Turkish Airlines, through its technology company Turkish Technology, set out to build an AI-ready foundation that could support many teams and use cases across the business. The goal was to move from isolated experiments to an AI-driven organization where every business domain could run machine learning (ML) and generative AI (Gen AI) projects.

To do this, they needed to:

• Handle large and growing data volumes.
• Give data scientists managed, self-service access to data and compute.
• Automate workspace creation and standardize deployment processes.
• Introduce a cloud-ready, container-based orchestration layer.

After evaluating 10 vendor solutions, Turkish Technology selected Red Hat OpenShift AI, implemented on bare metal, on-premise, with support from a team of five Red Hat consultants. This platform now provides:

• A container orchestration layer that manages GPU and CPU resources.
• Automated creation of customized development environments and workspaces.
• Integrated data access via the Dremio distributed query engine, which stores curated data from many sources.
• Standardized pipelines, monitoring, and alerting for AI models.

With this setup, Turkish Airlines has been able to scale to more than 60 live AI models covering use cases such as real-time dynamic pricing, payment fraud detection, ground-time predictions, tail assignments, and on-time performance predictions. The same platform also runs multiple Gen AI use cases focused on employee experience and productivity.

Adopting Red Hat OpenShift AI has delivered both operational and financial impact for Turkish Airlines.

Key operational outcomes:

• Workspace creation time cut from hours to minutes, allowing data scientists to start experimentation much faster.
• AI model deployment times reduced by about half, thanks to standardized templates, automated processes, and self-service deployment.
• Roughly 80% of AI project time that is typically spent on data gathering and preparation is now supported by automated data connections and a standardized data layer, reducing manual work.
• More than 200 employees are now working on AI-based development, including “citizen data scientists” in business units.
• Over 60 live AI models are in production, covering revenue optimization, operations, fraud detection, and employee productivity.

Financial impact:

• The company targets over USD 100 million in financial impact from its AI projects, driven by higher revenue, lower operational costs, and efficiency gains.

Beyond the numbers, OpenShift AI has helped Turkish Airlines:

• Reimagine AI as a shared capability that “every corner of the business” can use.
• Reduce risk and overhead through autoscaling, self-healing, and controlled access to compute and data.
• Standardize best practices so that once a problem (for example, a data cleansing issue) is solved, it can be turned into a reusable template for others.

Turkish Airlines approached culture change and technology change together, using OpenShift AI as an enabler rather than just a tool.

1. Empowering “citizen data scientists”

• The CEO asked business departments to deliver their own ML and Gen AI projects, not just rely on central teams.
• With OpenShift AI, business users and data scientists can spin up workspaces quickly and safely, without risking the stability of shared environments.
• Red Hat Consulting provided one-to-one mentorship, helping teams adopt standard practices and build confidence in the platform.

2. Making experimentation safer and faster

• Previously, trying new packages or extensions could break the entire development environment. Now, standardized images and templates isolate experiments and reduce risk.
• Data scientists can easily download and test new large language models (LLMs) and share what works.
• When someone solves a recurring problem (for example, a data cleansing challenge), Yavuz’s team can turn that solution into a reusable image or template for others.

3. Structuring access and governance

• OpenShift AI automatically allocates access to compute resources and data sources when a new environment is created.
• Access is limited to only the data and compute each user needs, with integration to Active Directory for consistent identity management.
• Automated processes and standardized templates help ensure regulatory requirements are met and reduce manual configuration risk.

4. Treating AI as a shared business capability

• OpenShift AI is positioned as a common platform where any department can initiate AI projects on demand.
• AI is used across revenue, operations, fraud, and employee productivity use cases, reinforcing that it is a cross-company capability, not a niche tool.
• This approach is helping Turkish Airlines reshape how AI is adopted in aviation, with the aim of making AI a commodity capability across the organization.