{"id":3000085610,"date":"2026-10-20T05:51:00","date_gmt":"2026-10-20T09:51:00","guid":{"rendered":"https:\/\/www.wework.com\/ideas\/?p=3000085610"},"modified":"2026-10-20T06:00:15","modified_gmt":"2026-10-20T10:00:15","slug":"wework-for-business-paris-recap-five-lessons-for-putting-ai-to-work","status":"publish","type":"post","link":"https:\/\/www.wework.com\/ideas\/professional-development\/wework-for-business-paris-recap-five-lessons-for-putting-ai-to-work","title":{"rendered":"WeWork for Business Paris Recap: Five Lessons for Putting AI to Work"},"content":{"rendered":"\n

The way companies work, grow, and make decisions is changing faster than ever. Our WeWork for Business<\/strong> event series brings business leaders and industry experts together in New York, Paris, and Mexico City to talk about what that change means in practice.<\/p>\n\n\n\n

On September 29, the series came to WeWork 33 Rue la Fayette<\/a> in Paris for AI: What\u2019s Really Changing for Businesses<\/em>. Keynote speaker Gilles Babinet<\/strong>, entrepreneur and president of Caf\u00e9 IA, opened with an important question: why are companies investing so heavily in AI without seeing widespread productivity gains?<\/strong> Most organizations still run on principles inherited from the Industrial Revolution, and simply adding AI to existing ways of working won\u2019t, by itself, make people more productive.<\/p>\n\n\n\n

A panel moderated by Les \u00c9chos<\/em> journalist Charlie Perreau<\/strong> picked up that thread with In\u00e8s Salhi<\/strong>, Chief Product Officer at Payfit; Adrien Raffin<\/strong> of CBRE; and Albin Serviant<\/strong>, creator of Cortex House.<\/p>\n\n\n\n

Here are five lessons from the evening for balancing AI\u2019s promise and its results.<\/p>\n\n\n\n

1. Start with the business problem, not the technology<\/h2>\n\n\n\n

New models and tools appear almost daily, and Raffin admitted CBRE is \u201cconstantly approached\u201d<\/em> by companies offering new solutions. \u201cThe important thing is not to start by asking which AI tool we should use,\u201d <\/em>he said. \u201cWe first need to understand where AI can create value.\u201d <\/em>For CBRE, that means finding inefficiencies and friction between departments before choosing any technology.<\/p>\n\n\n\n

Salhi has come to the same view at Payfit. \u201cThe latest model is not necessarily what will make the biggest difference to our customers or our productivity,\u201d<\/em> she said. Her team puts its energy into how agents are built and what information they can reach.<\/p>\n\n\n\n

Babinet argued that the biggest gains come from rethinking how a business creates and delivers value. He pointed to Tesla, which has expanded from cars into software, charging, insurance, and autonomous driving, and suggested retail, real estate, and building management could see similar shifts.<\/p>\n\n\n\n

2. AI adoption is moving from individual tools to connected workflows<\/h2>\n\n\n\n

Payfit introduced Payfit Copilot early as a knowledge-sharing chatbot, and it was adopted faster than any product the company had launched. Salhi described what came next. First, the goal was getting as many employees as possible comfortable experimenting. Then came shared agents and knowledge management. Now Payfit is building workflows that span customer support, product, and sales.<\/p>\n\n\n\n

\u201cThese are no longer individual productivity tools,\u201d<\/em> Salhi said. \u201cThey are collective workflows.\u201d<\/em><\/p>\n\n\n\n

Letting employees pick their own tools helped early adoption<\/strong>. Once teams started building shared agents, Payfit moved most of them onto one platform so they could stop debating tools. Babinet sees this across the industry, with more of AI\u2019s value now coming from the orchestration and workflows built around the models.<\/p>\n\n\n\n

\"WeWork<\/figure>\n\n\n\n

3. Company knowledge is now a competitive asset to protect<\/h2>\n\n\n\n

Babinet warned about the risk to what he called a company\u2019s \u201ccognitive image,\u201d its collective knowledge of how it actually operates. With agentic AI, he said, access to a company\u2019s internal communications and systems could let another organization reconstruct much of its operating model. He expects more companies to keep sensitive data on private infrastructure and use external models for specific tasks.<\/p>\n\n\n\n

The panelists described how they handle this today. \u201cWhen we build an AI agent for our customers, it must operate with exactly the same permissions as the person using it,\u201d <\/em>Salhi said. Payfit applies the same rule internally and reviews each new connector, since information hidden in an app\u2019s interface can sometimes still be reached through an integration. At CBRE, where data is \u201ca significant part of the value we provide to our clients,\u201d<\/em> AI has been introduced gradually in secure environments. Serviant pointed out that the connections between systems can be vulnerable even when each application is secure.<\/p>\n\n\n