Case Study: Enbridge’s Journey to Cloud and AI Integration

Enbridge Inc. stands as a critical player in North America’s energy infrastructure, transporting a significant portion of the region’s crude oil and natural gas. As the largest natural gas utility in North America, servicing over 7 million customers, Enbridge has experienced rapid growth, particularly between 2015 and 2020, driven by mergers and acquisitions. This growth led to a 150% increase in its technology footprint, necessitating a strategic transformation to manage and scale its operations effectively. To address these challenges and support its business goals, Enbridge embarked on a comprehensive cloud migration journey, leveraging artificial intelligence (AI) to revolutionize its operations.

Key Takeaways

  • Enbridge migrated 74% of its workloads to the cloud, resulting in a 66% reduction in its carbon footprint.
  • The transition reduced critical service outages by 70% and enhanced overall infrastructure availability to 99.5%.
  • AI applications have been pivotal in enhancing operations, safety, customer experience, and environmental performance.
  • Upskilling initiatives have ensured that 60% of technology information services employees now possess cloud training and agile development skills.
  • The company has significantly reduced infrastructure costs and deployment times, achieving substantial operational efficiencies.


Enbridge’s transformation began with a strategic focus on reducing technical debt and improving application reliability through cloud adoption. This approach aimed to streamline IT operations, mitigate operational risks, enhance business agility, and boost operational efficiencies. The migration involved consolidating data centers and shifting workloads to the cloud, alongside harnessing the power of data for business intelligence. By integrating advanced AI solutions, Enbridge sought to drive innovation and create a more resilient and efficient technological landscape.


The implementation phase saw Enbridge consolidate 13 data centers and migrate 594 applications to the cloud, including critical workforce productivity tools. This move resulted in decommissioning 9,050 servers and establishing a highly reliable hybrid environment. The company’s data transformation efforts involved moving siloed data to a cloud-based marketplace, where a data catalog and quality standards were implemented. Advanced data governance and security measures ensured robust protection of data assets. Additionally, Enbridge integrated cloud-native AI and machine learning tools to generate valuable insights and predictions for demand forecasting, asset optimization, and anomaly detection. AI-powered code assistants and productivity applications were deployed to enhance efficiency and drive innovation.


The results of Enbridge’s cloud migration were remarkable. Infrastructure deployment times were slashed from four months to just four hours, while “day 1” integration times were reduced by 30%. This transformation led to a 50% reduction in infrastructure costs, which would have otherwise increased by 52%, and substantial savings in network bandwidth. The company achieved a 66% reduction in its carbon footprint by cutting the number of data centers from 17 to four and shifting workloads to cloud data centers powered by renewable energy. Service reliability also improved significantly, with a 70% reduction in critical service outages and an overall availability rate of 99.5%.

Challenges and Barriers

Despite these successes, Enbridge faced several challenges during its transformation. The complexity of managing and scaling multiple platforms, applications, and data centers, particularly with legacy systems, posed significant risks. Meeting new regulatory demands, especially in cybersecurity, required stringent measures and rapid adaptation. Additionally, upskilling the workforce to ensure proficiency in cloud technologies and agile development demanded substantial investment in training and development.

Future Outlook

Looking ahead, Enbridge’s cloud and AI journey positions the company for continuous innovation and efficiency. The company is committed to achieving zero emissions by 2050, with cloud migration playing a crucial role in this sustainability target. Enbridge plans to further expand its AI capabilities, leveraging generative AI platforms to drive innovation in operations, safety, and customer experience. As AI technology evolves, Enbridge aims to remain at the forefront of these advancements, supporting the energy transition and catalyzing further innovation in the sector.

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Cloud migration drives AI revival at Enbridge

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