The workforce of the future in energy: From challenge to transformation

Two of the energy industry’s most profound operating assumptions have forever changed. Where companies once operated with an abundance of low-cost workers and limited high-cost technology, they now face a forever labour shortage and an explosion of low-cost, highly capable automation tools. [i]

This paper follows ‘The workforce of the future in energy: Challenges ahead', and ‘The workforce of the future: Opportunities ahead', which explored the forces shaping the energy workforce of tomorrow. [ii] [iii] With those pressures established, the focus now shifts to the era of energy transition, and its implications for the workforce.

Unlike industrial energy consumers, the vast majority of whom have the flexibility to source cleaner energy, producers of energy such as oil and gas companies must actively navigate three separate energy transition challenges:

Continuing to supply traditional energy in a flat or declining market.

Diversifying into new energy opportunities and alternative fuels in the face of uncertain market demand.

Transitioning internal energy use to lower-carbon sources. [iv]

Relying on human labour exclusively to meet these challenges no longer guarantees success. The workforce of the future will have to be leaner, more specialized, and digitally savvy. [v]

It is also clear that the technology constraints of the past no longer apply. Energy firms that redesign their processes for automation-first execution will best respond to workforce shortages. A great example is Iberdrola’s latest green hydrogen plant which features end-to-end process control. [vi] Those that fail to adapt will likely struggle to compete in a shrinking talent market.

This paper explores the age of energy transition as it is shaped by the contours of the future workforce. Future papers will examine the workforce in an age of digital and the evolution of the workforce from a human standpoint.

Energy transition is a business process shift

For upstream oil and gas producers, energy transition is the triple challenge of sustaining existing production, diversifying energy products, and adopting sustainable fuels for internal use. Producers must sustain volumes at acceptable margins in a flat or declining market, to satisfy capital markets and shareholders. But with a shrinking workforce and rising labour costs, maintaining production at scale requires substituting labour for capital and manual for digital.

The challenge extends beyond production. Many producers are exploring opportunities to diversify their energy mix, whether through carbon capture, hydrogen, geothermal, renewables, and even nuclear. [vii] In some cases, emerging energy sources, such as geothermal and carbon capture, can leverage existing processes, such as drilling and completions.

However, other energy sources demand entirely new ways of working, ecosystems, and technical expertise. Even within core hydrocarbon production, companies are deploying solar-powered pumps, autonomous production, and AI-driven emissions monitoring, including industry leaders like Chevron. [viii] These shifts, in turn, require new skills in design, operations, maintenance, and commercial support, reshaping the technical and back-office workforces.

Energy transition isn’t just a technology shift—it’s a redesign of how energy is produced, managed, and monetized.

Legacy energy processes were built in an era where human execution was the default, either because automation was unavailable, regulatory frameworks prescribed processes, or economic conditions incentivized people-intensive workflows. In today’s context, simply layering automation on top of existing human-centric methods will not offset their built-in constraints.

To sustain production, companies will be forced to redesign operations for automation-first execution—rethinking how assets are managed, how compliance is tracked, and how production decisions are made.

Industrial energy management — a process that must be reinvented

For energy producers, energy transition also means using energy more efficiently within existing operations while minimizing emissions. Energy is one of the largest operating costs in the upstream, but it is also a direct driver of methane and CO₂ emissions, according to the IEA. [ix]

Engineering estimates of energy and emissions have proven consistently at variance with the reality of actual asset-level consumption and emissions. A recent study of the Permian Basin via satellite suggests emissions are double bottom-up inventory calculations. [x] Shrewd producers recognize that tracking actual energy use with greater precision can achieve cost savings, improved production and emissions reductions.

For large producers with hundreds of wells, multiple processing facilities, and vast midstream networks, manually tracking energy use and emissions at an asset level is infeasible. Yet without accurate, real-time data, companies risk misreporting emissions, overspending on energy, and sub-optimizing production.

Digital advances now make it possible to track actual energy use and emissions in real time at the asset level. Instead of relying on engineering estimates, AI-driven energy management platforms collect continuous actuals, identify inefficiencies, and make automated adjustments to optimize both consumption and production. CGI recently assisted a Canadian oil and gas company create a digital twin of a production asset to detect leaks sooner, leveraging satellite data, sensor data from the plant, and live video feeds. [xi]

Companies that embed data-driven energy and emissions optimization into their operations will surely gain a competitive edge, cutting costs while ensuring compliance with tightening emissions standards. Those that remain dependent on static models and manual interventions will find themselves increasingly exposed—both to regulatory risk and operational inefficiencies.

