In the bustling world of retail, where customer expectations shift faster than stock levels, a quiet revolution is underway. Major chains across the US and Europe now rely on AI chatbots to handle 70 percent of incoming customer queries, according to a new report from Forrester Research released this week. This milestone marks a tipping point in how brands interact with shoppers, blending efficiency gains with fresh challenges in personalisation and trust.
The data comes from Forrester’s 2026 Customer Experience Index, which surveyed over 500 retail executives and analyzed query logs from chains like Walmart, Tesco, and Carrefour. In these giants, AI systems processed 68 to 72 percent of inquiries last quarter, up from just 42 percent two years ago. Smaller players, such as mid-tier fashion outlets like ASOS and Zalando, hit similar marks at 65 percent. “We’re seeing AI take over routine tasks so humans can focus on complex issues,” said Forrester analyst Nigel Fenwick in the report. This shift isn’t just about numbers; it signals a broader pivot in eCommerce operations, where technology promises cost savings but demands careful oversight to avoid alienating customers.
Retailers have poured resources into this trend for years, but the past 18 months accelerated it. Generative AI models, refined since tools like ChatGPT burst onto the scene in late 2022, now power chatbots that resolve issues with uncanny speed. Walmart, for instance, deployed its “Walmart Voice Order” AI last year, which fields queries on stock availability, returns, and delivery slots. Internal data shared with analysts shows it handles 71 percent of its 15 million monthly chats autonomously. Tesco followed suit with an upgraded “Clubcard Chat” bot, resolving 69 percent of queries without human intervention, per UK retail filings.
Why the surge? Cost is a big driver. Human agents cost retailers an average of $6 to $12 per interaction, depending on location and complexity, while AI drops that to under $0.50, per Gartner estimates. For chains processing millions of queries daily, the math adds up fast. Take Target: its AI rollout saved $120 million in labor costs in 2025 alone, according to a company earnings call. Multiply that across sectors, and global retail could shave $50 billion off service expenses by 2028, Forrester projects. Yet this efficiency comes amid rising query volumes, fueled by eCommerce’s post-pandemic boom. Global online sales hit $6.5 trillion in 2025, per eMarketer, driving a 25 percent uptick in customer support tickets.
The Technology Powering the Shift
At the heart of this change lie large language models (LLMs) fine-tuned for retail. Companies like Google with its Gemini-powered bots and Microsoft via Azure AI lead the pack, but specialists such as Ada and Intercom dominate eCommerce deployments. These tools use natural language processing to parse queries like “Is my order delayed?” or “What sizes are left in the blue jacket?” and respond in seconds.
Consider the mechanics. A typical chatbot ingests query data, cross-references it with real-time inventory from ERP systems like SAP or Shopify, and generates replies. Accuracy has soared: resolution rates now average 85 percent on first contact, up from 60 percent in 2023, thanks to retrieval-augmented generation (RAG). This technique pulls live data into AI responses, reducing hallucinations – those pesky incorrect answers that plagued early bots.
A clear example unfolded at Amazon last Black Friday. Its Rufus AI assistant fielded 75 percent of queries, handling 2.5 million interactions per hour at peak. “Rufus didn’t just answer; it upsold by suggesting alternatives when items were out of stock,” noted Amazon exec Stefano Perego in a post-event briefing. Conversion rates on those chats rose 12 percent, blending service with sales.
Numbers paint a vivid picture. Here’s a snapshot of adoption across major chains:
| Retailer | AI Query Handling (%) | Annual Queries (Millions) | Cost Savings (2025, $M) |
| Walmart | 71 | 180 | 150 |
| Tesco | 69 | 120 | 85 |
| Target | 70 | 95 | 120 |
| Carrefour | 68 | 110 | 90 |
| ASOS | 65 | 45 | 35 |
Source: Aggregated from company reports, Forrester, and Gartner (2026 data).
This table underscores the scale. Walmart’s volume alone dwarfs many countries’ call centers, making AI not just desirable but essential.
