Feb 24, 2025
Over the last six months, Gemini on Pixel received quite a few improvements. Here are six updates we’ve launched and how you can use them.

• Six updates to Gemini on Pixel make it smarter, faster, and more useful.
• New AI models, including Flash, Flash Thinking, and Pro, improve Gemini’s capabilities.
• Multimodal capabilities in Gemini Live let you add images, files, and videos to conversations.
• Deep Research uses Gemini models to search and write reports on complex topics.
• Gemini now answers questions even when your phone is locked and integrates with various apps.

Six months ago, we introduced our first Pixel phones with Gemini built in. Since then, we’ve been busy updating Gemini models and the Gemini app, along with developing new features that make it more useful. Here are six upgrades that launched over the past six months for Gemini:
In December, we introduced experimental versions of our latest family of models, Gemini 2.0. This includes Flash, Flash Thinking and Pro — each of which is for specific use cases. 2.0 Flash can handle your everyday tasks, try 2.0 Flash Thinking when you have questions that require multiple steps and 2.0 Pro is great at coding, math and other complex queries. In January, an updated version of 2.0 Flash launched for all Gemini app users on desktop as well as mobile. All of this means that Gemini now answers your questions faster and is better at answering more complex questions, too.
Plus, the Gemini app now uses our latest Imagen 3 model, delivering significantly brighter, better composed images and more accurate rendering of diverse art styles, from photorealism to anime.
We added multimodal capabilities to Gemini Live in January. Gemini Live (available for Android and iOS phones) lets you have free-flowing conversations with Gemini. Multimodal capabilities in Gemini Live allow you to add images, files and YouTube videos to your conversations to provide more context about what exactly you’re looking for or trying to understand — this means you can do things like take a photo of a plant and have a conversation with Gemini Live about whether it will survive in your yard and when you should plant it, or link to a cooking tutorial video on YouTube and ask Gemini to talk you through how to double the recipe.
Launched in December, Deep Research is our new agentic feature in Gemini Advanced: It uses Gemini models to search dozens of websites and explore complex topics for you and delivers its findings in easy-to-read reports. You can ask Deep Research to compare mortgage rates in different cities or help you decide what car you should buy. The reports include source links and you can always use the chat feature to add more information or edit the report. Recently, we also made Deep Research available on mobile (including Pixel users, of course) in the Gemini app, in addition to it being available for everyone via desktop.
An Assistant can’t be helpful if it isn’t able to answer your questions when you need it, so now Gemini responds to more of your questions in more places. Gemini now answers your queries, even when your phone is locked.
Over the past six months, Gemini broadened its capabilities by integrating a number of new extensions. For example, Gemini’s Google Home extension lets you do things from your Pixel, like ask it to dim your lights or turn on your TV. You can also ask Gemini to call personal contacts or businesses, as well as draft and send messages with your default phone and messaging apps. And with the new Utilities extension, Gemini can even set alarms, control your device settings and open your camera to take a quick selfie. The list of available extensions includes apps like Google Calendar, Google Tasks, Spotify and more — and the list is growing!
At the beginning of this year, Gemini’s overlay on Pixel got a new look: The simple, intuitive layout makes it easy to prompt Gemini whenever you need it. Simply long press the power button or say “Hey Google” to activate it.
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Google told us the June 2025 core update completed early on Thursday, July 17th, but now, four days later, we are still seeing incredibly heated volatility, even through today. The tools and community are still experiencing significant ranking movement and instability, even today.
Is this ranking volatility related to the tail end of the core update, or is this something new Google pushed under the radar after the core update completed? I am not sure.
As a reminder, when the June 2025 core update was announced, we didn’t see much of any volatility. But then we saw volaitlity touch down on July 2nd. Then on July 10th we reported on folks noticing partial recoveries from previous core updates and helpful content updates (again, not everyone). And then, even four days after the core update completed, the volatility was heated throughout and it still as not calmed down.
So what are we seeing? It seems like not only has the volatility remained heated but yesterday, Saturday, something bigger happened.

Google Tracking Post June 2025 Core Update

You will see that many of the tools have not calmed down much since after July 17th – here are those charts:
Semrush:

SimilarWeb:

Wincher:

Advanced Web Rankings:

Mozcast:

Cognitive SEO:

Accuranker:

Mangools:

Data For SEO:

SERPstat:

Sistrix:

Algoroo:

Wiredboard’s Aggregator of Tools – this report shows the aggregate of the tools above and plots them on one chart:

SEO Chatter Post June 2025 Core Update

The chatter is pretty heated also over the past few days (after the core update completed) – here are some comments from this site and from WebmasterWorld:

Today’s traffic is butchered ! don’t know if it’s an analytics bug or real drop…

Yeah, traffic drop over here too. Didn’t last long, did it.. Would love to think its an analytics bug but I’m more inclined to think its an actual drop. Considering how things usually go these days.

They have published more aio, and the increasing keywords today seem to have stabilized, this is for the few sites I follow. A small increase that will now collapse again. It seems to be on top of a roller coaster, now after the climb (so to speak), there is the descent

After a much-improved traffic week midnight Saturday UK time came and the traffic immediately died. After 12 hours I’m at 15% of this last week’s average … Is my update boost over and done with?