The role of digital and innovation in executing new processes

The shift to data-driven energy management while tackling energy transition is consistent with the broader transformation of industry: automation is the foundation of operations. The same powerful analytic tools that optimize energy use and emissions tracking are also reshaping how production is managed, how assets are maintained, and how decisions are made. Indeed, upstream companies operating in tight resource plays behave more like resource factories than wild-cat explorers, with the repeatable processes, intelligent technologies that improve operations, and resilient supply chains described by CGI's research into manufacturing. [xii]

Instead of humans collecting data, sensors and AI-driven systems provide real-time insights. Instead of manual adjustments, automated controls optimize performance in real time. Instead of compliance teams assembling emissions reports, AI compiles, verifies, and submits accurate data automatically. The model that best enables this approach is one that features the human in the middle—directing, shaping, and steering.

Digital innovation is unlocking new levels of efficiency, insight, and operational resilience.

This shift delivers both efficiency and scalability, allowing automation-first companies to manage assets at scale without expanding headcount in the traditional linear fashion.

The future workforce: smaller, smarter, and AI-first

It is evident that the upstream oil and gas workforce is undergoing a fundamental shift. Where production once relied on large field teams, manual inspections, and hands-on operations, the workforce of the future will be smaller, more specialized, and focused on managing automation.

Instead of trying to replace retiring workers one-for-one, companies should vigorously redesign work itself, deepening automation, accelerating AI usage, and adopting digital workflows so that far fewer workers can oversee larger, more complex operations. Solutions such as robotic process automation from CGI illustrate how technology can take on much of the work previously dedicated to humans. [xiii]

Within this vision of the workforce of the future, the role of the worker is changed. Instead of performing tasks manually, the workforce will design, manage, and optimize intelligent systems. This shift does not eliminate the need for human expertise—it centers humans in the middle. Investments in upskilling workers to manage automation-first operations will build a workforce that is leaner, more agile, and far more productive.

Conclusion: the companies that lead will automate first

The upstream oil and gas workforce is no longer expanding—it is being redesigned. The energy transition demands a new approach: automation-first operations, AI-driven decision-making, and a workforce built to oversee digital systems rather than execute manual tasks.

The energy transition is not just about new fuels—it is about reinventing the way energy businesses operate, and the products they offer. The companies that act now to build a smaller, smarter, AI-first workforce will define the future of the industry.

This article was co-written by the following two experts:

Geoffrey Cann, Advocate for Digital Innovation in Energy	Peter Warren, Vice-President, Global Industry Lead, Energy & Utilities, CGI

If you’d like more information on our work in this area, feel free to contact Peter.

Reference 5: [v]

National Skills Coalition. 2022. New Report: 92% of Jobs Require Digital Skills; One-Third of Workers Have Low or No Digital Skills Due to Historic Underinvestment, Structural Inequities. Washington, DC: National Skills Coalition. https://nationalskillscoalition.org/news/press-releases/new-report-92-of-jobs-require-digital-skills-one-third-of-workers-have-low-or-no-digital-skills-due-to-historic-underinvestment-structural-inequities/

Reference 6: [vi]

CGI. 2023. Enabling End-to-End Control of Europe’s Largest Green Hydrogen Plant. CGI. https://www.cgi.com/en/case-study/energy-utilities/enabling-end-end-control-europes-largest-green-hydrogen-plant.

Reference 7: [vii]

Mitsubishi Corporation. 2024. ADNOC Joins ExxonMobil and Mitsubishi Corporation’s Low-Carbon Hydrogen Project in Texas. September 4, 2024. https://www.mitsubishicorp.com/jp/en/news/release/2024/0000054472.html.

Reference 8: [viii]

Chevron, AI Boosts Profitability in the Permian Basin, December 18, 2024, https://www.chevron.com/newsroom/2024/q4/ai-boosts-profitability-in-the-permian-basin.

Reference 9: [ix]

International Energy Agency. 2023. Emissions from Oil and Gas Operations in Net Zero Transitions. Paris: IEA. https://www.iea.org/reports/emissions-from-oil-and-gas-operations-in-net-zero-transitions.

Reference 10: [x]

Brandt, Adam R., Thomas Yeskoo, Amanda Zavala-Araiza, David R. Lyon, R. Subramanian, and Steven P. Hamburg. 2020. “Airborne Measurements of Methane Emissions from Oil and Gas Production Basins in the U.S.” Science Advances 6 (17): eaaz5120. https://doi.org/10.1126/sciadv.aaz5120.

Reference 11: [xi]

CGI’s digital twin solution for Canadian oil and gas company.

Reference 12: [xii]

CGI. 2024. AI and diversification: A dual strategy powering manufacturers’ resilience. https://www.cgi.com/en/blog/manufacturing/ai-and-diversification-dual-strategy-powering-manufacturers-resilience.

Reference 13: [xiii]

CGI. 2024. Robotic Process Automation (RPA). Accessed March 26, 2025. https://www.cgi.com/en/automation/rpa.

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