How Bouygues Telecom uses AI

Bouygues Telecom relies on contractors for its fiber rollout and used to check only a small share of installations through manual back office audits. After a proof of concept, technicians now photograph the cabinet, distribution point and modem or ONT with a smartphone, and an image recognition model flags problems such as unconnected fibers, wrong color coding and cable paths that break the rules. IQGeo's case study says the solution is already analyzing more than 3 million installations and reaches 98% accuracy on visible defects. Both figures are IQGeo's own claims.

After building Iris, an Agentforce answer agent used by 6,000 contact center reps and 500 retail store associates, Bouygues Telecom's next step is extending that same agentic capability to 10,000 field technicians. Salesforce's case study says Field Service and Operations will give technicians the context to arrive at a job prepared, resolve issues faster and complete more jobs per day, with guidance offered before, during and after each visit, and describes this as designed to add 10,000 more service appointments a day without growing the workforce. The case study states this as a planned next phase of the program rather than a completed or measured field rollout.

Bouygues Telecom built Iris, an employee facing agent on Salesforce Agentforce, over a rewritten knowledge base of more than 500 articles and a unified customer profile. Its 6,000 service reps ask Iris questions about billing, technical issues and promotions during calls, and the same answers are now available to associates in 500 retail stores. Before launch, Bouygues Telecom required Iris to exceed 90% accuracy or outperform a supervisor; Salesforce reports 95% on day one. Reps stay in control of what the customer hears.