The Skills Intelligence Engine for an AI-Ready Energy Workforce

Abstract

Abstract As digitalization and AI reshape the energy industry, operators must transform large technical workforces without eroding core domain expertise. The challenge goes beyond training digital specialists; it requires evolving domain professionals into domain-plus-AI, domain-plus-digital, and domain-plus-business practitioners. This paper presents a framework of energy organization's Skills Intelligence Infrastructure, a single engine linking learning activity, curated curricula, skills maps, HR data, and a conversational AI agent (beta) that bridges HR and business to support upskilling, mobility, promotion readiness, and strategic workforce planning. The infrastructure was developed through a four-layer architecture. First, a unified data foundation integrates employee learning activity with HR data, enabling segmentation by role, organization, geography, seniority, and business area. Second, curated curricula and skills maps are designed with business owners to align with enterprise priorities across AI, machine learning, data, operations, sustainability, project management, safety-critical training, sales, and domain competence. These resources support aspirational and promotion-linked roles while clarifying expectations, gaps, and priorities. Third, persona-driven experiences serve employees and managers: employees pursue pathways, identify gaps and future requirements, and build T-shaped capability—deep domain expertise broadened by AI, digital, project, and business skills—while managers monitor development, assess the regional distribution of skills, and identify talent opportunities for mobility, promotion, and hiring. Fourth, a conversational AI agent lets employees ask which skills target roles require and which pathways to prioritize, while managers evaluate talent against skills, learning records, pathway completion, and readiness indicators. Deployed across approximately 8,000 professionals, the platform delivers curated curricula for more than 60 aspirational roles, including 12 promotion-linked roles, and hundreds of pathways across digital, AI, data, project management, safety, sales, and domain expertise. As the enterprise system of record for capability, it provides end-to-end visibility into the AI upskilling funnel: more than 3,000 employees advancing their skills, more than 1,500 certified data science practitioners, and early identification of domain data scientist candidates. It surfaces more than 150 AI-powered innovation projects across the E&P lifecycle and tracks participation in an enterprise's strategic development program. For managers, it reveals skills trends across regions, business lines, and disciplines, exposing hidden capability gaps and talent opportunities. By favoring internal development over hiring, it has reduced recruitment costs for scarce digital talent and improved satisfaction with learning and career development. Unlike commercial talent-marketplace platforms, this skills-based workforce intelligence solution is purpose-built for a large technical energy workforce. It links HR and business through manager-owned skills maps, integrates siloed domain certifications and critical pathways, and operationalizes the domain-to-domain-plus-AI transformation at scale. It supports upskilling, talent conversion, mobility, promotion readiness, compliance tracking, and build-versus-hire decisions. Future enhancements will infer skills from roles, projects, and experience and extend the AI agent into talent management. This provides a foundation on which the energy workforce can build as AI reshapes the industry.