How AI Is Powering the Next Wave of Social Commerce
How to build a futureproof relationship with AI
AI is transforming social commerce by simplifying how people shop, discover products, and interact with brands. Here's what you need to know:
AI Personalization: Tailors shopping experiences based on user behavior, increasing conversion rates by 15–25%. For example, AI recommendations drive 35% of Amazon's sales.
Live Shopping & Shoppable Videos: AI hosts livestreams 24/7, answers customer questions, and boosts conversion rates by up to 10x compared to traditional e-commerce.
Content Creation: AI automates influencer partnerships and generates user-style videos, cutting time and costs while maintaining engagement.
Backend Improvements: AI predicts demand, manages inventory, and reduces fraud, saving businesses time and money.
AI Impact on Social Commerce: Key Statistics and ROI Metrics
How AI And Social Media Are Enhancing The Shopping Experience | Industry Insights
How AI Personalizes the Shopping Experience
Today's shoppers expect brands to anticipate their needs, and AI is making that expectation a reality. By analyzing customer behavior - like browsing history, purchase habits, and even social media activity - AI adjusts the shopping experience in real time. For example, it considers items added to a cart or specific search queries to create a tailored experience. These advancements are driving a new wave of social commerce across digital platforms.
Here’s why this matters: 91% of consumers prefer brands that offer personalized recommendations, and 80% are more likely to purchase from companies that deliver customized experiences. On the flip side, 76% of shoppers feel frustrated when personalization is missing. In today’s competitive landscape, personalization isn’t just a nice touch - it’s essential.
And it pays off. Companies leveraging AI for personalization often see 15–25% higher conversion rates compared to generic marketing approaches. Look at Amazon: its recommendation engine accounts for nearly 35% of the company’s total sales. Similarly, Netflix credits over 80% of its watched content to AI-driven suggestions. These numbers highlight how personalization directly drives consumer engagement and business growth.
Dynamic Product Recommendations
AI-powered recommendation engines work through two main techniques: collaborative filtering, which analyzes patterns among similar users, and content-based filtering, which matches product features to individual preferences. By using past and current behavior, these systems predict what a customer might want next.
The results are impressive. For instance, Yves Rocher, a cosmetics brand, adopted AI personalization in January 2026 and saw an 11x increase in purchase rates compared to traditional top-seller recommendations. Similarly, HP Tronic, a consumer electronics company in the Czech Republic and Slovakia, personalized website content with AI and boosted conversion rates for new customers by 136%.
Even brick-and-mortar stores are getting smarter. Smart shopping carts equipped with recommendation features can increase average order values by 18%. The goal is clear: move beyond general audience segmentation to create truly one-to-one, in-the-moment shopping experiences.
While product recommendations are a big part of AI’s role, they’re far from the whole story. AI is transforming the entire customer journey.
Real-Time Behavioral Personalization
AI doesn’t just suggest products - it customizes the entire shopping experience. This includes dynamic pricing, tailored promotions, and landing pages that adapt based on a customer’s profile and behavior on the site.
For example, TFG (The Foschini Group) used an AI chatbot during Black Friday, which led to a 35.2% boost in online conversion rates and a 39.8% jump in revenue per visit. Similarly, Benefit Cosmetics leveraged AI to trigger action-based emails, resulting in a 50% increase in click-through rates and a 40% rise in overall revenue.
Gary Hawkins, Founder and CEO of the Center for Advancing Retail & Technology, summed it up perfectly:
"Retail competition has shifted to the individual customer, and knowing who your customers are along with their purchases and other information is no longer optional".
AI is redefining how brands engage with customers at every stage of the shopping journey.
This shift also highlights the growing importance of first-party data. With privacy laws like GDPR and CCPA phasing out third-party cookies, brands need to rely on data collected directly from their customers. Offering incentives like loyalty programs, personalized accounts, or exclusive content can encourage shoppers to share their information, enabling AI to deliver even more precise personalization.
AI-Driven Live Shopping and Shoppable Videos
AI is reshaping how we shop in real time, going beyond personalized product recommendations to revolutionize live shopping experiences.