Google is likely still testing, so fluctuations are part of the shakeout. Let’s watch a few more days.
I was hoping the uplift would continue. Could just be part of the post-update reshuffle; I’d give it several days before calling it permanent. What are your impressions looking like in GSC?

I am still seeing a lot of changes to the ranking of my pages and blog posts.
One day, they can be found and the next day, they disappear from the SERP.
As usual, there’s nothing we can do. Just got to wait for the effects of the core update to settle down and see how they affect my site.

Same, one day I see website in Discover, next day – nothing. Same in Search.

Update still not completed. Now is total mix, index issues. All search, Discover and News is destroyed.

Yeah, I swear the update is still going on. Just seeing everything like crap today. and yesterday.

During the entire 16 days of the update, our traffic was recovering. Then, on the very day the update’s end was announced, our site lost all traffic. What’s the logic?

Is this update done? Is this some sort of new update? What is going on?
Forum discussion at WebmasterWorld.
The content at the Search Engine Roundtable are the sole opinion of the authors and in no way reflect views of RustyBrick ®, Inc
Copyright © 1994-2025 RustyBrick ®, Inc. Web Development All Rights Reserved.
This work by Search Engine Roundtable is licensed under a Creative Commons Attribution 3.0 United States License. Creative Commons License and YouTube videos under YouTube’s ToS.

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We believe in change driven by technology and innovation.
Join our team of experts to make a difference in the real world.
Learn about Appinventiv’s product lifecycle development process.
Meet the brains behind our smooth running and powerful machine.
that deploy customized solutions in a wide range of industries
Our software development services are built to evolve your business idea into a successful growth story
A leading digital platform to offer engaging shopping experience to users
A transforming ERP Solution for the world’s largest furniture retailer
A mobile app to digitalize & expand KFC’s digital footprint
A refined UX strategy for Domino’s to increase their conversion rate by 23%
The MIT Innovation award-winning app with $52 Million funding reshaping the employment landscape
A SaaS-based financial literacy and smart money management platform for kids
to steadfast success for top globally leading brands
Artificial Intelligence has emerged as a transformative force in the 21st century, revolutionizing every aspect of our daily lives. Its most pronounced influence can be observed in the social media ecosystem, which has become the central online communication and connectivity stage.
AI in social media now stands as a powerful driving force, reshaping the dynamics of our online interactions. It influences everything from automated content moderation and tailored content recommendations to the advertisements that flood our feeds.
According to Backlinko, social media leaders leveraging AI in social media marketing strategies and personalized recommendations are increasingly influencing 82% of the population in Europe and North America.
However, integrating AI in social media platforms is a strategic move that can revolutionize how companies engage with their audience and the market.
The AI in Social Media Market, projected to grow from USD 2.69 billion in 2025 to USD 9.25 billion by 2030 at a CAGR of 28.04%, presents significant business opportunities across various sectors. (Source: Mordor Intelligence)

This blog will help you understand everything related to AI in social media and how this technology can transform how we engage and interact in the digital age. We will also explore real-life examples of how social media organizations leverage AI to achieve maximum ROI and explore this ecosystem’s current and future trends. So, without further ado, let’s dive right into the details.
Businesses harness the power of AI algorithms and machine learning models to enhance various aspects of social media, such as user engagement, content creation, and data interpretation. Using AI for social media marketing mainly enhances user interactions, simplifies marketing operations, and empowers informed, data-backed decision-making. Social media and Artificial Intelligence together make the social media experience more personalized, efficient, and engaging for users and businesses:
AI algorithms can analyze user behavior and preferences to deliver tailored content and recommendations. This helps users discover new and interesting content and connect with people and businesses they are most likely interested in.
AI can also help businesses to automate and streamline their marketing efforts. For example, AI-powered tools can help to identify and target ideal customers, create personalized ad campaigns, and measure the ROI of marketing campaigns.
The combination of personalization, efficiency, and informed decision-making is the driving force behind AI’s transformative impact on social media. It has become the defining characteristic of AI social media marketing, bringing in an era of smarter and more engaging online experiences.
As per artsmart.ai, businesses that have integrated AI into their social media strategies have reported substantial improvements, with engagement rates rising by 15 to 25%, contributing to higher revenues.
According to artsmart.ai, as of 2024, there are 5.17 billion global social media users, representing 63.7% of the world’s population. This vast audience is increasingly being served with AI-powered content recommendations, with over 80% of these suggestions generated by artificial intelligence. This technology significantly enhances user retention rates.
Given these reasons, social media businesses that have not yet started leveraging AI should consider it imperative to adopt these technologies now. This strategic move is crucial to capitalize on the growing market and enhance their competitive edge.
AI has a significant influence on the landscape of social media. It can simply help in enhancing personalization, efficiency, and content relevance. There are multiple applications of AI in social media that help enrich user experiences and streamline operations. Let us look at the multiple applications to understand the impact of artificial intelligence on social media:
AI analyzes the sentiment of social media posts and comments. This helps businesses understand the general mood and emotions behind content and also assists in monitoring customer feedback and reactions.
Twitter employs sentiment analysis algorithms to determine the emotional tone of users’ tweets. This helps businesses understand people’s feelings about specific topics or brands, allowing for real-time insights into public opinion and sentiment trends.
In 2012, Twitter launched Twindex, a service that deploys sentiment analysis algorithms. It tracks how voters feel and the daily shifts in opinion about presidential candidates. This move showed Twitter getting serious about big data, using massive data analysis to predict politics.
AI-powered chatbots provide users with real-time support and information. They can answer questions, guide users to relevant content, and enhance customer engagement.
Facebook Messenger’s AI chatbots boost customer service by quickly responding to inquiries, fostering engagement, and enhancing user experiences. This keeps users active and increases their time on the platform.

