The oil and gas industry stands at a pivotal transformation point where artificial intelligence is moving from experimental technology to operational necessity.
This webinar provides oil and gas engineers with a practical roadmap for identifying, evaluating, and implementing AI solutions that deliver measurable results across upstream, midstream, and downstream operations.
With more than 20 years of experience transforming business strategies into results-driven enterprise solutions, Senthil Arcot has proven track record modernizing energy industry operations through fit-for-purpose, next-generation technologies. His career bridges strategy and execution—bringing innovative, scalable systems to complex production operational landscapes.
Arcot has led digital transformation initiatives across the energy sector, aligning stakeholders, justifying investments, and delivering solutions that unlock measurable business value. From program and change management to technical advisory roles, he brings a cross-functional, end-to-end view to every engagement.
As Managing Director at Azo Global, he spearheaded multiple intelligent energy projects for various oil production companies that redefined digital capabilities in upstream operations and he has led the evolution of legacy engineering software into cloud-based platforms.
By integrating automation, analytics, and stakeholder alignment, Arcot consistently drives breakthrough performance—from production optimization and tank management to surveillance and field development planning.
Rajni Jaipaul is an accomplished AI enthusiast and program manager with over 20 years of experience leading multimillion-dollar technology transformation initiatives across diverse industries. Rajni specializes in identifying and implementing AI solutions that drive measurable operational excellence.
With an MBA from UT Austin's McCombs School of Business and extensive experience at leading organizations including Dell, Accenture, and Fiserv, Rajni brings a unique perspective to AI implementation strategy. His background spans supply chain optimization, revenue cycle management, and complex systems integration—giving him deep insight into the operational challenges that AI can solve across industries.
Rajni has developed practical frameworks for helping organizations navigate the transition from traditional workflows to intelligent, automated systems. His "3 Rs Framework" for identifying AI opportunities focuses on Repeatable processes, Resource-intensive tasks, and Rule-based operations—a systematic approach that has helped teams uncover high-impact use cases while building sustainable AI programs through incremental wins.
Rajni is passionate about bridging the gap between AI technology and real-world business value. He specializes in helping organizations prioritize AI investments based on cost impact, accuracy improvements, and productivity gains, ensuring that digital transformation initiatives deliver tangible results rather than just technological novelty.
