Accor’s Nicolas Maynard on Closing AI’s Industrialization Gap

Nicolas Maynard spent years building AI products at Amazon, including Alexa, before taking on a different scale problem at Accor: a portfolio of brands and hotels spread across markets that run on different systems and rules. As Senior Vice President, Data Science & AI, he joins Skift Data + AI Summit Europe, October 6, 2026, at Mastercard London. Ahead of the Summit, he shared where AI deployments stall and where he expects the payoff. The Gap Between the Pilot and the Property Skift: What is the single most important factor for successfully scaling AI in travel operations across European markets? Nicolas: I have seen many organizations successfully launch AI pilots. Far fewer manage to industrialize them. To me, the most important factor is bridging the ‘industrialization gap’ through a federated operating model that balances central governance with local regional empowerment. Across the industry, we see over 90% of hospitality players piloting AI, but only about 30% successfully embedding it into operations due to fragmented legacy systems and localized operational differences. To scale successfully across diverse European markets and brands, you cannot rely on a purely top-down approach. At Accor, we address this through a hybrid framework: Our central GenAI Center of Excellence defines the core architecture, security, ethical guidelines, and reusable components. Simultaneously, we empower regional business teams and our GenAI Ambassadors to adapt and deploy these tools locally. This balance ensures we maintain strict data privacy and security compliance (critical in Europe) while remaining agile enough to meet the unique operational realities of individual hotels. Accor’s federated AI operating model Built at the center, deployed by the regions Accor splits AI ownership in two so tools can scale across European markets and brands while fitting the reality of each hotel. Central governance GenAI Center of Excellence Defines Core architecture Security Ethical guidelines Reusable components Local empowerment Regional business teams and GenAI Ambassadors Adapt and deploy Local adaptation of central tools Deployment that fits each hotel’s operations What the balance protects Strict data privacy and security compliance, critical in Europe Agility to meet the operational realities of individual hotels Source: Nicolas Maynard, Accor, in conversation with Skift Skift: What has surprised you most about applying AI at scale in your organization? Nicolas: We quickly realized that scaling AI isn’t just a technology deployment; it’s a cultural transformation. Having spent years building AI-powered products at Amazon, I expected the technology challenges. What surprised me most at Accor was actually the human side. Our Heartists embraced AI much faster than anticipated. The real challenge was not convincing people to use AI, but ensuring we could support the demand responsibly and at scale. Skift: Can you share one insight from your experience with AI that attendees might not expect? Nicolas: Agentic AI in corporate environments is significantly more challenging than consumer-facing AI experiences might suggest. While consumer tools create the impression that autonomous AI can be deployed quickly and seamlessly, enterprise reality is far more complex due to fragmented legacy systems, strict security and compliance requirements, data quality constraints, and the need to orchestrate actions across multiple business processes. This gap between expectations and operational reality can create frustration among employees who expect consumer-grade simplicity but encounter the complexity inherent to enterprise-scale deployment. Where the Returns Land Skift: Are there common misconceptions about AI in travel operations that you would like to address? Nicolas: After spending years working on Alexa at Amazon, I have heard the same concern emerge with every major AI wave: that technology will replace people. In reality, the most successful deployments I have seen are the ones that make people more effective, not less relevant. In hospitality, the in-stay experience remains fundamentally human-led. Accor’s strategy is built on the philosophy of ‘Augmented Hospitality’, which means using AI to empower our Heartists, not replace them. We use AI to automate the repetitive, high-volume administrative tasks that keep our staff looking at screens rather than looking at guests. For example, our Guest Relation AI Platform (deployed in 200+ hotels) has reduced guest query response times from 30 minutes to just 1 minute, saving up to 100 hours per hotel per month. This doesn’t remove the human touch; it frees up our teams from manual drafting so they can dedicate more high-quality, face-to-face time to our guests. AI handles the friction, so humans can handle the hospitality. And all this strategy remains aligned with Accor’s purpose: Pioneering the Art of Responsible Hospitality, Connecting Cultures, with Heartfelt Care. Skift: Where do you see the biggest opportunities for AI to impact business outcomes in travel? Nicolas: If I had to bet on one shift over the next few years, despite the questions I’ve raised before, it would be the move from AI assistants to AI agents capable of executing actions autonomously. We see massive business impact in three key areas: Hyper-Personalized, Intent-Driven Conversion: Moving away from static marketing segments to real-time, intent-based personalization on channels like ALL.com, which can drive a 15% to 40% uplift in conversion and average basket size. Operational Efficiency in Shared Services: Our ‘AI Butler’ will act as a proactive, conversational entry point for hotel support. By late 2026, we target having up to 30% of internal support requests resolved end-to-end autonomously by AI, and 30-40% assisted by AI, allowing human experts to focus purely on complex cases. Process Re-engineering: Using agentic platforms to automate complex workflows across corporate functions like Finance, Legal, and HR, driving measurable savings and allowing teams to focus on strategic business growth. The Calls on the Table Operating model: Nicolas’ federated approach keeps architecture, security and guardrails at the center and hands deployment to regional teams. For multi-brand groups in Europe, the open call is how much central ownership compliance requires before it slows the hotels down. Agent readiness: Consumer AI sets employee expectations that legacy systems and data quality struggle to meet. Operators planning agent rollouts need to budget for that integration work before they budget for autonomy. Labor model: Accor measures Augmented Hospitality in hours returned to hotel teams. That sets up the harder question of what each property does with the time. Autonomy targets: Accor is targeting up to 30% of internal support requests resolved end to end by AI by late 2026. Peers now have a concrete benchmark for autonomous resolution at hotel-group scale. Hear Nicolas Maynard live at Skift Data + AI Summit Europe, October 6 in London, where the day’s lineup also includes Benjamin Cany of Amadeus and Sheena Varma of American Express Global Business Travel, among other travel leaders.