Meta AI is a smart assistant integrated into Messenger that answers users’ questions within chats. It recommends movies, restaurants, and other options based on user preferences. Additionally, Meta AI offers creative support by generating images and ideas on demand.
AI is utilized to identify emerging trends and topics among multiple social media conversations. This empowers companies to create content that resonates with their target audience’s interests and conversations.
Twitter uses AI to track trending hashtags and topics, enabling businesses to align their content with popular discussions. Its AI agents automate the monitoring and analysis of Twitter data and deploy NLP and sentiment analysis to assess tweet volume, engagement metrics, and user interactions to determine trending content.​
AI algorithms can predict user behavior by analyzing their past interactions and preferences. This empowers businesses to offer highly personalized content and recommendations, fostering stronger customer engagement and satisfaction.
Facebook uses AI to predict user behavior by analyzing past interactions and preferences, and personalizes experiences across its platforms:
AI-driven speech recognition technology increasingly integrates into social media platforms, enabling voice commands and transcription services for various purposes. This allows features like dictating messages, searching content, or transcribing audio/video for captions, enhancing accessibility and convenience for diverse user needs.
Vyrb, developed by Appinventiv for Innovative Eyewear, is an innovative social media platform optimized for Bluetooth wearables, particularly glasses. It enables users to send and receive audio messages and create voice-based posts for platforms like Twitter and Facebook, offering a hands-free, seamless experience.

Features like Integration of voice-command functionality with Siri and Google Assistant, autoplay, and audio manipulation tools drive 50,000+ downloads, indicating significant user adoption.
AI social media marketing tools streamline advertising by analyzing customer data and targeting by creating and delivering tailored ad variations to specific audience segments, maximizing relevance and impact. AI-powered campaign adjustments enhance efficiency, reduce costs, and boost conversion rates, fostering stronger connections between brands and their audiences.
Facebook’s ad platform utilizes AI to optimize ad delivery based on user behavior. It is one of the simplest platforms for analyzing AI’s impact on social media. Here’s an overview of how AI functions:
AI is revolutionizing influencer marketing by automating tricky tasks and providing insights rooted in data to make campaigns more efficient and effective. AI helps pick influencers quicker and ensures they’re more relevant and real. AI makes running campaigns smoother, not just for finding peeps and guessing outcomes. It allows brands to get their influencer marketing game on point, boosts their returns on investment, and helps them make real connections with the folks they want to reach.
AspireIQ uses AI to match brands with influencers whose audience demographics align with the campaign’s target market. Explore how AspireIQ leverages AI to streamline influencer marketing by enhancing discovery, collaboration, and campaign management:
Content moderation is one of the leading applications of AI in social media. AI-driven bots enable businesses to detect, assess, and manage vast amounts of user-generated content in real time. They also scan and filter content for spam, guideline violations, or inappropriate material.
Instagram employs AI to block comments that violate its guidelines. It also relies on AI to check its content and ensure it fits the Community Rules. These smart systems are always on the lookout for posts that break the rules, such as mean comments, unwanted naked pics, and super violent images. Instagram employs AI to identify and mitigate harmful behaviors, such as bullying, by prompting users to reconsider posting potentially offensive comments.

