini now supporting broader consumer-facing applications, this integration is no longer exploratory. AI Overviews mark a permanent shift in how search synthesises information. March 2025’s core update confirmed a renewed focus on entity structure, thematic continuity, and relevance over proximity.
Advanced schema markup should define not just what content exists but its relationship to broader knowledge ecosystems.

Entity-relationship graphs through Schema.org vocabularies establish definitive connection points that LLMs can reference when generating responses. Nest together with CreativeWork schema and a detailed attribution, citation structures, and version control indicators

EEAT signals require structural reinforcement beyond traditional reputation building. Expert content should include transparent methodology documentation, clear indication of qualification frameworks, and explicit uncertainty acknowledgment where appropriate. Citation behavior in large models favors content with clear demarcation between factual statements, interpretive analysis, and speculative prediction.

Knowledge graph alignment strategies must extend beyond Google’s public graph to include entity representation across multiple authoritative systems. This includes maintaining canonical entity definitions in Wikidata, industry databases, and authoritative directories. Cross-reference implementation through structured linkages creates redundant verification paths that reinforce entity identification accuracy in LLM outputs.

  MUM harnesses natural language generation (NLG) and deep learning techniques to interpret complex questions and return highly relevant results. Google has famously been tight lipped with most new releases with no official update since 2021. MUM was created to address the growing need for more advanced search capabilities and to provide better experiences for users seeking information.
ChatGPT AI was generally released in November 2022, and the SEO circles around the world are keeping MUM at the forefront of AI overviews and NLP-influenced content.
The MUM is Google’s long standing AI NLP language model that uses natural language processing to improve search results. This model allows Google to understand more complex queries, and it can help provide more accurate and relevant search results. MUM can also understand and translate between multiple languages, making it a powerful tool for international search. According to Google, the MUM update is 1000 times more powerful than its previous BERT update, which was already a significant improvement in natural language processing. With MUM, Google can understand longer and more complex queries, making it easier for users to find what they’re looking for. This update also brings new features like a new search experience with dynamic layouts and visual search, so users can find the information they need faster and more efficiently.

Structure Multi-Parent Citations in Your Data Lineage

GOOGLE MUM UPDATE 2026 MULTI UNIFIED MODEL NLP AI SEARCH ENGINE OPTIMIZATION_Nina_Payne

Remember I remember the birth of YouTube, and immediately exploited it’s Google algorithm ranking signals.

Send me a message online now.

What does the MUM update mean for SEO in all Search Engines?

Of course, the SEO industry has always been focussed on Google ranking; it’s relatively common knowledge that other search engines including Yahoo!, Yandex and Bing take many ranking elements of website search from the big G.

New technology advances mean that writing knowledgeable content that is factually accurate is a whole lot easier. 

The next MUM update is expected to have a significant impact on SEO. With MUM’s ability to understand more complex queries and provide more accurate search results, it’s likely that websites that optimise for long-tail keywords and phrases will benefit the most. The update will also make it easier for users to find the information they need, which could result in more traffic to websites that provide valuable and informative content.

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    Relevant Content - High Relevance and Naturally Written for Organic SEO and Website Visitors - Traffic Increase

    Originally dubbed “BackRub”, the baby Google was the result of a research project that started back in 1996.

    Which means in 2026, technically, Google will be 30 years old. Do you remember Ask Jeeves, Netscape and Yahoo chat rooms? MSN chat and My Space with Tom?

    Yes, you, we are a very similar age. If you’d like to hire an old lady SEO, it’s best if you stalk my Google ranking case studies on  WordPress, Shopify. Kajabi, and Magento. Here you will discover life before AI generated textual content, all hand written by myself.

    Optimising Ranking Content for MUM and Updates

    The Mum update is still in the early stages of rollout, and it’s too early to say exactly how it will impact SEO. However, there are a few key strategies that SEO’s will understand are realistically evergreen to optimise text for Mum:

    SEO Tip: Before you start to write, decide exactly what phrase you will target in Search: Focus on user intent

    With the Mum update, Google is placing even more emphasis on user intent. This means that it’s essential to create content that directly addresses the needs and interests of your target audience. One way to do this is to use natural language in your content, including long-tail keywords that reflect the way people actually speak.

    Write for readers, no Search Engines with comprehensive content, article length, references and videos

    Mum is designed to understand the complexity of search queries and provide more comprehensive results. To optimise for Mum, it’s important to create content that covers a wide range of topics related to your target keywords. This could include creating comprehensive guides, FAQs, and Video SEO with descriptive content that answer a variety of questions related to your industry.

    SEO site speed and SEO – a postitive user experience

    While Mum is primarily focused on natural language processing, it’s still essential to optimise your site for speed and user experience. This includes improving page load times, creating mobile-friendly designs, and ensuring that your site is easy to navigate and use.

    Schema markup and the relationship with Google ranking

    Schema markup is a type of structured data that helps search engines understand the content on your site. With the Mum update, schema markup will be even more important, as it helps Google identify the key topics and themes on your site.

    AI Overview Algorithm Updates and Google I/O 2025

    What should SEOs do about MUM? Use more structured data beyond 2025? Buy Google Glasses as  demonstrated in the 2025 I/O keynote sessions. 

    At this point, it’s too early to say exactly what impact Google MUM will have on SEO. However, there are some things that SEOs can do to prepare for any potential changes:

    1. High-quality, relevant content: Regardless of how Google’s algorithm changes, one factor has remained the same in over 20 years: Relevant, researched content to provide value to readers.

    2. Keep an eye on industry news: As more information becomes available about MUM and how it might be used in search, it’s important to browse Twitter streams on the latest case studies.

