GE Aerospace’s latest strides in artificial intelligence have been significantly shaped by its Data Sciences and Analytics teams in Bengaluru, India. In a recent statement, Dinakar Deshmukh, Vice-President of Data Sciences and Analytics at GE Aerospace, acknowledged the critical contribution of Indian engineers to the development of one of GE’s most promising tools—AI Wingmate, a custom-built generative AI assistant.

The Bengaluru Brainpower Behind GE's Digital Transformation

The John F. Welch Technology Centre (JFWTC) in Bengaluru, GE’s largest R&D centre outside the US, has long been an innovation hub for the company. The data science and engineering teams based here have played a pivotal role in the creation and development of digital twin technology—a concept that involves building a virtual replica of an aircraft engine to track real-time performance, predict maintenance needs, and prevent failures.

This digital twin system, now integrated across GE Aerospace’s service platforms, has emerged as a core enabler for predictive analytics and asset optimisation, helping airline clients around the globe.

The Rise of Generative AI and the Birth of AI Wingmate

The landscape of artificial intelligence shifted dramatically with the launch of ChatGPT by OpenAI in November 2022. This marked the beginning of a new era for AI adoption across industries, including aerospace. GE Aerospace recognised the transformational potential of generative AI, but also flagged concerns over IP leakage and data security.

To overcome these concerns, GE Aerospace chose not to rely on open platforms. Instead, it partnered with Microsoft to build an in-house solution called AI Wingmate. This customised generative AI assistant is designed to enhance employee productivity, deliver superior customer support, and, most importantly, secure proprietary information.

AI Wingmate ensures that sensitive engine data, customer diagnostics, and research are kept within the enterprise firewall, giving GE Aerospace better control over intellectual property while still leveraging the vast capabilities of generative AI models.

Engine Health Monitoring and Predictive Maintenance

According to Mr. Deshmukh, AI is driving significant gains in engine health monitoring, enabling the company to:

• Reduce lead times for issue detection

• Improve failure prediction accuracy

• Lower false positives, which had historically plagued engine performance analytics

By applying AI models to historical flight and engine data, GE can detect anomalies much earlier, often before they manifest into serious maintenance problems. This is vital in an industry where engine downtime directly translates to financial losses and customer dissatisfaction.

AI Applications Beyond Wingmate

The impact of GE’s AI journey isn’t limited to AI Wingmate. The India-based team has developed advanced inspection tools, including blade inspection technology, that combine AI with high-resolution imaging to detect cracks or wear in turbine blades—a crucial component of jet engines.

Similarly, digital twins are now being used not just for monitoring but also to simulate real-world flight conditions, which help engineers test improvements virtually before applying them in physical models. This dramatically shortens R&D cycles and improves safety and efficiency.

India's Central Role in GE Aerospace’s AI Strategy

Mr. Deshmukh credited the Bengaluru team’s proactive culture and deep expertise in both AI and aerospace systems for helping GE stay ahead of the curve. JFWTC has been leading several innovation programmes, not just in software development, but also in hardware-software integration, a key requirement in aerospace applications.

With over 5,000 engineers and scientists, the centre is playing a strategic role in GE’s global transformation, with teams contributing to initiatives like:

• Condition-based engine maintenance

• Real-time flight analytics

• AI-powered diagnostic platforms

Security and Innovation: A Balanced AI Approach

A major concern for companies leveraging generative AI is data privacy and model security. With Wingmate, GE Aerospace has created a sandboxed environment, offering similar capabilities to ChatGPT but entirely secured within its enterprise ecosystem.

Built in collaboration with Microsoft, Wingmate runs on a private cloud infrastructure, ensuring data never leaves GE’s control. It can process natural language queries, summarise complex technical documents, assist in coding, and support decision-making for engineers and service teams.

Business Value and Future Outlook

Mr. Deshmukh noted that Wingmate has already shown strong ROI by improving internal workflows and reducing time spent on repetitive tasks. This allows highly skilled engineers to focus more on innovation and customer engagement.

Looking forward, GE plans to expand Wingmate’s use cases into customer-facing operations, supply chain management, and even training modules for aerospace technicians. The company is also exploring how generative AI can support autonomous flight diagnostics, aligning with the broader industry move toward AI-enhanced aviation.

Conclusion: India at the Heart of GE's AI Revolution

The success of AI Wingmate underscores the strategic importance of India in GE Aerospace’s innovation roadmap. By blending domain expertise in aerospace with cutting-edge AI capabilities, the Bengaluru team is delivering solutions that transform engine performance, improve operational reliability, and protect critical intellectual property.

GE Aerospace’s approach demonstrates that with the right safeguards, generative AI can unlock unprecedented value, and with secure platforms like AI Wingmate, organisations can innovate without compromising on data protection.

As the aerospace industry continues to evolve, AI-led digital transformation, powered by talent hubs like Bengaluru, is poised to redefine the future of engine technology and aircraft maintenance.

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