In the U.S., live shopping is projected to hit $68 billion by 2026, with conversion rates up to 10× higher than traditional e-commerce. Yet, traditional livestreams can be resource-heavy, requiring constant coordination and high production costs. AI is stepping in to make live shopping more scalable, engaging, and accessible around the clock.
Jane Cheung, Global Research Leader for Consumer Industries at IBM Institute for Business Value, captures the essence of live shopping's appeal:
"If you can define what's most important to your core customer, then a livestream can speak to them in an easy, targeted and entertaining manner."
The numbers back this up: 82% of consumers prefer watching livestreams from brands over reading social media posts, and 47% of Gen Z consumers in the U.S. and U.K. have already embraced livestream shopping. AI is removing the logistical hurdles that once held back live shopping's potential, making it more interactive and far-reaching.
AI-Hosted Livestreams
Enter AI-powered hosts, or "AI Twins", which can run branded livestreams 24/7 without human input. These AI agents handle everything - answering customer questions in real time, showcasing products, and adjusting promotions based on viewer behavior. They even support over 40 languages, making it possible to engage global audiences simultaneously without the need for separate production teams or translations.
The results are impressive. 28% of AI-driven live sales chats convert into purchases, compared to just 2% for standard e-commerce. Brands adopting AI-powered live shopping have seen a 57% increase in average order value and a 21% reduction in product returns. For example, Walmart’s partnership with TikTok for a shoppable livestream in December 2020 exceeded expectations, generating 7 times more views than anticipated and boosting its TikTok follower count by 25%. This success spurred follow-up events like the "Spring Shop-Along: Beauty Edition" in 2021.
AI also adds a personal touch. By analyzing viewer comments, questions, and even emojis during livestreams, AI can deliver tailored product recommendations on the spot. For instance, if someone asks about sizing or color options, the AI responds immediately. Generative AI chatbots, trained to mimic the host’s tone and style, continue answering questions even after the livestream ends.
Shantha Farris, Sales and Commerce Offering Strategy Leader at IBM Consulting, highlights the value of live commerce:
"Live commerce makes it so much easier for a customer to fully understand a product so there are no surprises after the purchase."
But AI's contributions don’t stop with live streams - it’s also revolutionizing video content creation.
Shoppable Video Content
AI is transforming how brands create shoppable videos, turning product images and scripts into user-generated content (UGC)-style videos in seconds. These short clips, designed for platforms like TikTok, Instagram Reels, and YouTube Shorts, include integrated product links, enabling viewers to shop directly from the video without leaving the app.
Shoppable posts have been shown to deliver a 161% boost in conversions and 4× higher click-through rates. AI also supports "interactive discovery", where viewers can ask questions like, "What can I buy from this video?" or request similar items, turning passive browsing into active engagement.
Between 2024 and 2025, AI-driven referral traffic to retailers surged more than 10 times. Brands are also using AI to identify standout moments from livestreams and automatically repurpose them into evergreen shoppable clips for product pages and social media feeds.
Scaling Creator Content with AI
AI isn’t just reshaping live shopping - it’s also changing how brands scale creator content to meet the demands of social commerce.
Keeping up with the constant need for fresh content is a major hurdle for brands. Traditional influencer partnerships require time-consuming outreach, negotiations, and coordination, making it hard to scale efficiently. AI is flipping the script by automating content production and influencer licensing, all while keeping the creators’ authentic voices intact.
The stats back it up: 73% of marketers believe AI can largely automate influencer marketing, and 66.4% say campaigns that incorporate AI see better results, such as higher reach and conversions. With AI, brands can now manage hundreds of creator partnerships at once, turning a process that used to take weeks into something that happens in minutes. This not only speeds up content creation but also ensures it aligns seamlessly with brand strategies.
UGC Automation
AI-powered platforms are enabling brands to create user-generated content (UGC) instantly - no need to wait on creators to film, edit, and deliver. Using AI-generated creator avatars, brands can produce UGC-style videos on demand, replicating each creator’s unique style while scaling content for entire product catalogs.
What’s more, this technology supports 40+ languages, allowing brands to create localized content for global audiences all at once.
The impact is already measurable. 63% of marketers report increased revenue after integrating AI into their social media strategies. AI tools that repurpose content - like breaking down long-form videos into bite-sized clips for TikTok, Instagram Reels, and YouTube Shorts - help brands get the most out of each piece of creator content. These tools can also tag products, extract quotes, and generate ad variations, creating an efficient "UGC-to-Shop" workflow.