AI in facial recognition and image analysis software recognizes facial structures and identifies users applying overly edited filters, ensuring content quality and authenticity.
TikTok employs AI-based facial recognition and image analysis to identify users who apply excessive and unnatural filters to their videos. It relies on cutting-edge AI tech, such as computer vision and face recognition, to check and tweak facial features in real time. This allows it to apply AI Face, AI Style, and AI Manga filters.
These filters can turn users into different characters or styles, like golden statues or manga figures, by spotting and changing facial traits. This filtering system makes videos look better and gives users lots of creative options to play with.
AI is now capable of generating creative content, including text, images, and videos, tailored to the preferences of specific audiences. It allows companies to write posts, create pictures, and shape messages for different groups of people. Using tools like GPT for writing and DALL·E for images, AI can quickly create top-notch captions, pictures, and even videos. AI doesn’t just create content—it also impacts how well that content performs. It helps marketers make choices based on data by improving and testing different versions.
Pinterest uses AI to create personalized content suggestions that align with user interests based on past interactions. This enhances user engagement and also aids in maintaining a steady stream of relevant content. One cool thing they’ve done is Pinterest Canvas, a system that turns text into images. This helps advertisers make eye-catching backgrounds for their product shots, which makes ads work better. On top of that, Pinterest uses AI to create new stuff to make its platform more inclusive.
AI helps in curating content by sorting through massive amounts of media to find the most relevant, interesting, and valuable content for users. AI algorithms review many media, such as articles, videos, pictures, and posts. They look at what users like, how they act, what’s popular, and how people interact with content.
This helps AI determine and select the most interesting, engaging, and high-quality content for each user or group. Eliminating irrelevant material saves people time and improves their experience by giving them personalized content they’ll find useful.
Flipboard uses AI to analyze user preferences and reading habits to curate a personalized news feed, ensuring that users are more likely to engage with the content on their feed. Flipboard uses AI to improve its content curation. The AI systems on the platform pull out topics from content, eliminate duplicate information, and ensure variety to provide users with relevant and high-quality content.
Also, Flipboard’s own Interest Graph uses AI to show individual content based on how people interact with over 30,000 topics, always changing to fit users’ interests. This use of AI allows Flipboard to give users a custom-made and interesting content experience.
AI technologies are increasingly sophisticated in analyzing images to recognize faces, objects, and emotions, enabling richer interactions and functionalities. These capabilities enhance interactions by powering functionalities such as targeted advertising, accessibility tools (e.g., describing images for visually impaired users), and immersive features like augmented reality filters.
Snapchat extensively leverages AI in its image recognition features to enhance user interaction and engagement. The company utilizes image recognition to apply filters and suggest tags, improving user experiences and engagement through interactive and fun elements. AI-powered computer vision and deep learning algorithms allow Snapchat to identify and examine facial landmarks, objects, and scenes in photos and videos. The technology produces interactive lenses and filters that constantly change according to users’ facial expressions and movements to deliver a dynamic augmented reality experience.
AI and machine learning are crucial in identifying and mitigating fraudulent activities on social media platforms, such as fake accounts and spam. By analyzing patterns and inconsistencies in account behavior, AI can flag potentially fraudulent activity before it affects users.
Platforms like Facebook and Twitter extensively use these systems to maintain the integrity and safety of their user interactions.
AI-driven language translation allows users from different linguistic backgrounds to interact seamlessly. AI eliminates language barriers through instantaneous text and speech translation into preferred languages, enabling smooth interaction and collaboration among online global communities. It ensures effortless engagement among diverse groups to exchange ideas and establish connections without needing language translation or language skills.
Social media platforms like Twitter and Facebook have integrated real-time translation features that will enable posts and comments to be instantly translated, breaking down language barriers and fostering a global conversation. Simply put, AI for social media posts revolutionizes communication by making it universally accessible and connecting people across the globe like never before.
After reviewing the multiple AI examples in social media, let’s examine the benefits it offers businesses worldwide.
“AI is the umbrella term for the algorithms, technologies, and techniques that make machines smart and give marketers superhuman capabilities.”
By Paul Roetzer – Founder, Marketing AI Institute
Artificial intelligence is rapidly transforming the social media landscape. AI algorithms now power various apps that combining AI and social media marketing, offering features and tools to create more personalized, efficient, and engaging content for users and businesses.
Here are some of the key benefits of AI use in social media:

AI can analyze user behavior and preferences to recommend content more likely to interest them. With the rise of artificial intelligence tools, there are tons of social media tools like Sprout Social or HubSpot that can craft personalized content, captions, and posts. This helps your users to discover new and interesting content and save time by avoiding irrelevant content.
AI can help to improve the accuracy and relevance of search results. This makes it easier for your users to find the information they seek quickly while saving precious time.
One of the major benefits of AI use in social media is language translation. AI can translate languages in real-time, making it easier for your users to connect with people worldwide.
AI for social media platforms can be used to detect and remove spam and malware. This helps to create a safer and more secure environment for your users.
AI can be used to identify and remove harmful content from social media platforms, such as hate speech and violence. This helps to create a more positive and inclusive environment for your users.
AI can be used to protect user privacy by encrypting data and developing new technologies that preserve privacy.
AI can be used to analyze user behavior and preferences data to identify and target ideal customers. This helps you to target the right people with the right marketing efforts.
AI can be used to create personalized ad campaigns tailored to individual users’ interests. This helps you to increase the effectiveness of your marketing campaigns.
[Also Read: How Will AI Improve Customer Experience in 2025?]
AI can be used to track and measure the results of marketing campaigns. This data can be used to identify which campaigns are performing well and make necessary adjustments.
AI can analyze data on user engagement to identify the types of content that their target audience is most interested in. It is one of the benefits of AI in social media that helps businesses create and share content more likely to be seen, liked, and shared.
AI-powered chatbots can provide 24/7 customer support, responding to customer inquiries promptly and efficiently. This helps you to improve their customer satisfaction and loyalty.
AI can be used to run social media contests and giveaways more efficiently and effectively. For example, AI can be used to automatically select winners and distribute prizes.
AI social media marketing, combined in a tool can help businesses collect and analyze social media performance data. This data can be used to identify areas for improvement and develop more effective social media strategies. For example, businesses can use social media analytics data to determine which types of content are performing well, which channels drive the most traffic, and which influencers generate the most engagement.
To stay ahead in the dynamic field of AI in social media, understanding both current trends and anticipating future developments is crucial. Here’s an overview of the trends that are shaping the industry in 2025 and beyond:
Let’s delve into the latest trends and what they mean for businesses:

AI-powered chatbots have revolutionized social media customer service by providing instant responses, streamlining inquiries, and offering personalized assistance. Voice bots driven by AI are also gaining popularity, allowing users to engage with the social media channel through voice commands and responses. This trend of AI for social media has prompted businesses to invest in chatbots, enhancing customer engagement and providing 24/7 support.
AR has revolutionized social media, making it interactive and engaging. Businesses are leveraging AR to engage users through interactive advertising campaigns and branded AR experiences. Platforms like Instagram and Snapchat offer AR filters that businesses use to boost brand visibility and increase user engagement.
AI is revolutionizing personalization by delivering hyper-personalized content and recommendations based on user preferences and behavior. This trend highlights the role of artificial intelligence in social media market lookup and presents a unique opportunity for businesses to engage users on a one-to-one level, resulting in increased user satisfaction and loyalty.
The use of generative AI has evolved from basic content creation to generating highly sophisticated and contextually relevant multimedia content, including videos, graphics, and interactive elements. This AI capability enables brands to create engaging and diverse content at scale, tailored to the choices of their target audiences.
AI tools can now analyze social media interactions in real time, providing brands with immediate feedback on the effectiveness of their posts, campaigns, and user engagement strategies. This includes emotional analysis, which can interpret the sentiment behind comments and reactions, allowing brands to adjust their strategy dynamically.
AI’s role in image and video analysis has deepened, with more accurate recognition of objects, scenes, and activities. This technology enhances user experience through smarter content filtering and search capabilities and aids in better ad targeting and content relevance.
As users become more aware of how their data is used, there is a significant push towards ethical AI practices. This includes transparent AI operations where users can understand and control how their data is being used, ensuring their privacy and building trust.
[Also Read: Responsible AI – Addressing Adoption Challenges With Guiding Principles and Strategies]
“The pace of progress in artificial intelligence is incredibly fast. Unless you have direct exposure to groups like DeepMind, you have no idea how fast—it is growing at a pace close to exponential.”
By Elon Musk
Coming to the future of AI in social media, let us understand the futuristic trends in detail below:

AI-powered Social Media Analytics provide social media brands with comprehensive data-driven insights. This enables them to create more effective and precisely targeted marketing campaigns, refine their strategies to align with audience preferences, and optimize their approach to drive higher engagement and user satisfaction.
Deepfake Detection, powered by AI, is crucial in ensuring the authenticity of content shared on social media platforms. By 2025, we can expect 8 million deepfakes shared online, consistently doubling deepfakes every six months. By utilizing advanced artificial intelligence algorithms, this technology can identify and flag manipulated content, such as videos or images, that has been altered to deceive viewers. This capability is of the utmost importance in fostering trust and security within these platforms, as it helps to prevent the spread of misinformation and fraudulent content.
Future social media and AI platforms will likely incorporate emotion AI technologies beyond text analysis, including voice tone and facial expression analysis in videos and live streams. This will allow for a deeper understanding of user sentiments and more seamless audience engagement. According to National Center for Biotechnology Information, sentiment analysis can achieve up to 87% accuracy in classifying social media emotions, so platforms can reliably interpret user sentiments from live streams or videos.
With increasing concerns about data privacy and misinformation, AI in social media will play a critical role in helping these platforms comply with regulatory requirements. AI can automate the monitoring and moderation of content to ensure adherence to legal standards, assisting platforms to avoid hefty fines and reputational damage.
[Also Read: How to Avoid Compliance Violations While Developing AI Products]
Personal AI agents could become the norm for users, assisting them in managing their social media activities. These agents would help curate content, manage privacy settings, and interact with other users, providing a tailored social media experience based on individual preferences and behaviors.
As concerns about concentrated control over AI grow, the future may shift towards decentralized AI models. This approach would allow more stakeholders to participate in the development and management of AI, promoting innovation and reducing biases in AI algorithms.
According to the Global Banking & Finance Review®, in 2025, predictive analytics in social media is expected to increase engagement by 30-40%. AI will analyze user behavior and predict future trends, enabling content creators and marketers to stay ahead of the curve. This predictive capability will allow brands to prepare content that aligns with anticipated changes in user preferences and global trends.
Now that you have a clear answer to the question, ” What is the future of social media with AI?”, let’s examine the step-by-step guide to combining artificial intelligence with social media.
AI integration in social media platforms can bring transformative benefits, but it also presents several problems with AI in social media.  There are a few noticeable challenges that businesses must navigate carefully. Understanding and preparing strategies to overcome these hurdles is crucial for successful AI integration.