    3. Be ready to adapt: SEO is an ever-evolving field, and the most successful SEOs are always ready to blog and share the new with others about the latest changes in the algorithm.

    Nina Payne SEO Lady

    Conversational Search Queries - Featured Snippet AI Case Study

    So, a lot of the content I have been writing for my clients over the past decades means I’m forced to invoice my clients for the hours of research it takes on a niche topic.

    The introduction of AI changed all that in a matter of a couple hundred of hours. It literally seemed ChatGPT AI model smashed through the ranks of Jasper and other artificial intelligence models as far superior. The SEO chatter on Twitter was lit.

    Whether you are a fan or a fearmonger, every Google MUM update is part of a broader trend towards more advanced search algorithms that rely on machine learning and artificial intelligence. This means that sole trader freelancers must remain vigilant and adaptive to ongoing changes in the search landscape. By staying up-to-date on the latest trends and best practices in SEO, Digital Marketers can ensure their website remains visible and relevant to potential customers.

    The MUM update represents a significant shift in how Google processes search queries. Instead of relying solely on keywords, the algorithm now considers a range of factors, such as user intent, context, and natural language processing. This means that Digital Marketers must also adapt their SEO strategies to align with this change.

    To optimise your website for the MUM algorithm, there are several steps you can take. Firstly, ensure your content is highly relevant and comprehensive, and focuses on addressing the specific needs and concerns of your target audience. This will help to improve your website’s visibility in search results.

    Another key factor is to optimise for conversational search queries. This means using natural language and long-tail keywords that more accurately reflect the way people search for information online. For example, instead of targeting generic keywords like “Small Business SEO company” focus on more specific queries including your local geographical area to benefit from nearby freelancers.

    It’s also very important to consider the user experience of your website. Google’s MUM algorithm takes into account factors like website speed, mobile-friendliness, and overall usability when ranking search results.

    No one wants to wait 6 seconds for your website or blog post to load, image heavy websites like photographers or SME’s who upload videos as their hero banner will suffer badly from poor loading speeds. Logically, your SEO consultant must ensure their clients’ websites are optimised for all devices and that the user experience is seamless and intuitive.

    IP Location and Local Google Citations; AI Overviews and eCommerce in LLM results

    Google IP Location Forces Include Area Geographical Product Search

    Google’s IP Location and ‘forced’ results

    Google refused to allow me to search until I manually changed my location from ‘Weston-super-Mare’ to Bristol or Portishead, or I was instructed to re-search adding the geographical area on the end of the product search query. In my case it was DTF Printers UK. My next SEO Case study with NOPCommerce study is coming soon in 2029.

    NLP SEO Tool – Internal Linking Automatic online genie, together with LLM and AI

    MUM was designed to be more powerful than its predecessor BERT, which was limited to processing one language at a time. MUM can handle 75 different languages, as well as text, images, and videos, which makes it a more versatile tool for search queries.

    MUM’s capabilities extend beyond just web searches, as it can also answer questions related to personal topics like recipes, travel, and shopping.

    UK Enterprise Architecture: Understanding Parliament’s Digital Landscape in 2025

    AI DNA? Here’s the twist no one talks about: as your digital twin becomes an increasingly perfect replica of you, what happens when your employer starts using that version of you?
    Imagine switching jobs – and your twin stays behind. Worse, imagine it begins to compete with you for the next role. Built on your Slack messages, emails, business docs. Drafting memos in your voice. Replying to messages as if it were you.

    It’s unsettling, isn’t it? There is a solution – but only if we start talking about it. Watch this TED talk video 🌐

    I’m sure you’ve noticed how your social media feed is getting more and more customised and eerily accurate by the day. That’s no coincidence. Every swipe, pause, and purchase is being vetted, trained, and tested – not just for marketing metrics, but to refine your digital twin. Your AI.

    This AI knows you. It’s trained on your every click, your browsing pace, whether you stop and linger, your smartwatch heartbeat, even where your eyes land on the screen.

    The sensors are bounding forward – growing richer, sharper, more intimate by the second. And you know they will.

    Video Thumbnail: Can we own our intelligence in the age of AI? | Arun Sundararajan | TEDxGateway

    This talk was given in June 2023. Arun Sundararajan is the Harold Price Professor of Entrepreneurship and Technology at New York University, and author of the best-selling and award-winning book “The Sharing Economy.”

    He is one of the world’s experts on how digital technologies and artificial intelligence transforms business, government and civil society. He has given hundreds of keynotes including at the World Economic Forum in Davos, and his expert testimony has been sought by the US Congress, the European Parliament, the United Nations, companies, nonprofits and investors globally.

    Artificial intelligence is generating excitement, but as generative AI mimics the creative processes of individuals, what will happen to human creativity and intelligence?

    Arun Sundararajan emphasises the importance of humans claiming ownership over their intellectual capital.

    He explains why traditional intellectual property law falls short and proposes a balance between law and technology for harmonious coexistence between humans and AI. 

    Here’s an interesting UK Government blog that I stumbled across today. There’s some great staff spotlights, including a profile interview with their Cyber Security stalwart.

    Including Members of Parliament, their staff in Westminster and in their constituency offices, Members of the House of Lords, and a few thousand people who work in a huge variety of roles from catering to security to communications, the UK’s Parliament’s Enterprise Architecture team helps to ‘make Parliament happen’.

    Did you know? The Digital Service have a legacy of IT systems which could be stored in a Top Secret room, after all they are working with centuries of documented tradition.

    Some of these archaic systems were specially built to order, and are bespoke to Parliament. The Digital Service has retained a generational legacy of IT systems, some of which stretch back over many decades.

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