Influencer Licensing at Scale
AI isn’t just about creating new content - it’s also revolutionizing how brands license and repurpose influencer content. AI tools can analyze millions of profiles to evaluate influencers based on authenticity, engagement, and brand compatibility. This shifts the focus from follower counts to performance metrics that actually drive results.
A great example of this is Marks & Spencer, which introduced its "Style Types and Outfit Explorer" tool in 2025. Used by 450,000 customers, this AI-driven system generated 40 million outfit combinations tailored to style preferences and body shapes. The tool played a significant role in the app driving 44% of all online orders.
AI also helps brands maintain consistency across vast networks of creator partnerships. It ensures that while creators bring their unique flair, the brand message stays cohesive. As Deloitte notes, the key is balancing creative freedom with brand alignment.
James Nord, Founder of Fohr, sums it up well: "AI can help you understand what seems to be working across all these different people and these tens of thousands of posts".
Backend AI Improvements for Operations
While AI-powered live shopping and creator content often steal the spotlight, the real game-changer might be happening behind the scenes. Backend AI upgrades are reshaping how brands handle inventory, detect fraud, and fulfill orders. These advancements are making social commerce faster, safer, and more efficient. While customer-facing AI drives engagement, these backend systems provide the crucial support needed to deliver a seamless experience.
Here’s what the numbers say: 60% of retail buyers report that AI has improved the accuracy of their demand forecasting. Additionally, 78% of global business and technology leaders state that AI has strengthened fraud detection and risk management. AI-powered demand planning tools can even cut overall inventory levels by 20% to 30%, freeing up capital that would otherwise be tied up in excess stock. These behind-the-scenes improvements may not grab headlines, but they’re the backbone of modern social commerce.
Inventory Forecasting and Demand Prediction
The days of relying on spreadsheets for inventory management are over - especially in a world where a single viral TikTok can cause demand to skyrocket overnight. Brands unprepared for these sudden spikes risk stockouts or expensive last-minute shipping to meet demand.
AI steps in by monitoring social signals in real time. It identifies viral trends and adjusts inventory levels before the surge hits. Daniel Lewis, CEO of LegalOn, highlights how AI outperforms traditional methods:
"Our AI system detected viral TikTok trends and unseasonable weather patterns that spreadsheets failed to identify".
This ability to anticipate demand can free up as much as 30% of working capital in just a few weeks. For brands running live shopping events across platforms like TikTok Shop, Instagram, or their own storefronts, AI ensures inventory stays synchronized. This prevents overselling and avoids frustrating customers.
AI doesn’t just predict demand - it also forecasts returns. Social commerce, with its live shopping events and impulse buys, often sees higher return rates than traditional ecommerce. By anticipating these returns, AI helps brands adjust future stock levels and minimize reverse logistics costs. Panos Voulgaris, Creative Strategy Director, explains:
"Usual stock management involves human involvement, but by setting up Flow, we're able to save a huge amount of time and eliminate human error".
Fraud Prevention and Order Fulfillment
Inventory management is only part of the equation - secure and reliable order fulfillment is just as critical. Social commerce, with its fast-paced and impulsive transactions, creates fertile ground for fraud. In fact, global ecommerce fraud is expected to hit $107 billion by 2029 - a staggering 141% increase from 2024. Fraudsters exploit social commerce using bots, fake accounts, and stolen payment details.
AI tackles these threats with real-time anomaly detection, analyzing purchase patterns, device behavior, and navigation speed to differentiate between genuine shoppers and fraudsters. This approach reduces false positives by up to 85%, allowing legitimate transactions to go through while safeguarding customer trust.
The impact is clear. In 2025, skincare brand Paula's Choice saw a 6x ROI boost after adopting AI-driven fraud detection. Within just three days, they saved over $100,000 from fraudulent orders and reduced chargeback rates by 0.2%. Similarly, care brand Harry’s slashed chargebacks by 85% in two months by using AI to flag suspicious bulk purchases from fake accounts.
