The energy and commodities sector is at a pivotal crossroads. As experienced workers retire and new talent enters the field, organizations face a critical challenge: how to retain institutional knowledge, accelerate onboarding, and upskill employees to ensure operational continuity and future growth. Generative AI is emerging as a transformative solution, enabling companies to codify expertise, empower the next generation of workers, and mitigate the risks of workforce attrition.
A significant portion of the energy and commodities workforce is nearing retirement. For example, nearly 27% of oil and gas laborers are over the age of 55, and the average age of agricultural workers continues to rise. This demographic shift threatens to create a "brain drain," where decades of operational know-how, best practices, and safety protocols risk being lost. Traditional onboarding and training methods are often too slow and fail to capture the tacit knowledge accumulated over years of field experience. The result? Slower onboarding, increased operational risk, and a workforce ill-prepared for the demands of digital transformation.
Generative AI, powered by large language models (LLMs) and advanced machine learning, is fundamentally changing how energy and commodities organizations manage knowledge and develop talent. Unlike traditional rule-based automation, generative AI can synthesize vast, disparate datasets, generate contextualized content, and interface with existing digital tools using natural, human-like language. This enables organizations to:
Generative AI enables the creation of dynamic, searchable knowledge repositories that capture decades of operational expertise, maintenance logs, and best practices. For example, a major downstream oil and gas company implemented a generative AI-powered search tool that allows employees to query a 200GB+ repository in natural language, reducing average search times from five minutes to just 20 seconds and increasing data retrieval accuracy by 94%. This not only boosts productivity but also ensures that critical information is accessible to new hires and distributed teams, reducing reliance on "tribal knowledge."
AI-powered digital co-pilots can support field technicians and operators in real time. In upstream oil and gas, generative AI assistants help diagnose equipment failures, provide step-by-step repair instructions, and optimize maintenance schedules by tapping into both structured sensor data and unstructured maintenance records. These assistants learn from user interactions, continuously improving their recommendations and closing the feedback loop. The result is faster problem resolution, reduced downtime, and a more confident, capable workforce.
Generative AI platforms can analyze employee data and learning preferences to deliver customized training paths and recommend relevant content. Proprietary tools, such as those developed by Publicis Sapient, provide organizations with pre-vetted large language models and frameworks to scale knowledge sharing and personalized learning across any major cloud platform. This approach helps employees acquire new skills faster, adapt to evolving business needs, and remain engaged in their professional growth.
By codifying institutional knowledge and making it accessible through intuitive, conversational interfaces, generative AI dramatically reduces the learning curve for new employees. It accelerates onboarding, supports continuous upskilling, and ensures that hard-won expertise is preserved and leveraged across the organization. This is especially critical as the sector faces a demographic shift and the risk of institutional brain drain.
Generative AI also enables the automation of reporting, research, and planning tasks, freeing up skilled professionals to focus on higher-value, strategic activities. As new technology-driven roles emerge—such as AI engineers, prompt designers, and data stewards—organizations must invest in targeted upskilling programs, blending technical training with domain expertise.
Deploying generative AI for workforce enablement in a highly regulated industry requires robust data governance, security, and ethical frameworks. Best practices include:
The integration of generative AI into workforce strategies delivers measurable outcomes:
To maximize the benefits of generative AI, organizations should:
Publicis Sapient brings deep expertise in digital business transformation and generative AI, with a proven track record of helping energy and commodities organizations navigate the complexities of workforce transformation. Our proprietary platforms, such as Bodhi and PSChat, combined with our integrated SPEED (Strategy, Product, Experience, Engineering, Data & AI) model, enable end-to-end execution and measurable impact. We help clients design, implement, and scale secure, scalable AI solutions tailored to their unique needs—empowering every employee to leverage AI safely and effectively.
As the future of work continues to evolve, generative AI will play an increasingly central role in shaping how organizations attract, develop, and retain talent. By partnering with Publicis Sapient, leaders can confidently harness generative AI to drive operational efficiency, ensure compliance, and build a future-ready workforce—turning today’s challenges into tomorrow’s competitive advantage.
Ready to transform your employee experience and upskill your workforce with generative AI? Connect with our experts to start your journey.