Retail News CRM

Tag: Agentic Commerce

  • Only 45% of Retailers Scale AI Despite Threefold Earnings Advantage

    Only 45% of Retailers Scale AI Despite Threefold Earnings Advantage

    Only 45 percent of retailers are scaling artificial intelligence across their operations, even as businesses committing heavily to the technology generate three times higher revenue and earnings growth.

    According to research highlighted this week by Boston Consulting Group managing director and partner Charlie Reid, operators treating artificial intelligence as a core discipline outpace rivals by triple on top-line sales and EBITDAR. Yet widespread experimentation across scattered pilots leaves the majority of commercial operators unable to convert software trials into balance sheet gains.

    Fragmented initiatives and inadequate organisational changes continue to limit companies from translating investments into measurable financial returns, Boston Consulting Group noted in November 2026 findings.

    Where Merchandising Delivers Fast Payback

    Capital is flowing primarily into core store and supply chain operations rather than back-office corporate support. Retailers are largely bypassing enterprise applications across human resources, procurement, and finance because those departments offer lower immediate financial return.

    Merchandising operations are providing the quickest path to measurable payback. Adjusting product assortment, pricing, promotion schedules, and vendor negotiations through artificial intelligence tools generates cash flow that operators use to fund broader technology rollouts. Getting shelf assortment right yields up to a 5 percent increase in like-for-like sales.

    The Friction Behind Operating Models

    Fragmented rollouts and weak internal adoption explain why most deployments stall at the testing phase. Boston Consulting Group measures technology implementation through what it terms a 10-20-70 operating breakdown: algorithms account for 10 percent of the transformation, data and systems represent 20 percent, while people, operating processes, and institutional structure dictate the remaining 70 percent.

    Tools fail when buyers and floor staff lack clear authority or incentive to execute automated guidance. An algorithmic recommendation creates zero value if a category merchandiser overrides the system or if store staff fail to reset physical shelf space. Executive teams routinely hunt for novel software without identifying the exact financial metric they need to alter.

    “So, at BCG, we call it the 10 2070 rule. 10% of the AI transformation is driven by the algorithm. 20% by the data and technology and then 70% by the organization, the processes um and and and and the people in the organization.”

    Competing for Automated Buyers

    Consumer interaction is shifting toward agentic commerce, where automated systems handle product discovery, price comparisons, and digital checkout tasks. Shoppers currently manage friction across physical aisles and mobile applications, frequently abandoning journeys when items show out of stock at checkout.

    Software agents compress that multi-step search into direct prompts, assembling tailored baskets against specific household dietary rules and spending limits. Over extended periods, these systems track household consumption patterns and reorder domestic staples before pantries run empty.

    That shift alters digital distribution outside merchant properties. Consumers searching through external platforms like Google and ChatGPT rely on software agents that scrape product attributes, ingredient registries, and live inventory across competing web domains simultaneously. Retailers must structure open, accurate product catalogues for algorithmic inspection rather than relying solely on visual merchandising to win human attention.

    Pruning Unfocused Software Trials

    Commercial operators face pressure to demonstrate cash returns on software capital expenditures. Treating machine learning as an exploratory technical exercise without strict hurdle rates has tied up working capital across fragmented vendor contracts.

    Survival across competitive consumer markets requires pruning low-yield software trials to protect core operating margins. Retailers that narrow their engineering resources to inventory visibility, predictive replenishment, and machine-readable data feeds will command distribution as autonomous purchasing tools take over routine household spending.

  • Digital Retailers Lead AI Commerce as Consumer Brands Lag, Benchmark Shows

    Digital Retailers Lead AI Commerce as Consumer Brands Lag, Benchmark Shows

    Retailers are locking down direct access to automated shopping systems, leaving consumer goods manufacturers scrambling to keep their products visible as buyers hand search queries over to algorithms. Checkout platforms control the transaction pipe, and that proximity gives them the power to dictate terms.

    An evaluation of 106 consumer companies published in October 2026 shows all six digital retail platforms evaluated maintain an explicit agentic commerce strategy, with five operating live tools. By contrast, only two out of 53 consumer products manufacturers run an active offering.

    The divide reflects who owns customer interactions at the point of purchase. Retailers are deploying their own virtual assistants and linking inventories directly into third-party artificial intelligence engines to protect baskets. Consumer product makers remain largely relegated to optimizing product descriptions so language models recommend their items.

    Early Revenue Shows High Basket Sizes

    Conversion metrics explain the speed of retail investment. AI-referred shoppers to retail portals convert 42 percent better than conventional inbound channels, reversing the prior year when such traffic converted 38 percent worse. In the United States, 40 percent of shoppers report using automated systems to buy goods online, with 85 percent rating the automated journey higher than standard site search.

    Top-tier operators report material revenue gains from proprietary tools. Amazon attributes roughly $12 billion in incremental annualized sales to its Alexa for Shopping platform, formerly known as Rufus. Walmart recorded a 35 percent rise in average order value among customers using its Sparky assistant.

    Supermarket and specialty store operators are taking defensive positions against third-party aggregators. Eleven of 16 surveyed domestic and specialty retailers hold an explicit automated commerce strategy, with eight running live customer-facing systems. Walmart cited agentic platforms as an operational risk in its corporate filings, while Kroger warned investors that external platforms risk disintermediating direct shopper relationships.

    Asian Travel Retailers Test Automated Assistants

    Travel retail represents the slowest segment in the benchmark. Only two of 11 operators maintain an active roadmap, and none outline specific AI commercial goals in investor reporting.

    Pockets of regional testing show how duty-free operators intend to bridge the gap. In South Korea, Lotte Duty Free introduced a ChatGPT shopping service in July 2026 to guide travelers through duty-free assortments. In Australia, WH Smith deployed a pilot in-store AI assistant at Melbourne Airport to answer traveler product queries at the shelf edge.