Benefits: Speed, Scale, and 24/7 Reach
The upsides are hard to ignore. Customers get instant replies, often outperforming wait times. A Zendesk study found AI chats resolve issues 40 percent faster than humans, with satisfaction scores holding steady at 82 percent – on par with live agents. For global chains, this means uniform service across time zones. Carrefour’s bot, for example, supports 12 languages and handles queries from Paris to São Paulo without fatigue.
Scalability shines during peaks. Cyber Monday 2025 saw query volumes spike 300 percent; AI absorbed the load, preventing meltdowns that once cost retailers millions in lost sales. “It’s like having an infinite workforce,” says Dipanjan Chatterjee, Gartner’s research VP. Environmentally, it cuts paper trails – digital resolutions slash printing by 30 percent in some operations.
In niche areas, AI excels. Product recommendations via chat boost average order values by 15 to 20 percent, per McKinsey. Fashion retailer Zalando reports its bot influences 18 percent of purchases through query-driven suggestions.
Challenges: When AI Falls Short
No revolution lacks friction. Despite the 70 percent benchmark, the remaining 30 percent of queries – often emotional or nuanced – demand human touch. Complaints about bot limitations abound. A BrightLocal survey revealed 42 percent of consumers distrust AI for complex issues like refunds or disputes, citing “inhumane” responses.
Errors persist too. Early 2026 saw United Airlines’ bot glitch, misrouting 5 percent of baggage queries and sparking social media backlash. Resolution rates dip below 70 percent for queries involving policy exceptions, where context matters. Privacy worries loom large: with GDPR and CCPA tightening, mishandled data in chats could invite fines. The EU fined a major retailer €20 million last year for inadequate AI consent logs.
Training data biases add another layer. Bots trained on skewed datasets underperform for non-English speakers or underserved demographics. In the US, Black and Hispanic shoppers report 15 percent lower satisfaction with AI service, per a Pew study, prompting calls for diverse datasets.
Workforce impacts stir debate. AI has displaced 200,000 retail support jobs since 2023, Oxford Economics estimates, though it creates roles in AI oversight. “We’re reskilling agents for high-value work,” Tesco’s customer ops head told me in a recent interview. Still, unions push back, demanding transparency.
Competitive Landscape and Future Trajectories
Who leads? US chains edge ahead, with 75 percent adoption in top-10 grocers versus 62 percent in Europe, per Statista. Asia lags at 55 percent but grows fastest, led by Alibaba’s Cainiao bot handling 80 percent of queries in China.
Emerging trends point to multimodality. Voice and image-integrated bots, like Apple’s Siri upgrades for shopping, could push handling to 85 percent by 2028. Voice commerce, already 25 percent of Amazon’s queries, grows 35 percent yearly.
Integration with other tech amplifies gains. Pairing AI with AR for virtual try-ons, as Lululemon does, resolves 78 percent of fit queries instantly. Predictive analytics forecast issues pre-query, potentially cutting volumes 20 percent.
Yet regulation beckons. The EU’s AI Act, effective 2026, classifies retail bots as “high-risk,” mandating audits. US states eye similar rules, which could slow rollouts but boost trust.
Voices from the Front Lines
Shoppers offer mixed views. “It’s great for quick stock checks, but I hang up on bots for returns,” says Maria Lopez, a frequent Target online buyer from Chicago. Executives remain bullish. “70 percent is our floor; we’re aiming for 90,” Walmart’s eCommerce chief declared at CES 2026.
Analysts like myself see this as eCommerce’s next maturity phase. Chains mastering AI-human hybrids will pull ahead, much like early adopters of mobile apps dominated a decade ago.
Balancing Efficiency with Empathy
As AI chatbots claim 70 percent of the query battlefield, retail stands at a crossroads. The gains in speed and cost are undeniable, freeing resources for innovation amid $6.5 trillion in sales. Yet success hinges on bridging gaps – refining accuracy, embedding empathy, and prioritizing human oversight for the rest.
For major chains, this isn’t a tech gimmick but a core competency. Those who blend AI’s scale with genuine connection will define customer loyalty in the 2020s. Forward-thinking leaders must invest now: audit biases, train hybrids, and listen to feedback. The query volume won’t slow; neither should the evolution. In eCommerce, adaptation isn’t optional – it’s survival.
