Lloyds Banking Group has transformed how its teams develop and deploy AI through Atlas, a cloud-native ML and AI platform that embeds governance, automation, and collaboration into every stage of delivery. By replacing fragmented ways of working with a single operating model, Atlas has enabled AI to scale safely across the organisation while delivering significant business value.
As organisations accelerate their investment in AI, many face the challenge of moving promising ideas into production without compromising governance or resilience. Lloyds Banking Group addressed that challenge by creating Atlas, a cloud-native machine learning and AI platform that fundamentally changed how data scientists, engineers, risk specialists, and business teams work together.
Rather than viewing Atlas as a technology platform, the bank designed it as a new operating model for AI delivery. Built on Google Cloud Platform, it provides a consistent route from experimentation to production, embedding governance, security, and Responsible AI controls directly into automated workflows while giving teams the flexibility to innovate at pace.
Building a new operating model for AI
Atlas was created to overcome the limitations of fragmented AI development, where manual handovers, inconsistent deployment practices, and specialist dependencies slowed innovation and made scaling increasingly difficult.
The platform standardises the end-to-end AI lifecycle, enabling teams to move seamlessly from experimentation to production through automated pipelines and self-service tooling. Governance is no longer treated as a separate stage in the process; security, compliance, lineage, and Responsible AI checks are built into every deployment through policy-as-code.
The platform supports collaboration across Lloyds Banking Group’s hybrid data estate, allowing teams to work consistently across cloud and on-premises environments while following delivery standards for both traditional ML and Generative AI.
“A standout example of redefining what good data work looks like at scale. Skills, ownership and purpose are embedded, making work more meaningful while delivering better customer outcomes.” – Judges’ comments
Delivering AI at enterprise scale
By changing how teams collaborate around data and AI, Atlas has created a more predictable, scalable approach to delivering innovation.
Key outcomes include:
- Enabled the delivery of 50 Generative AI use cases during 2025.
- Contributed £50 million in business value.
- Supported 2x year-on-year growth in deployed AI models.
- Established a single operating model for both ML and Generative AI.
- Embedded governance, security, compliance, and Responsible AI controls into every deployment.
- Reduced reliance on specialist platform teams through self-service workbenches and automated deployment pipelines.
Data scientists, engineers, cloud teams, security specialists, risk teams, and business stakeholders now work within a shared framework, replacing fragmented processes with consistent ways of working that accelerate delivery while maintaining robust governance.
Significantly, Atlas has made AI delivery predictable. Leaders can invest with confidence, knowing that new AI capabilities can be deployed consistently, securely, and at scale without creating additional operational risk.
A secure and scalable future
Atlas demonstrates that transforming AI delivery requires more than modern infrastructure. By treating MLOps as a product, embedding governance into automation, and creating shared standards across technical and business teams, Lloyds Banking Group has fundamentally changed how AI is developed across the organisation.
The platform has established strong foundations for the future. As Generative AI continues to evolve, Atlas ensures new technologies are introduced within the same trusted operating model, avoiding the creation of disconnected tools or inconsistent governance practices.
The DataIQ judges recognised Atlas as an outstanding example of new ways of working with data because it combines agility with accountability. By creating a single, enterprise-wide approach to AI delivery, Lloyds Banking Group has shown how organisations can scale innovation without sacrificing trust, setting a benchmark for how modern data and AI platforms should enable collaboration across the business.