    For Asian department stores and cross-border airport operators, third-party agents threaten high-margin concession models. If transit passengers rely on personal AI agents to compare tax-free allowances and local downtown prices, airport concessionaires lose pricing use. Terminal retail landlords face weaker tenant turnover if automated comparison engines steer passengers toward duty-paid domestic orders before they board.

    Manufacturers Pay to Win Model Recommendations

    Consumer goods makers operate below the checkout interface. Only 20 of 53 manufacturers evaluated possess an AI commerce strategy, focusing primarily on search visibility rather than direct checkout mechanics.

    Basic content restructuring produces immediate results. Confectionery maker Mondelēz increased citation rates for its Oreo brand from 10 percent to roughly 70 percent in cookie-related AI queries by formatting public product descriptions into machine-readable data. Beauty conglomerate L’Oréal paired visibility optimization across its catalog with proprietary conversational interfaces, introducing its Beauty Genius advisor alongside a checkout path and virtual try-on system linked with ChatGPT.

    Visibility optimization is shifting into a paid auction channel. OpenAI generated an estimated $1 billion annual revenue run rate within 200 days of launching sponsored placements in ChatGPT. Purchasing intent within the chat platform rose from 13.9 percent to 19.2 percent over 12 months, representing 28 billion shopping-focused conversations annually.

    Auditing Enterprise Catalogs for Bot Traffic

    The rush toward bot-ready inventory follows a year of mixed commercial pilots. Early conversational commerce interfaces suffered from product hallucinations, out-of-stock suggestions, and high bounce rates before direct platform catalog integrations took hold.

    Retail networks and packaged goods groups are reallocating promotional funds away from traditional retail media networks and keyword search auctions toward large language model placement. Brands that establish structured product data feeds retain control over their pack sizes and ingredient claims, while slow manufacturers risk total exclusion from automated basket-building workflows.

    The operational battleground now shifts to API access agreements. Store operators must negotiate whether external agents like ChatGPT or Google Gemini are permitted to scan internal inventories without paying data licensing fees. The next round of retailer quarterly earnings will clarify which platforms block automated screen scrapers and which operators sell privileged inventory feeds directly to tech intermediaries.

  • Tech Mahindra Partners with Rezolve Ai to Scale Agentic Retail Commerce

    Tech Mahindra Partners with Rezolve Ai to Scale Agentic Retail Commerce

    Indian IT services major Tech Mahindra partnered with London-based Rezolve Ai to deploy automated agentic shopping technology across its network of more than 1,100 enterprise clients.

    The agreement gives Rezolve access to 146,000 systems professionals across 90 countries to take retail artificial intelligence beyond conversational chatbots and into live transaction processing.

    Integrating AI Checkout into Enterprise Systems

    Under the alliance, Rezolve Ai will supply its Brain Suite software, which includes Brain Commerce for conversational product discovery and Brain Checkout for autonomous transactions. The system runs on proprietary brainpowa models designed to eliminate hallucinations during commercial transactions, alongside TraceWare audit software that tracks automated agent decisions.

    Tech Mahindra will manage consulting, cloud infrastructure and systems engineering for retail, consumer goods and financial services clients. The combined setup allows AI agents to interpret consumer intent, recommend inventory and execute payments inside existing digital storefronts.

    Daniel M. Wagner, chairman and chief executive of Rezolve Ai, noted that Tech Mahindra’s existing enterprise relationships provide the distribution engine needed to deploy transactional AI at commercial scale.

    Enterprise Push for Transactional AI

    Systems integrators across Asia are racing to shift enterprise clients from experimental chatbots to revenue-generating commerce tools. While basic generative AI handled customer support across Asian retail platforms over the past two years, enterprise rollouts previously stalled at checkout where transaction security and inventory data errors create financial liability.

    Rezolve Ai plans to present its enterprise commerce deployment data during an investor presentation scheduled for October 6, 2026.

  • Over A Third of Asian Shoppers Would Let AI Switch Brands, Accenture Finds

    Over A Third of Asian Shoppers Would Let AI Switch Brands, Accenture Finds

    More than a third of consumers across Asia would let artificial intelligence switch their purchases to a competing brand if the algorithm found a better match, according to data from Accenture.

    The finding reveals that conventional customer loyalty offers little protection against automated shopping tools designed to optimize price and product fit.

    Shoppers who identify as loyal to specific labels are willing to delegate buying decisions to autonomous digital assistants. These systems evaluate alternative products in real time and execute switches without requiring consumers to compare catalogs manually.

    Automated choices challenge legacy loyalty

    Retailers across the Asia-Pacific region have invested heavily in points schemes, subscription tiers, and bespoke mobile apps to lock in repeat buyers. Autonomous software cuts through those incentives by prioritizing immediate utility over historical brand affinity.

    When an algorithm spots a cheaper alternative, faster delivery, or better specifications, consumer willingness to let the machine override personal habits leaves traditional retention strategies exposed.

    The change shifts power toward platforms that control the automated interface rather than the merchants producing the goods.

    Trust gaps determine adoption speed

    Consumer willingness to hand over purchasing authority depends directly on how much trust shoppers place in the underlying algorithms. Retailers operating in Asian markets must now compete not only on shelf presence and digital advertising, but on whether their product feeds are structured for automated evaluation by third-party AI agents.

    Brands that fail to provide clean, verifiable product specifications risk being bypassed entirely by autonomous recommendation engines.

    Enterprise retailers across the region are now reassessing product data infrastructure as agentic commerce tools move from experimental pilots into mainstream consumer applications across Asian digital storefronts.