On 8 October 2026, La Retail Tech community brought together leading retail businesses to discuss the challenges facing marketplaces. As a technology and AI partner and an active member of this ecosystem, Novity took part in the discussions.
Leaders from established retailers, including But, Conforama, Fnac Darty, Rue du Commerce and Adeo (formerly Groupe Leroy Merlin), highlighted a common challenge.
Shopping habits are changing. Competition is increasing, and customers expect a consistent experience across online and physical channels.
To keep pace, IT teams must integrate AI responsibly and manage large volumes of data. They also need to demonstrate a measurable return on investment.
Unified commerce and the shift towards hybrid retail models
Online-only retail has its limits, particularly in sectors such as home furnishings. Combining digital channels with physical stores is becoming increasingly important. During the event, Alexandre Falck, CEO of But and Conforama, explained that e-commerce accounts for between 12% and 15% of their business.
The home furnishings market is closely linked to changes in the property sector. Physical stores therefore remain important. They support logistics and give customers confidence before making a purchase.
Marketplaces help retailers connect these channels. At Adeo, furniture has become the largest online sales category, despite traditionally taking up less space in physical stores. Its marketplace allows the company to offer a broader product range and reach customers throughout their buying journey.
Retailers are also exploring new sources of growth. Fnac Darty is expanding its refurbished product offering to capture opportunities in the circular economy, including C2C and B2B2C models. Rue du Commerce is moving further into home products, while Adeo is developing a services marketplace that connects customers with tradespeople.
These changes require resilient platforms. At Novity, our engineering teams already support a major French company specialising in refurbished technology products. This experience gives us direct insight into the technical challenges of this market.
As marketplaces expand, their architectures must manage customer identity, financial transactions and payments across the entire buying flow. We recently explored these challenges with the teams at Purse. Their experience highlights the importance of flexible transaction systems. Without them, adding new services can quickly create technical and regulatory challenges.
Scaling artificial intelligence across retail operations
Generative AI creates new opportunities to improve customer experiences. However, deploying it at scale also raises important governance questions for IT leaders. One concern is the growing use of unapproved AI tools, often referred to as Shadow IT. These tools can expose sensitive business data and create security risks.
For business leaders, establishing consistent rules for AI use is becoming a priority. Managing the cost of large language models (LLMs) is another challenge.
As discussed during the event, two seemingly similar requests can consume very different numbers of tokens from one week to the next.
This makes AI infrastructure costs difficult to predict and manage across an organisation.
Three practical AI applications for retail operations
To generate lasting value from AI investments, retail leaders are focusing on three areas:
- Supply chain management: Connect supply flows and improve how products are routed to warehouses and stores.
- Software engineering: Speed up development through AI-assisted coding, bug detection and automated test generation.
- Customer service: Introduce conversational AI agents that can understand customer intent more accurately than traditional rule-based chatbots.
Moving beyond AI pilots with a technology partner
Scaling AI requires a clear technical framework and a reliable software architecture. This is the approach we take when supporting our clients' data and AI transformation.
Our teams have validated their technical expertise through Anthropic's Claude Certified Architect – Foundations (CCA-F) certification programme. Novity has also achieved Certified status within the Claude Partner Network.
This recognition reflects our commitment to structured, well-documented AI engineering. From initial planning to production deployment, our specialists assess existing architectures and identify ways to improve product performance.
We build AI solutions that work with our clients' existing systems, tools and databases. In practice, this includes autonomous AI agents and solutions built using LLMs, Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP). The objective is to turn AI capabilities into practical applications that deliver measurable value for e-commerce platforms.
Improving product catalogue data for more accurate AI
Agentic AI is opening new opportunities for conversational commerce. However, autonomous assistants can only make useful recommendations when they have access to reliable product data.
Poor-quality data reduces the accuracy of AI recommendations. It can also undermine customer trust and slow adoption. For marketplaces, improving product information management (PIM) is therefore a technical priority.
We recently discussed the importance of catalogue optimisation with SteerFox, a specialist in e-commerce customer acquisition and product assortment optimisation. Their analysis shows that businesses need to standardise data flows and automate product information enrichment before introducing AI into customer-facing interfaces.
Antoine Pougeas, Chief Sales Officer at Novity −
« The quality of the discussions at La Retail Tech Thursdays shows how mature the ecosystem has become. Hearing retail leaders share their experience of managing AI was particularly valuable.
Unpredictable token costs and Shadow IT are real challenges at an organisational level.
This confirms what we see among our clients: technology is moving quickly, but without clear governance and reliable data architecture, costs can spiral.Supporting teams through this transition requires a structured approach.»
Key technology challenges for E-commerce platforms in 2026