One of the primary problems with AI in social media challenges is ensuring the privacy and security of user data, as AI systems often require access to large amounts of sensitive information.
Solution: Implement robust data encryption and access protocols. In addition to this, regularly update security measures to protect against evolving threats.
AI systems can unintentionally learn and increase biases in their training data, leading to unfair outcomes, risks or discrimination.
Solution: Use diverse datasets for training AI models and regularly audit them for bias. Additionally, fairness-enhancing techniques should be employed to ensure AI decisions are equal.
Developing, training, and deploying AI can involve significant costs, especially for custom solutions tailored to specific needs.
Solution: Consider starting with smaller, pilot projects to understand the effectiveness before full-scale implementation.
Integrating AI into existing social media platforms can be technically challenging, requiring significant modifications to the existing architecture.
Solution: Partnering with a reliable social media app development firm with expertise in AI can help manage these complexities effectively, ensuring seamless integration.
The field of AI is rapidly evolving, and keeping the integrated systems up to date with the latest developments can be challenging.
Solution: Hire an external team to monitor and integrate the latest AI technologies and practices continuously.
Users may be skeptical about AI-driven features, especially if they significantly alter the user experience or raise privacy concerns.
Solution: Communicate the benefits of AI features to users and provide them with controls to manage their AI interactions. Furthermore, transparency about how AI uses their data can also help build trust.
AI implementations must comply with various regulations, varying by region and changing over time.
Solution: Regularly review and adapt AI practices to ensure compliance with all relevant laws and regulations, particularly data protection and privacy.
In a world where social media is the most vital entity of digital communication, integrating artificial intelligence in social media marketing strategies is no longer just a choice; it’s a necessity.
Appinventiv is a leading AI development company that can be your strategic partner in harnessing the power of AI to transform your social media app. Whether you are seeking for a new app from the ground up or looking to seamlessly integrate cutting-edge AI-powered features in your existing app, we can be your strategic partner that can help you meet distinct business requirements while ensuring maximum ROI in this dynamic ecosystem.
Our experts can ensure your social media  and AI strategies leverage the latest trends and technologies, keeping you ahead of the competition. By harnessing the full potential of AI for enhanced user engagement, streamlined marketing operations, and data-driven decision-making, our social media app development services can ensure maximum ROI for your social media brand.
Get in touch with us to explore how we can help you leverage AI in the social media industry and transform your business.
Q. What is AI in social media?
A. AI for social media involves the use of artificial intelligence technologies on social networking platforms. Its purpose is to improve user experiences, simplify marketing procedures, and enable data-driven decision-making.

