Uploaded July 2026 | Updated September 2026, 3 weeks ago
*Featured in this video:* Stephen Lee, Head of Enterprise Data Engineering and Metadata Management at TELUS
*Executive summary:* Telco business TELUS, based in Canada, provides cell phone and internet service along with Digital, Health, and Agriculture & Consumer Goods service areas. It’s evolved beyond a traditional telecom provider, and now, as a global communications tech company, TELUS continually innovates for better customer experiences. TELUS built a unified Agentic Data Cloud with Google Cloud and BigQuery as its central engine to help engender trust in data. With that centralized platform, TELUS added security and governance to its data, and brought Gemini Enterprise for CX to its call centers. TELUS also built Fuel iX, its self-serve AI platform that lets any employee choose from vetted models to create their own innovative use cases.
*Challenge:* To scale generative AI, TELUS needed to dismantle legacy walled gardens and silos across its diverse business units. Legacy, end-of-life on-premises data platforms left the company with multiple sources of truth, creating a trust gap that blocked the adoption of autonomous AI agents and real-time decision-making.
*Solution:* TELUS moved to Google Cloud, consolidating over 14 petabytes of data into BigQuery to establish an agentic data cloud. The team uses Knowledge Catalog (formerly Dataplex) to automate data quality and governance, alongside BigQuery Analytics Hub for instant, zero-copy data sharing. Transitioning to a real-time system of action, TELUS deployed Gemini Enterprise for Customer Experience (CX) to resolve customer issues proactively before a complaint is ever filed. The team also uses this real-time architecture to build and scale self-healing networks that automatically resolve faults before subscribers are impacted.
*Results:* By building a modern, unified data infrastructure and a flexible generative AI platform, TELUS has empowered over 57,000 team members with AI access to create more than 13,000 custom solutions. This strategy has driven tens of millions of dollars in operational savings through proactive support, reduced call volumes, and sped up software engineering velocity by 30%.
*Key takeaways and highlights from our interview with Stephen Lee, Head of Enterprise Data Engineering and Metadata Management at TELUS:*
→ “That's what great data engineering is all about: Being able to cut through the noise and empower our business with insights so that users can make smart decisions, even in times of uncertainty.”
→ “You can only have meaningful AI if you have a solid data foundation. We unified our customer data in an agentic data cloud, and now our team members, instead of waiting for the data, can action it in real time to drive business outcomes.”
→ “AI is only as good as its data foundation and the reference data. By leveraging reference information that is specific to TELUS, we can ensure that our AI services provide the right information, context, and timing for everybody to use at TELUS.”
→ “By moving to Google BigQuery and creating one unified data foundation for customer information across the enterprise, we're able to increase trust in the data. We've also created a self-serve layer in Google Cloud platform so all TELUS team members can innovate and drive new ideas using data and AI to create business value.”
*Google Cloud products used:* Gemini Enterprise Agent Platform, Gemini Enterprise for CX, Gemini, BigQuery, Cloud SQL, Analytics Hub, Knowledge Catalog (Dataplex)
*Learn more:*
→ TELUS: Unleashing workplace innovation and engineering excellence with AI cloud.google.com/customers/telusai?hl=en&e=48754805
→ How TELUS is powering growth and productivity with Google cloud.google.com/blog/products/chrome-enterprise/how-telus-is-powering-growth-and-productivity-with-google
→ Gemini Enterprise for Customer Experience cloud.google.com/gemini-enterprise-cx
*Featured in this video:* Stephen Lee, Head of Enterprise Data Engineering and Metadata Management at TELUS
*Executive summary:* Telco business TELUS, based in Canada, provides cell phone and internet service along with Digital, Health, and Agriculture & Consumer Goods service areas. It’s evolved beyond a traditional telecom provider, and now, as a global communications tech company, TELUS continually innovates for better customer experiences. TELUS built a unified Agentic Data Cloud with Google Cloud and BigQuery as its central engine to help engender trust in data. With that centralized platform, TELUS added security and governance to its data, and brought Gemini Enterprise for CX to its call centers. TELUS also built Fuel iX, its self-serve AI platform that lets any employee choose from vetted models to create their own innovative use cases.
*Challenge:* To scale generative AI, TELUS needed to dismantle legacy walled gardens and silos across its diverse business units. Legacy, end-of-life on-premises data platforms left the company with multiple sources of truth, creating a trust gap that blocked the adoption of autonomous AI agents and real-time decision-making.
*Solution:* TELUS moved to Google Cloud, consolidating over 14 petabytes of data into BigQuery to establish an agentic data cloud. The team uses Knowledge Catalog (formerly Dataplex) to automate data quality and governance, alongside BigQuery Analytics Hub for instant, zero-copy data sharing. Transitioning to a real-time system of action, TELUS deployed Gemini Enterprise for Customer Experience (CX) to resolve customer issues proactively before a complaint is ever filed. The team also uses this real-time architecture to build and scale self-healing networks that automatically resolve faults before subscribers are impacted.
*Results:* By building a modern, unified data infrastructure and a flexible generative AI platform, TELUS has empowered over 57,000 team members with AI access to create more than 13,000 custom solutions. This strategy has driven tens of millions of dollars in operational savings through proactive support, reduced call volumes, and sped up software engineering velocity by 30%.
*Key takeaways and highlights from our interview with Stephen Lee, Head of Enterprise Data Engineering and Metadata Management at TELUS:*
→ “That's what great data engineering is all about: Being able to cut through the noise and empower our business with insights so that users can make smart decisions, even in times of uncertainty.”
→ “You can only have meaningful AI if you have a solid data foundation. We unified our customer data in an agentic data cloud, and now our team members, instead of waiting for the data, can action it in real time to drive business outcomes.”
→ “AI is only as good as its data foundation and the reference data. By leveraging reference information that is specific to TELUS, we can ensure that our AI services provide the right information, context, and timing for everybody to use at TELUS.”
→ “By moving to Google BigQuery and creating one unified data foundation for customer information across the enterprise, we're able to increase trust in the data. We've also created a self-serve layer in Google Cloud platform so all TELUS team members can innovate and drive new ideas using data and AI to create business value.”
*Google Cloud products used:* Gemini Enterprise Agent Platform, Gemini Enterprise for CX, Gemini, BigQuery, Cloud SQL, Analytics Hub, Knowledge Catalog (Dataplex)
*Learn more:*
→ TELUS: Unleashing workplace innovation and engineering excellence with AI cloud.google.com/customers/telusai?hl=en&e=48754805
→ How TELUS is powering growth and productivity with Google cloud.google.com/blog/products/chrome-enterprise/how-telus-is-powering-growth-and-productivity-with-google
→ Gemini Enterprise for Customer Experience cloud.google.com/gemini-enterprise-cx
