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July 3, 2025
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by Shreya Mattoo
If you’re in SEO, you’ve probably felt like Google changes the rules just when you’ve figured them out. One minute it’s BERT; next, it’s MUM—an AI update that doesn’t just tweak search, it redefines it.Launched in 2021, Google MUM strategically consolidated user-centric blocks of content on the main search engine results page to drive quick action and assistance.
To remain relevant to your audiences and get more Google featured snippet features, SEO and content enthusiasts fairly recommend AI content creation software to curate contextual content fast and remain more relevant to swiftly acting audiences. Let’s learn about Google MUM in detail.
Google MUM (Multitask Unified Model) is a multimodal AI developed by Google to improve search by analyzing text, images, and video simultaneously. Announced in May 2021, MUM outperforms BERT by delivering more nuanced, context-rich answers across languages and formats, making search results faster, deeper, and more informative.
MUM isn’t just working behind the scenes; it’s changing how search looks and feels. Google’s aiming to serve up everything you might need (text, video, visuals) in one go, instead of making you click around.
If you ask Google MUM to compare and contrast climbing Mt. Adams and Mt. Fuji, given that you have already trekked Mt. Adams, it not only returns the list of differences or similarities but also adds additional shop links for trek gear and video links.
As an upgraded AI technology, the MUM update improves the functionality of the BERT model. The primary reason for launching MUM was to give users a 360° search experience.
Both BERT and MUM represent major leaps in Google’s understanding of natural language and search intent.
BERT helped Google better understand language. MUM takes that a step further, turning search into a more human, visual, and intuitive experience across formats and languages.
While BERT laid the groundwork for more human-like query understanding, MUM takes it several steps further, making search smarter, more visual, and globally accessible. Preparing your content for MUM means thinking beyond keywords to deliver true, multimodal value.
Google has been continuously evolving its AI backbone by integrating LLM architecture and serverless data warehousing into its search methodology. From 2012 to 2025, the search algorithm underwent significant iterations and innovations to make browsing simpler and more convenient.
In the following years, Google released several updates.
Google MUM is engineered to deliver a more contextual, multimedia-rich, and language-agnostic search experience. Below is a breakdown of how it processes, interprets, and responds to complex user queries:
Based on past personalization attempts with iGoogle interface, MUM bought everything trendy and high-quality under one umbrella so that user doesn’t have to waste time scrolling through content.
For different systems, servers, and data transfers, MUM will work with a certain degree of efficiency. For now, three existing levels have already been implemented using Google MUM:
Did you know? In a matter of seconds, MUM was able to list 800 variations of COVID-19 vaccines in more than 50 languages. After testing the findings, this data was used to deliver high-quality and critical vaccine information to different locations.
Traditionally, the SERP was a flat list of blue links and a featured snippet. However, with Google MUM, the search interface is becoming more dynamic, visual, and intent-driven, designed to help users explore deeper, faster, and with more context.
MUM transforms search from a static results list into an interactive, visually layered experience that prioritizes relevance, context, and exploration over link ranking.
Google MUM (Multitask Unified Model) isn’t just another algorithm update; it’s a foundational shift in how Google interprets, processes, and responds to search queries across languages and content formats.
Here’s what it brings to the table for SEO and digital strategy:
Google MUM rewards content that’s layered, visual, multilingual, and semantically rich. To stay visible, create media-integrated assets that satisfy both user intent and SERP format diversity.
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While MUM brings new opportunities, it also increases complexity, content volatility, and the need for technical SEO excellence.
MUM isn’t Google’s first AI sprint. For years, Google’s CEO, Sundar Pichai, has pushed the envelope of generative AI and its volumes of possibilities. Google aims to inject diversity, equity, and inclusion guidelines within MUM through artificial intelligence.
Google MUM raises the bar. Success now depends on technical readiness, multimedia integration, and delivering value across all content surfaces, not just your domain.
Before, you’d Google 3–4 separate things. Now, Google does the heavy lifting for you in one view.
To help your content align with the demands of MUM, across media formats, languages, and semantic understanding, here’s a tactical checklist, with each item explained for actionable implementation:
To compete with Google MUM, you need to treat each content format as a ranking asset; don’t silo text, images, or video. MUM rewards content ecosystems that meet search intent from multiple angles.
Let’s break down how MUM handles complex, multimodal, and multilingual queries, illustrating its transformative impact on the search experience. Each example shows a before-and-after scenario to clarify how MUM changes the SERP dynamics.
SERPs surface Spanish-language gear guides, Patagonia-specific hiking vlogs, local Reddit threads on winter gear, and infographics showing what to wear.
SERP blends video comparisons, interactive carousels, translated user reviews from photography forums, and zoomable product images.
