Recommendations

The conservative approach of energy and utilities has served the industry well to date. But, what has worked well so far may not continue to do so in a world that demands unprecedented levels of energy infrastructure on compressed timelines, while access to talent continues to tighten. Organizations will need to be faster and more agile, all while maintaining the industry's commitment to safety and reliability.

We conclude with some practical thoughts on how to succeed.

Embrace AI's potential

Build the data foundations first. AI is only as good as the information it can access. Prioritize connected, trusted operational and engineering data, so AI can support decisions across the asset lifecycle, rather than being limited to isolated use cases. For example, Capgemini is working with a global energy company to create a standardized industrial data platform. This platform connects engineering information, eliminates data silos, and enables reusable AI-enabled data products across multiple sites.
Move from pilots to platforms^[7]. Successful AI projects are now commonplace. The challenge is scaling them – across engineering, operations, and asset management – through common governance, reusable tools, and standardized ways of working. The aforementioned data platform makes this possible, but company-wide commitment and support are also critical to scaling AI adoption.
Reimagine workflows, not just tasks. Don’t simply automate existing activities. Instead, redesign end-to-end engineering processes to benefit from AI, from planning and compliance to maintenance and inspections. In safety-critical areas, progress will rightly take a measured approach; elsewhere, be prepared to rethink how work is delivered.

2. Expand engineering capacity through global capability models

Separate work by value, not location. Keep strategic, site-based, and customer-facing activities close to the asset. But leverage global engineering capability centers for repeatable engineering, digital, compliance, and analytical work.
Build long-term engineering capability, not short-term capacity. Develop global Centers of Excellence that accumulate specialist expertise, standardize delivery, and provide scalable support across multiple infrastructure programs.
Use global talent to accelerate delivery. Don't let local labor shortages dictate project timelines. Combine local engineering teams with distributed global capability to expand delivery capacity on the ground.

3. Lead change with confidence

Treat change as an engineering discipline. Prioritize high-impact workflows, prove new approaches through controlled deployments, measure outcomes, and scale what works. Build confidence through evidence, rather than attempting organization-wide transformation.
Create human-AI chemistry^[8].The future is people and AI working together. Foster a culture where engineers are encouraged to use AI responsibly, with safe places to experiment, supported by trusted tools, clear governance, and practical guardrails. This can create the right ‘frame’ for the technology: allowing AI to be viewed positively as an enabler that strengthens professional judgment.
Balance innovation with assurance. Maintain the industry's uncompromising commitment to safety and reliability, while recognizing that delivery models – but not engineering standards – must evolve. The organizations that succeed will be those that modernize how infrastructure is planned, delivered, and maintained at greater speed and scale, without compromising the trust on which the sector depends.

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The next decade of infrastructure growth will require more than investment. It will demand engineering innovation, scalable talent models, and the responsible yet accelerated adoption of AI. Energy and utilities leaders who successfully bring these elements together will define the next era of industry leadership.”

Hariharan Krishnamurthy
Global Industry Leader of Energy & Utilities,
Capgemini Engineering

Caren Hochheimer
Global Energy & Utilities Marketing Leader,
Capgemini Engineering
caren.hochheimer@capgemini.com

Claire Gauthier
Group Industry Leader of Energy & Utilities,
Capgemini
claire.gauthier@capgemini.com

Hariharan Krishnamurthy
Global Industry Leader of Energy & Utilities,
Capgemini Engineering
hariharan.krishnamurthy@capgemini.com

Contributors

Duke Energy raises five-year capital expenditure plan to $103 billion as more US data centers sign on
https://www.reuters.com/business/energy/duke-energy-forecasts-higher-2026-profit-strong-power-demand-2026-02-10/
Capgemini Engineering and R&D Pulse 2026 https://www.capgemini.com/insights/research-library/engineering-research-development-pulse-2026/
TC Energy innovates using AWS to improve document consistency and asset management https://aws.amazon.com/blogs/industries/tc-energy-innovates-using-aws-to-improve-document-consistency-and-asset-management/
Capgemini Engineering and R&D Pulse 2026 https://www.capgemini.com/insights/research-library/engineering-research-development-pulse-2026/
AI revolutionizes inspection processes at EDP Redes España
https://www.capgemini.com/news/client-stories/ai-revolutionizes-inspection-process-at-edp-redes-espana/
Capgemini and Orano deploy the first intelligent humanoid robot in the nuclear sector
https://www.capgemini.com/news/press-releases/capgemini-and-orano-deploy-the-first-intelligent-humanoid-robot-in-the-nuclear-sector/
Capgemini, Why AI pilots succeed, but AI transformation fails at scale
https://www.capgemini.com/insights/research-library/why-ai-pilots-succeed-but-engineering-transformation-fails/
Resonance AI Framework by Capgemini
https://www.capgemini.com/solutions/resonance-ai-framework/