How artificial intelligence and machine learning can help revolutionize operations and reinvent the future of energy and utilities

Artificial intelligence (AI) and machine learning-based (ML) intelligent solutions can offer a flexible, intuitive and efficient way to solve day-to-day challenges, bring new insights and drive operational excellence. In my blog, I would like to share recommendations on how AI/ML can help the energy and utilities sector reinvent for the future.

Pandemic speeds transformation

The pandemic has led to accelerated pressure on energy and utilities to decarbonize and increase green production, resulting in the need to entirely rethink the energy value chain. This shift is driving new investments in adopting a customer-centric business model and innovating the energy transition to derive value for the increasingly digital future.

Our interviews with executives in the 2021 Voice of Our Clients – Energy & Utilities also reflects this trend. The priority for organizations is to become increasingly digital and optimize investments and operations by automation:

AI and ML can revolutionize operations 

Artificial intelligence and machine learning are key enablers for automation, digitization and analytics, here are some use cases:

• Robotic process automation to enhance business processes and customer experiences.
• Computer vision and AI to revolutionize supply chain and grid management for utilities.
• Hyper-automation to provide data and insights quickly for faster and more precise business decision-making.
• Data and predictive analytics to provide digital insights to drive business growth.

At CGI, we have been successful in accelerating several of our client’s AI/ML journeys, including:

• Monitoring and controlling renewable assets in real-time for a Portuguese utility. CGI’s Renewables Management System (RMS) helps achieve real-time monitoring and remote control of assets. CGI RMS provided a seamless switch to remote working during the pandemic, and the RMS mobile tool improved communication between team members.
• Transforming business processes through outsourcing, consolidation and automation for a large European utility to improve performance, cost to serve, quality of service and customer experience.
• Assisting a global utility in accelerating their move to Net Zero, instilling business agility, adopting a value-based business-IT operating model, and deploying innovative digital and agile work methods.
• Helping a North American power company move from a monopolistic to competitive model, including redesigning of the business models and OT/IT (operational technology/information technology) infrastructure and automation and cloud‑based solutions.

 5 Best practices to adopt AI and ML to improve operational performance

1. Take small steps to create quick wins

Driving incremental improvements and enhancements for immediate results will improve employee morale and garner the momentum for greater transformation efforts. It will also increase AI/ML transformation adoption among employees and within the organization. The major challenges to look out for are managing budget constraints and driving cultural change.

2. Develop a practical approach to evaluate and choose intelligent AI/ML strategy

Having a well-defined implementation strategy will drive results. We can take inspiration from the space industry, which uses space data and AI to reduce outages and predict and respond to floods, fires, oil spills and leaks.

3. Invest time in identifying and optimizing the most important business processes for automation

Not every problem can be solved using AI/ML. Hence it is vital to take the time to choose and prioritize use cases that will derive immediate business benefits before implementation.

4. Develop dedicated and skilled leadership and governance for intelligent AI/ML

Data and predictive analytics continue to be among the top priorities and areas for innovation and investment for the next few years. Collaboration and business-IT alignment fuel digital results and digital leaders excel at this over business leaders. Investing in the right people and mindset will drive change.

5. Motivate your workforce, upskill their capabilities, and offer a supportive ecosystem

Skilled resources with technology and business acumen are key in implementing AI/ML strategy. Understanding the core business challenge and offering the right solution will build stakeholder trust. Hence it is crucial to invest in developing and motivating the workforce to enhance their skills and knowledge.

The energy transition requires several investments, the most important being identifying the right partner to drive change. CGI’s industry expertise and portfolio of solutions can help you get started. Get in touch with us to start a conversation.