Q. How is AI used in social media marketing?
A. AI in social media marketing paves the way for the automation of content creation, accurate targeting of audiences, and easy performance tracking. It enhances ad campaigns, personalizes user interactions, and analyzes trends for better engagement. Additionally, AI-driven chatbots provide real-time customer support, and predictive analytics help forecast trends and refine strategies for improved results.
Q. How does AI affect social media?
A. AI significantly impacts social media by enhancing how businesses engage with users, manage content, and analyze data. It automates complex processes such as content curation, ad targeting, and customer service through intelligent chatbots, making these tasks more efficient and personalized. AI in social media apps also provides deep insights into user behavior and preferences, enabling businesses to tailor their strategies and content to meet the needs of their audience better.
Q. How do we implement AI in social media?
A. Integrating AI into a social media app can significantly enhance its functionality and user engagement. Here’s a simplified step-by-step guide that can help you effectively understand the process of AI adoption in social media business:
Q. What are the most common AI technologies currently used in social media platforms?
A. Some of the common AI technologies that are utilized on social media platforms are:
Chirag Bhardwaj is a technology specialist with over 10 years of expertise in transformative fields like AI, ML, Blockchain, AR/VR, and the Metaverse. His deep knowledge in crafting scalable enterprise-grade solutions has positioned him as a pivotal leader at Appinventiv, where he directly drives innovation across these key verticals. Chirag’s hands-on experience in developing cutting-edge AI-driven solutions for diverse industries has made him a trusted advisor to C-suite executives, enabling businesses to align their digital transformation efforts with technological advancements and evolving market needs.
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1600+ transformation engineers delivered
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Discover the latest Google Messages updates introducing this month. From Standalone gallery to Material 3 Expressive redesign.
Stay updated with the significant upgrades transforming messaging.
These are Messages features that Alphabet-owned firms have announced or have recently spotted in the wild by beta testers.
MLS encryption and Details page redesign
Universal Profile 3.0 rolls out MLS support for cross-platform encrypted RCS messaging. It allows users to check activation via the new Details page, displaying encryption type: “0” for current, “1” for MLS.
Standalone gallery
With this significant update, Google has addressed an issue regarding the fullscreen camera and gallery redesign launched in June by allowing users access to the latter separately.
Users can launch the ‘plus’ menu for a new “Gallery” grid that takes up the whole display.
Camera opens the existing merged interface. Notably, the shortcut at the end of the text box will not change as the default.
Material 3 Expressive redesign
As per 9to5 Google, Google Messages receives a major update with rounded chat containers, Image grouping, and revamped search, and settings pages reflect Material 3 Expressive design, offering a streamlined user experience.
Sensitive Content Warnings
This safety feature blurs photos “that may contain nudity” with an option to delete them before viewing.
It cautions “users of the risks of sending nude imagery and preventing accidental shares” before they share or forward any nude image.
Users above 18 can optionally enable the option by launching Settings > Protection & Safety > Manage sensitive content warnings.
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Medtech companies are at the forefront of healthcare innovation, developing life-changing devices and solutions to help clinicians diagnose diseases earlier, perform interventions more precisely, and monitor patient health more effectively. Innovations such as minimally invasive surgical robots, AI-powered diagnostic imaging, and connected diabetes management systems have transformed patient care.
As the industry emerges from a period of margin compression and dampened multiples, AI, enhanced by gen AI, can play a critical role in advancing medtech value creation priorities to boost productivity and, ultimately, profitability. McKinsey estimates that medtech companies could capture $14 billion to $55 billion per year in value from productivity gains and add $50 billion or more in annual revenue from product and service innovations.¹McKinsey analysis. Gen AI’s potential is particularly compelling for the medtech sector, given the ubiquity of data-enabled products and numerous critical but repetitive workflows ripe for digital enablement, including regulatory documentation, contract compliance tracking, and customer support.
A fall 2024 survey of 40 medtech executives responsible for gen AI strategy and budgets shows encouraging early adoption trends.²McKinsey medtech leaders survey, November 2024 (n = 40). Roughly two-thirds of respondents say their companies are already implementing gen AI (Exhibit 1). Although about half are still in the pilot phase, nearly 20 percent are scaling their solutions with successful early results. All respondents reported positive qualitative or quantitative improvements from gen AI, with nearly half seeing measurable quantitative and qualitative productivity benefits. Most notably, 15 percent of those implementing gen AI have reported a positive impact on their P&L.
This article explores prominent gen AI use cases where medtech organizations are seeing results and shares a framework that companies can take to successfully scale and generate value from this transformative technology.
According to the results of our survey, gen AI is deployed across several domains, including R&D, commercial, and operations (Exhibit 2). The most promising use cases emerging from these efforts include innovation acceleration (particularly in R&D and product development), process automation (such as content generation for marketing and regulatory compliance), and decision support (including sales enablement and supply chain optimization). Companies seeing the greatest impact are prioritizing use cases that drive meaningful business value through specialized knowledge agents and industry-specific process improvements.
R&D is the most frequently identified medtech domain for gen AI adoption; this group is typically tech-savvy and more willing to explore new tools. Individuals in these groups often use off-the-shelf gen AI tools to search for relevant articles or synthesize research papers.
Tools more customized to the medtech R&D workflows could provide additional impact and help R&D teams streamline processes and get products to market faster. In medtech, R&D teams face numerous documentation requirements throughout the product development life cycle—from clinical study design to regulatory submissions, technical specifications, and product labeling. Without AI, the process of compiling and reviewing trial data takes weeks. Compressing that timeline through AI-assisted drafting of key materials, such as product development documentation or labeling—with a human in the loop to review final submissions—can enhance quality and free up time for higher-value research and innovation and ultimately accelerate the pace to market for critical healthcare products. For example, we have observed medtech organizations that have used AI to help improve their labeling productivity by 20 to 30 percent.³McKinsey analysis.
Gen AI is transforming key commercial workflows in medtech, including marketing, insight generation, and customer interactions: More than half of survey respondents report gen AI deployment across commercial use cases. These workflows have often been a bottleneck for medtech commercial organizations, given their complex portfolios, which have numerous SKUs to manage, and their need to deliver personalized content to healthcare providers from different specialties, procurement teams, and other clinical and nonclinical stakeholders. AI-powered content generation is enabling teams to create personalized marketing collateral at scale, which bolsters the digital marketing required to meet increasing demand in medtech for omnichannel engagement. Using gen AI for insight generation facilitates such tasks as prioritizing accounts, streamlining research, optimizing customer engagement strategies, and predicting key messages that will resonate with different buying personas.
Meanwhile, AI-assisted customer-facing content empowers sales teams by delivering tailored messaging, autogenerated emails, and easily accessible existing collateral. One-third of the medtech companies in our survey are using gen AI to accelerate marketing content creation and medical and legal reviews, while 40 percent are implementing or planning AI-powered customer service solutions to improve the speed and quality of responses from human agents.
