Nada Al Meqbali

Nada Al Meqbali is a dynamic and results-driven leader with over 10 years of experience at ADNOC, specializing in driving AI transformation programs and advancing technological innovation in the energy sector. As the Vice President of Future Foresight, she has played a pivotal role in leading ADNOC’s AI accelerator program, maximizing value through the deployment of AI across the value chain. She also founded the AI Lab, which has tripled the pace of proof-of-concept development, positioning ADNOC as a leader in AI-driven operational excellence. Nada is a key contributor to the operationalization of AI and digital transformation projects, mentoring national talent, and fostering strategic partnerships to ensure sustainable growth. She is passionate about leveraging technology to drive value and has designed impactful programs that build AI capabilities, empower employees, and foster a culture of innovation and transformation across the organization.

Session Overview

Wednesday, 5 November

17:10

Digitalisation & AI ICC Hall B 17:10 - 17:40

AI talent revolution in energy: building the human-AI workforce

The wide adoption of AI is transforming not just technological capabilities, but the human talent that drives the industry forward. To remain resilient and competitive in our modern age of disruption, energy leaders must revisit their talent strategies to prepare for the world of tomorrow. To achieve success, they must facilitate close collaboration between human experts and AI agents. While remaining inclusive of the traditional skills associated with the energy industry, leaders must develop a technological skilled workforce including expertise to guide and interpret AI process to oversight and validation roles. Energy companies must take real steps to realign their talent pools and seek a blend of human expertise with machine-driven intelligence to unlock real operational value.

Attendee insights:

Learn how leading energy companies are preparing AI-ready workforces by cultivating dynamic skills and adaptable structures, building capabilities through cross-functional teams, innovative training methods, and continuous learning models to empower employees and ensure the success of AI-driven operations.