Unified SERP experience with integrated JR train schedules, bloom forecast data, YouTube route previews, and mapped scenic stops.
MUM isn’t just smarter, it’s more situational. It elevates relevance by blending location, language, media, and user nuance into one cohesive search experience.
MUM can be classified as the next big AI milestone. The traditional way of tackling information and finding the best choice for your needs is being revolutionized. Soon, users will be able to virtualize related topics for the primary query. Finding quality content in one place will reduce their frustration and web consumption time. That’s what the network behind MUM is striving for.
Previous machine learning updates leaned towards stabilizing the search experience, avoiding bugs, and detecting blackhat links and plagiarized content on the web. In a couple of later updates, Google reinforced the “intent” mechanism. Using advanced ML, it mapped the search query language with underlying NLP processors to satisfy user intent and make Google more reliable as an engine.
Earlier AI updates like neural matching, Hummingbird, RankBrain, and BERT were focused on technical SEO and structured data alignment. They gave headroom for organic content and expert-written content. However, with generative AI, the focus shifts to what is best for the user to see, regardless of whether it is organic or sponsored. Google aims to achieve the unimaginable by turning SERP into a distributed social and community network. With this in-depth SEO technique, users will be exposed to recent trends and news in the particular industry they’re looking for.
Google will not only minimize research efforts but also provide a wealth of information with AI.
“AI will impact every product across every company. For example, if you think about 5 to 10 years from now, you are going to have an AI collaborator with you. Let’s say you have a hundred things to go through, it may say, “these are the most serious cases you need to look at first.”
The good news for SEO marketers is that they can continue with their current analysis of how to improve their websites’ Google rankings. People are still debating whether MUM will be a search engine ranking factor or simply a data-dispersing bridge.
To compete with the MUM update, brands need to bolster both organic and earned media strategies. While paid media doesn’t always yield CPCs, organic search and SEO will help brands stay ahead. Even if MUM does affect a fair share of SERPs, the highest-ranking pages and featured snippets will still be preferred.
Brands should start taking their on-page SEO strategies more seriously, not just to rank higher but also to identify their target audience and transfer learnings. Ideating and designing image packs, making introductory videos, and building awareness will help brands weather the MUM thunderstorm.
With MUM, newly sprouted SEO strategies will come into play. Things-to-know sections, video search, visual search, zoom-ins, and voice search will lessen user tedium by giving them all answers in one place. At the same time, it is not a question-answer mechanism. Google aims to create a network of like-minded people to “go smart.”
Google MUM (Multitask Unified Model) is an AI-powered algorithm designed to understand complex search queries across text, images, and video. It uses a multimodal, multilingual model to process information from diverse sources and deliver deeper, more contextual results.
While BERT focused on understanding natural language within text-based queries, MUM takes it further by analyzing multiple formats, like images and videos, and handling over 75 languages. It’s built on a more advanced architecture (T5) to interpret user intent with broader contextual awareness.
As of now, Google has started integrating MUM in specific features like COVID vaccine searches and visual searches via Google Lens. A full rollout is ongoing in phases, with more capabilities expected to appear across search in the coming months.
To align with MUM, focus on multimodal content: integrating videos, images, and well-structured text. Use schema markup, ensure your content is multilingual or localization-ready, and build content clusters that address layered user intent.
Expect more visually rich, interactive SERPs with integrated videos, images, and multilingual sources. Results may include multiple content types per query and deeper topical connections, reducing the need for follow-up searches.
As MUM evolves, so should your content. Think bigger than rankings, think relevance, engagement, and experience. That’s where the next generation of SEO wins. MUM also focuses on adding filters like budget, technical criteria, region, use-case specificity, cross-language, and pricing to give a cohesive search experience and empower quick and reliable decision-making for internet users.
With MUM, Google has made a crucial advance into the AI-powered search browsing landscape. This only paves the way for an even more competitive and future-proof SERP containing real-life visualizations, reviews, demos, and walkthroughs for immersive search experiences.
Learn how you can customize your audience’s needs with web personalization.
This article was originally published in 2023. It has been updated with new information.
Shreya Mattoo is a former Content Marketing Specialist at G2. She completed her Bachelor’s in Computer Applications and is now pursuing Master’s in Strategy and Leadership from Deakin University. She also holds an Advance Diploma in Business Analytics from NSDC. Her expertise lies in developing content around Augmented Reality, Virtual Reality, Artificial intelligence, Machine Learning, Peer Review Code, and Development Software. She wants to spread awareness for self-assist technologies in the tech community. When not working, she is either jamming out to rock music, reading crime fiction, or channeling her inner chef in the kitchen.
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