Opportunity and Trends: Why Energy Operators Are Turning to AI and Robotics
The global momentum around AI in energy operations is undeniable and accelerating. According to Markets and Markets, the AI market for energy (including robotics) is currently valued at 6.2$ billion, with expectations to more than double to 13.2$ billion by 2029 (CAGR 16%). Deloitte’s 2024 Energy Tech Survey reinforces this trajectory, with 65% of companies planning to increase investment in AI and robotics for operations and maintenance (O&M) use cases.
For Oil & Gas specifically, Fortune Business Insights forecasts a CAGR of 6.81% in the robotics inspections market – reaching 1.3$ billion by 2032. These figures show a clear trend: energy organizations are shifting rapidly toward automation to address performance, safety, and workforce challenges.
So what’s behind this transformation?
Integrated, Scalable Intelligence
Thanks to advances in autonomous mobile robots (AMRs), AI, drones and cloud-based systems, companies can now integrate robotic inspection solutions into existing or new infrastructures. These technologies – layered with AI models like computer vision – enable high-fidelity asset monitoring for corrosion, leaks, and anomalies in real time.
Addressing the Workforce Gap
As experienced personnel retire, energy companies are facing growing skill shortages in inspection and O&M roles. Robotics is filling the gap: offering consistent, high-quality inspections while reducing operational burden on human teams.
Safety at the core
From high-risk areas with extreme temperatures to zones with gas, dust, or confined spaces, autonomous robots like ANYmal can operate where humans shouldn’t. This capability is a core driver of demand, as organizations prioritize both worker safety and uptime.
In short, the need for safer, smarter, and more scalable asset operations is reshaping the industry. Robotics and AI are no longer aspirational, they are becoming fundamental.
ANYbotics, GE Vernova and AWS: A strategic collaboration for Autonomous Inspection
To advance this shift, we’ve entered into a formal technology collaboration with GE Vernova’s Power & Energy Resources Software (PERS) business and AWS. This partnership integrates our autonomous legged robot ANYmal with GE Vernova’s industry-leading Asset performance Management (APM) suite via the Autonomous Inspection Application, leveraging AI/ML and scalable cloud infrastructure.
Our collaboration with GE Vernova and AWS reflects a shared vision: empowering industrial operators to unlock safer, smarter, and more scalable asset intelligence. By integrating ANYmal’s autonomous inspection capabilities with GE’s APM and AWS infrastructure, we’re bridging a gap between robotics, AI, and operational excellence—bringing next-gen transformation to the industrial realm.
— Oussama Darouichi, Global Director of Strategic Partnerships, ANYbotics
I am thrilled to share our vision for transforming the traditional inspection landscape. Autonomous Inspection represents a significant leap forward by automating and enhancing the image capture and analysis process, driven by cutting-edge AI/ML models developed by GE Vernova. This innovative solution converts images into valuable time-series data, enabling deep data analysis and facilitating actionable insights. By integrating with APM applications, we are not only boosting operational efficiency but also empowering operators with timely alerts and access to image logs for verification, ensuring enhanced safety and decision-making. We are confident that Autonomous Inspection will redefine inspection standards, promoting transparency, accuracy, and ultimately elevating the performance and safety of industrial facilities.
– says Mazen Younes, Sr. Director of Platform Product Management and AI Strategy, GE Vernova
Bridging Robotics, AI, and Asset Intelligence
SaaS as a Scalable Digital Backbone
GE Vernova’s cloud-native APM platform leverages AWS microservices (S3, SageMaker, EKS on Fargate, and more) to centralize data and accelerate analytics. This architecture also enables smooth integration with ANYbotics’ autonomous inspection capabilities, ensuring image data from robots can be processed as structured time-series input for actionable insight.
From Reactive to Predictive Maintenance
Using AWS SageMaker, GE Vernova’s APM can now ingest and analyze unstructured image data – captured by ANYmal – in real time. When combined with APM SmartSignal and other modules, this empowers organizations to move from reactive repairs to predictive and even prescriptive maintenance strategies
High Fidelity On-the-Ground Data Collection
At the heart of this solution is ANYmal – designed to autonomously navigate hazardous or hard-to-access environments and collect inspection data with precision and repeatability.
This rich, multi-modal data is transmitted via AWS cloud infrastructure and made available within GE Vernova’s APM platform – enabling real-time insights, asset health tracking, and data-driven decision-making.
Technical Solution Overview:
- GE Vernova’s SaaS application, Autonomous Inspection, leverages computer vision models in SageMaker to ingest thermal, leak, gauge, and other visual inputs from fixed or mobile cameras.
- Images from asset management programs across energy enterprises are captured at the edge on local servers and uploaded to a customer-specific AWS S3 bucket via AWS Storage Gateway and ANYbotics APIs.
- Captured and stored images are then made accessible via ANYbotics APIs.
- Via Robotics-as-a-services (RaaS), data can be integrated into GE Vernova’s APM in the form of time series data.
- After this time series data is processed via deep learning CNN, it is stored in Amazon RDS Postgres.
- Then, using AWS Sagemaker in GE Vernova’s Autonomous Inspection application, pre-trained ML models analyze the images and generate inferences.
- Autonomous Inspection is also able to connect with enterprise resource planning (ERP), enterprise asset management (EAM), and ultimately can provide data for GE Vernova’s other APM applications, such as APM Health, APM SmartSignal and APM Integrity.
- Access alerts via APM, which is an integration of the data points from the image with a determined asset model and time series to provide the UI.
- Work in progress to further utilize AWS Generative AI services, Bedrock or Q, to submit natural language processing (NLP) queries to prompt from the data knowledge base.
AWS is looking forward to supporting how energy organizations use cloud technology to gain more visibility into their asset performance. The shared collaboration between AWS, ANYbotics and GE Vernova gives organizations access to technology that can help to change how they work.
– says Andrew Stulbarg, Sr. Sales Leader North American Energy & Utilities from AWS states.
Final Thoughts: Advancing the Autonomous Future of Energy Operations
At ANYbotics we believe the future of industrial inspections is autonomous, intelligent, and safe. This collaboration with GE Vernova and AWS marks a major leap towards that vision: allowing energy operators to inspect more often, respond faster and act with greater confidence.
Together we shape a new benchmark for industrial performance where robots don’t just inspect assets, but deliver the data foundation for more reliable, efficient, and sustainable operations.