By Bob Cavnar

The energy industry stands at the precipice of a monumental shift—a revolution as transformative as the ongoing rise of generative AI. As we pivot from extracting fossil fuels to producing low or zero carbon energy, the path forward may seem chaotic and unpredictable.

But as with other revolutionary change, the energy transition follows recognizable patterns that can help us navigate the tumultuous waters ahead. Generative AI is leading today’s tech revolution and poised to become a powerful catalyst for change in the energy industry. It also presents a unique opportunity to bridge generational gaps in the workforce.

The greatest risk in the energy transition isn’t only the challenge of generating value and profit amidst rapid technological advances that render previous innovations obsolete. It’s losing the irreplaceable knowledge of experienced workers while failing to fully leverage the new technical abilities and fields of expertise of younger staff. Companies must strive for genuine integration, using AI as a bridge between generations.

In this article, I break down this revolutionary human-to-AI collaboration, and what it means for companies and the future of the energy industry. 

While revolutions are commonly viewed as rule and history breakers, they actually follow known and predictable patterns. Like other revolutions, the clean energy transition can be mapped to three distinct phases. If the transition is shaped intentionally, with strategic planning and attention to career and workforce development within the industry, each phase that is accelerated by generative AI can be strengthened by intergenerational teamwork.

The Early Phase

We’re here now. It’s a time of optimism, pioneering spirits, and a wide array of new applications. Generative AI is speeding up this phase by rapidly iterating designs and simulating complex scenarios. The energy transition has to attract younger workers to the industry, ensuring a strong talent pipeline for the current aging workforce, and bringing fresh perspectives and technological savvy. It’s equally important for older workers to stay and contribute their invaluable industry experience and problem-solving skills.

The Emergent Shift

As the transition progresses, order will emerge from chaos. The traditional oil and gas industry has undergone a significant wave of consolidation over the last decade. As larger companies sell off parts of their businesses that no longer serve their strategy, smaller companies will acquire some of these assets that aren’t well-suited for newer, cleaner low-carbon technologies.

The transition can further accelerate if, to remain competitive, these smaller companies must adapt to continue advancing the shift to clean energy rather than resisting it. AI will play a crucial role in identifying emerging trends and optimizing resource allocation. This phase offers a prime opportunity for knowledge transfer between generations, with older workers sharing deep industry insights and younger workers helping to implement new approaches with cutting-edge technologies.

The New Normal

Eventually, clean energy will become the standard, with AI deeply integrated into every aspect of energy production. The workforce will have evolved into a seamless blend of people of all ages and career stages and the AI technologies supporting them.

Asking better questions to guide the AI-powered transition

The energy transition’s accelerating timeline demands not only technological agility but also a nimble, adaptable workforce. Companies must prioritize both responsible AI adoption and career and workforce development, with a particular focus on retraining older workers, building a strong talent pipeline for industry newcomers, and fostering intergenerational collaboration for renewed productivity.

When shaping big transitions and navigating revolutionary change, knowing how to ask better questions is a crucial skill for leaders. Generative AI tools have only increased the value of this skill with the emergence of “prompting.” Challenge Factory uses a “3-try process” to develop better questions and strategies through prompting. Let’s apply the process’ three steps to the clean energy transition, focusing on AI and workforce issues.

Step 1 – Starting Question

“How can we retrain our aging oil and gas workforce for the clean energy transition?”

This basic question might yield general advice about technical training programs but misses the opportunity for more innovative solutions.

Step 2 – Detailed Question

“How can we use AI to facilitate knowledge transfer between our experienced oil and gas workers and our younger clean energy experts?”

This more nuanced question recognizes the value of both industry cohorts and seeks to leverage AI in bridging the gap. For example, AI could be used to create personalized learning paths, matching the skills of older workers with the needs of new energy projects. However, this approach runs the risk of overlooking the future value of experienced workers once knowledge is transferred.

Step 3 – Emotional Question

“How can we create a culture where our veteran workers feel valued for their expertise while also feeling excited to learn new technologies alongside younger colleagues?”

This emotionally charged question gets to the heart of the matter. It places real people at the center of the industry transition and Future of Work. A successful transition is not just about skills. It’s also about creating a workplace culture that values both experience and innovation, and gives workers of all ages career ownership and agency within the change.

While AI will drive much of the shift to clean energy, success will hinge on the real people doing the work, particularly the successful integration of an intergenerational workforce. Here are five human-driven factors that will ensure this integration.

1. Leadership: Leaders must navigate not only technological change but also nuanced people differences and workforce change, fostering an environment of mutual respect and continuous learning.

2. Mentorship: Two-way mentorship programs empower older and younger workers to share their respective insights and practices, ensuring they learn together and cultivate caring rather than transactional relationships. Intergenerational triads offer even more value to employees and mentorship programs.

3. Collaborative Problem-Solving: To tackle complex challenges, diverse teams are needed that combine the pattern recognition of experienced workers with the new perspectives and emergent fields of expertise of younger staff, all integrated with the analytical power that AI-based tools can bring to the team.

4. Adaptability: Encouraging a growth mindset across all age groups emphasizes that learning is a lifelong process. No one was an AI expert 10 years ago, and few can make that claim today. We are all adapting, together.

5. Knowledge Management: Using AI can more effectively capture and assimilate the tacit knowledge of experienced workers to expand the knowledge base.

Generative AI, combined with a well-intentioned intergenerational workforce, can revolutionize the energy industry in exciting ways:

• AI can analyze decades of operational data from experienced workers to optimize new clean energy systems.
• Workers can develop AI interfaces that make complex new technologies accessible to all age groups.
• Veteran workers can provide crucial context and real-world testing for AI-generated solutions.
• Intergenerational teams can use AI to model and plan the transformation of existing fossil fuel infrastructure into clean energy assets.

As we navigate the energy revolution, remember that the generative AI revolution is occurring at the same time, and the future of energy is a human-to-AI collaboration across generations.

Technology will drive the transition, but people—of all ages—will determine its shape, impact, and sustainability. By understanding the nature of revolutionary change, asking better questions, focusing on the human-driven factors needed for success, and valuing the contributions of all team members, we can create an energy future that doesn’t only power our homes and businesses, but also empowers our society and honors the legacy of those who built the industry.

The wheel of progress turns once more, spinning faster than ever thanks to AI. The energy industry stands at its axis. Will existing companies be able to adapt and harness AI and the combined wisdom of multiple generations to accelerate the transition to clean energy? Or will they be left behind, a relic of the fossil fuel era, having failed to unite their workforce around a new reality? The choice—and the future—is ours to make.