Sales teams can benefit from an interactive gen AI tool that is integrated into their existing workflow and corresponding tools, such as a customer relationship management (CRM) or sales dashboard. This can help teams determine where to allocate their time, provide recommendations, and answer specific questions about how to engage stakeholders in their accounts.
The time savings can be reinvested into new business growth and allow sales teams to focus more on strengthening the customer relationship and less on administrative tasks. The most successful AI-assisted tools are tailored to specific roles and their workflows. For example, sales managers get tools for team coaching; key account managers receive insights about executive priorities in their accounts, based on a combination of public and interaction data across the account team; and sales reps receive alerts to changes in account buying patterns with recommendations for relevant marketing collateral. This enables users to make faster decisions, access key resources on the go, and deliver better customer experiences.
Medtech organizations are prioritizing AI solutions in three areas of operations: inventory management, contracting, and procurement negotiations. In inventory management, about 30 percent of survey respondents say they are utilizing AI tools for demand forecasting, disruption monitoring, and field inventory support. The potential for greater adoption and value generation is high, given the prevalence in medtech of inventory management models such as consignment, trunk stock, and loaner units that have led to increasingly complex inventory systems.
Procurement and contracting are being transformed by AI, which can analyze contract terms at scale, identify inconsistencies and flag risks, process data in real time during negotiations with suppliers, and monitor real spending patterns. Among the organizations surveyed, 20 percent are currently using or planning to use AI to scrutinize contract terms and conditions for cost-saving opportunities. Procurement use cases in contracting are also among the quickest to generate P&L impact: AI-powered invoice matching and contract reconciliation have resulted in cost reductions of 1 to 4 percent, while AI-enabled negotiation assistant tools have provided an additional 1 to 4 percent in savings.⁴McKinsey analysis.
The ambitious yet largely decentralized rollout of gen AI across medtech has limited some organizations’ ability to achieve scale and P&L impact. Although 65 percent of respondents to our survey say their companies are already implementing gen AI, many are pursuing a scattered approach, with over two-thirds reporting they are implementing across at least three functions. Further, 59 percent are taking a decentralized, or function-specific, approach (Exhibit 3).
This broad but diffused deployment strategy creates challenges that fall into three categories:
Leading gen AI adopters exhibit the success factors articulated in our rewired framework for AI transformation. Medtech organizations can apply the following factors to accelerate impact and create the conditions for a successful gen AI deployment.
Develop a strategic road map that focuses transformation efforts on one or two domains. Organizations that build solutions within a focused area—whether a specific function, such as regulatory or marketing, or a product suite—are more likely to realize value at scale. With this approach, a single accountable business owner collaborates with the chief information officer and chief technology officer to deliver value and remove roadblocks, allowing the business to implement interconnected use cases and manage change across common teams. For instance, a procurement team might start with invoice reconciliation before advancing to category management tools, or an R&D team could begin automating a few submissions and then expand to automate most other documentation tasks.
Business owners should also focus on use cases that can deliver quick wins, particularly in areas such as procurement, marketing, customer contracting, or regulatory compliance. Domain transformations can then be sequenced to create a transformation road map.
Medtech businesses and functions are often highly autonomous, which sets the stage for fragmented efforts that fail to build scalable platforms. Medtech leaders launching gen AI initiatives should balance creating solutions for an individual business with developing technical foundations that can be leveraged across businesses and use cases. Leaders can establish a gen AI center of excellence, staffed with centralized AI engineering talent, to build solutions on a common data foundation using shared data products and services. This team can support business units, ensuring alignment and reducing silos while preserving necessary functional expertise.
A central digital or IT team can also manage tech partnerships and develop enterprise-level AI capabilities. For example, one organization assigned product-focused use cases to R&D leadership while placing enterprise-level capabilities—such as enterprise-level tool selection and model creation for content generation or analytics—within the center of excellence.
Build with an agile operating model that includes IT and business partnership from day one. Too often, organizations either develop AI solutions without IT input or let IT drive deployment without sufficient business engagement. Early partnership of these functions throughout the journey improves feasibility assessments, accelerates scaling beyond pilots, and addresses critical integration and data privacy challenges. This collaboration also helps identify adjacent domains where solutions can be readily deployed in subsequent transformations.
For most medtech organizations, successful IT and business partnerships will depend on strengthening certain talent pools, including technical skills such as data engineering and data science, machine learning, and prompt engineering. Success also requires a strong product owner in each domain to drive integration. The product owner can coordinate cross-functionally to ensure appropriate risk management (such as ensuring appropriate separation between medical and commercial), safety, and adverse-event reporting.
Expand the IT-and-business partnership to technical and data needs. Too often, data sources in medtech reside within locally maintained spreadsheets or other one-off or manual documentation. Advancing gen AI use cases across domains will require more reusable data products. However, leaders should not let perfection stop early progress; instead, they can do an initial cleanup or mapping effort for the first data domain while establishing a broader data strategy and operating model for the future. Similarly, the first deployments may make some more pragmatic architecture choices while setting the stage for longer-term decisions around tech stack, cloud-based platforms, and software delivery automation, ultimately reducing the total cost of ownership.
Prioritize adoption as much as technical implementation. The success of gen AI deployment depends on how well employees integrate AI into their daily workflows. Embedding AI into existing processes, rather than treating it as an add-on, increases productivity and maximizes return on investment.
To achieve these outcomes, gen AI tools can be built in collaboration with end users and guided by a clear understanding of relevant workflows and a knowledge of the needed support. When possible, the tools should be customized to fit into the group’s existing processes. We have observed that organizations using generic AI tools that aren’t fit-for-purpose typically struggle with low adoption rates. Leading organizations also prepare for launch by investing in structured change management, integrating training into field events, offering incentives, and ensuring transparency on usage and target tracking for business impact.
The moment for medtech companies to act on gen AI is now. Early adopters are already seeing measurable results, because the technology demonstrates clear potential to address long-standing industry challenges that have hampered innovation and operational efficiency. Companies that move decisively but strategically will be best positioned to capture the technology’s full potential. Those that delay or act without planning risk falling behind as gen AI becomes an increasingly critical driver of competitive advantage in the industry.
Delphine Nain Zurkiya is a senior partner in McKinsey’s Boston office, where Julia Samorezov is a partner; Kent Gryskiewicz is a partner in the New Jersey office; and Meredith Langstaff is an associate partner in the Washington, DC, office.
The authors wish to thank Emma McLaughlin and Noelia Lombardo for their contributions to this article.
This article was edited by Jermey Matthews, an editor in the Boston office.

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