AI also enhances order fulfillment by dynamically choosing the most cost-effective shipping options. It factors in inventory location, customer preferences, and real-time logistics data to optimize delivery routes. This reduces inefficiencies - known as "blind handoffs" - in the supply chain, which cost the U.S. an estimated $95 billion annually.
Conclusion
AI is transforming social commerce in ways that were once unimaginable. It powers hyper-personalized recommendations, hosts AI-driven livestreams, and enables real-time targeting that turns casual browsers into loyal buyers. Behind the scenes, it fine-tunes inventory forecasting, combats fraud, and simplifies order fulfillment. The result? A smoother shopping experience, with AI personalization driving conversion rates up by 15–25% and delivering a marketing return of 5–8x.
Let’s talk numbers. AI-referred traffic to U.S. retail sites skyrocketed 4,700% year-over-year as of July 2025. Meanwhile, 63% of retail executives believe that failing to adopt AI agents could leave companies trailing behind within just two years. And Gen Z? This generation, projected to wield $9 trillion in spending power by 2034, is 10x more likely than older shoppers to use AI for discovering products.
The rise of agentic commerce is already happening. AI agents are evolving beyond basic chatbots to become autonomous shoppers - capable of finding products, comparing prices, and completing purchases. By 2030, these AI-driven agents could help generate up to $1 trillion in U.S. B2C retail revenue. Brands that act now to integrate AI into their strategies will be best positioned to capture this growing market.
AI is also revolutionizing content creation. Tools like TwinTone are helping brands produce authentic user-generated content (UGC), host AI-led livestreams, and automate creator content across platforms like TikTok, Shopify, Amazon, and YouTube. This eliminates the delays of traditional creator outreach, enabling ecommerce and DTC businesses to scale their social commerce efforts while keeping the authenticity that resonates with audiences.
Importantly, AI doesn’t replace creativity or brand identity - it enhances them. As Stanislas Vignon, Head of Insights at LVMH, aptly explains:
"Our creativity and authentic brand promise are what make us unique. AI cannot do that for us. What it will do is help us amplify our values and what differentiates us from others".
The question isn’t whether AI should be part of your strategy - it’s how fast you can make it happen. AI is no longer a future trend; it’s the present, and it’s reshaping the way we shop, connect, and grow.
FAQs
How does AI make shopping experiences more personalized in social commerce?
AI is reshaping the way we shop in the world of social commerce by diving deep into customer data - like browsing habits, past purchases, and even social media activity. By doing this, it gets a clear picture of what each shopper prefers. The result? Brands can offer product recommendations, promotions, and content that feel spot-on for every individual.
With tools like chatbots and recommendation engines working in real time, AI predicts what customers might want and suggests items that match their tastes or needs. This level of personalization doesn’t just grab attention - it encourages purchases and keeps customers coming back. In a competitive social commerce space, AI helps create shopping experiences that are smooth, engaging, and genuinely enjoyable.
How does AI improve live shopping and shoppable video experiences?
AI adds a new layer of excitement to live shopping and shoppable video content, making these experiences more dynamic, tailored, and engaging. During live events, AI works behind the scenes to analyze customer comments and behaviors as they happen. This allows brands to offer product recommendations and promotions that match individual preferences, creating a shopping experience that feels personal and interactive. The result? Higher engagement and better chances of converting viewers into buyers.
Beyond live events, AI-powered tools make product discovery a breeze. By personalizing content, these tools help shoppers easily find items that suit their style and needs. With relevant, real-time interactions, brands can create genuine shopping moments that connect with today’s consumers on a deeper level - strengthening relationships and driving sales.
How does AI improve backend operations like managing inventory and preventing fraud?
AI is transforming backend operations in social commerce, making them smarter and more efficient. Take inventory management as an example - AI dives into sales trends, customer habits, and supply chain data to forecast demand with precision. This means businesses can keep just the right amount of stock, sidestepping issues like overstocking or running out of popular items. It also streamlines logistics, keeping things running smoothly.
In the area of fraud prevention, AI steps up with advanced algorithms that monitor transactions and spot unusual activity in real time. Suspicious patterns are flagged instantly, reducing the risk of fraud and boosting customer confidence. By weaving AI into backend systems, brands can grow without compromising on security or operational efficiency.
