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In the latest episode of our Energy Transition Talks series, CGI Vice-President, Consulting – Data and Analytics Doug Leal discusses with Peter Warren the evolving landscape of data use in the energy and utilities sector, particularly in light of new AI applications. In the first instalment of this two-part conversation, they explore the challenges of scaling AI models, the move away from experimentation toward practical solutions and two key approaches to data management: the Data Lakehouse and the Data Mesh—both of which are shaping the future of data strategies’ success.

Utility organizations are facing increasing pressure to leverage data effectively for decision-making. This involves the integration of various data sources, such as Advanced Metering Infrastructure (AMI) and outage management systems, to enhance operational insights. While some organizations are already progressing in this area, Doug says, many are still in the early stages of their data journey.

Doug and Peter discuss two distinct approaches to AI: one that treats it as a novel tool to explore, and another that focuses on practical problem-solving. The latter, Doug says, is essential for developing a strategic approach to AI implementation, ensuring that solutions are not only effective for immediate challenges but also adaptable for future developments

“We need to be able to build a model or any type of AI solution in a way that will enable the organization to scale—not only scale that model for production, but also for everything that comes after that model, the innovation that comes after that model.”

The challenge of transitioning from proof of concept (POC) to production

Typically, a business unit recognizes the potential of a technology or model and decides to invest further. However, without a well-defined operational process to transition from proof of concept (POC) or proof of value to full production, this can create significant challenges and bottlenecks.

As Doug shares, only 53% of models successfully progress from POC to production, making it an expensive endeavor when roughly half fail to deliver results.

Shifting focus to Minimal Viable Products (MVPs) and practicality

Peter agrees, citing a current client’s approach that skips the POC entirely, jumping ahead to develop minimal viable products (MVPs) right away. He explains their strategy involves creating solutions that are aligned with their organizational goals and can be effectively scaled. This ensures that the IT team can support the growth of these products and that the business can derive tangible value from them.

Doug has also noticed a shift in mindset among clients. As he sees it, there’s a growing emphasis on how to effectively transition ideas into production rather than just experimenting, reflecting an increased understanding of the importance of assessing the real value and return on investment for these initiatives. Given the substantial costs associated with infrastructure, data scientists and machine learning engineers required for model development, organizations are increasingly cautious about treating these efforts as mere experiments.

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In the latest episode of our Energy Transition Talks series, CGI Global Industry Lead for Health and Life Sciences Ben Goldberg joins Peter Warren to discuss the interdependence between healthcare and energy systems, emphasizing the need for a balanced approach to ensure a healthy society. Specifically, they examine the interplay between ecosystems and supply chains, the emergence of smart, “green hospitals,” and how data innovation and digital twins are driving sustainable, resilient healthcare.

Digital twins and “triplets” in healthcare

While hospitals play a vital role in healthcare, they often contribute significantly to emissions due to aging infrastructure and inefficient buildings. For example, Ben points out that many hospitals have been around for decades, and while some modernization efforts have been made, they are still not energy friendly. This, he says, is an opportunity for new technologies to enter the mix.

Notably, digital twins—which create digital representation of physical assets—have gained traction in healthcare. Moving beyond just monitoring energy consumption, digital twins offer compelling use cases, such as providing visibility into the patient journey and help address outcomes. As Ben highlights, the ability to mirror the physical world digitally through digital twins has numerous facets and opportunities within the healthcare sector.

Sharing a term coined by Diane Gutiw, a leader in AI and digital twins at CGI, Peter raises the use cases for “digital triplets,” referring to using three interconnected digital twins:

1. A twin modeling the patient’s health and wellbeing
2. A twin modeling the operations of the healthcare facility itself (energy use, HVAC systems, etc.)
3. A third twin analyzing the causes and effects between the first two twins.

This model allows for optimizing not just patient care, but the facility's energy efficiency and sustainability as well. For example, Ben and Peter discuss the fact that "green hospitals" are being built globally to produce their own electricity and hydrogen fuel, while using digital twins to intelligently control heating, cooling, lighting, and more based on patient occupancy levels.

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In part two of the Energy Transition Talks discussion between Eurelectric’s Head of Energy Policy, Climate and Sustainability Paul Wilczek and CGI expert Peter Warren, they turn their focus to the opportunities and challenges of localized energy production, the role AI and new technologies play in balancing decentralized power grids and the long-term benefits of decarbonizing and electrifying the energy sector.

The renewable energy surge in Europe

Localized energy production and renewable energy is increasing, as energy and security of fossil fuels coming from more volatile regions face increased disruption and costs. Referencing various studies, projections and European Commission publications, Paul indicates that the deployment of renewable energy sources—particularly solar photovoltaic (PV) and onshore/offshore wind power—is expected to experience a massive surge in Europe across all scenarios.

As Paul explains, this rapid growth in localized renewable energy production offers several advantages:

· Homegrown electricity production: Europe will have a significant portion of its electricity generated domestically, reducing dependence on imports from potentially unreliable foreign partners, thereby enhancing energy security and supply reliability.

· Decarbonization: Renewable energy sources like solar and wind are carbon-free, contributing to the decarbonization of Europe's electricity sector.

· Price predictability: Domestically produced renewable energy can provide more predictable and stable power prices, reducing volatility associated with imported energy sources.

At the same time, he points out, the projected surge in renewable energy deployment presents challenges too: such rapid growth also necessitates addressing the challenges of variability and the need for substantial investments.

The role of AI and new technologies in managing the energy system efficiently

While traditional energy generation like hydroelectric power will continue to play a role, Peter says, the major shift towards renewable but volatile sources like wind and solar impacts not just the volume of energy produced, but also the frequency and grid balancing when the sun shines or wind blows. New technologies, he suggests, will play a supporting role in transitioning to distributed energy resources (DER) production.

Paul agrees, suggesting that a decade ago, few predicted the current dominance of wind and solar energy. Technologies like biomass and geothermal were expected to have a bigger role. However, the plummeting costs of wind and solar have made them the clear winners for now.

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