Jon Guidroz

Microsoft Corporation

Worldwide Partner Strategy Leader, Energy Industry

Jon Guidroz is Microsoft’s Worldwide Partner Strategy Leader for Energy, driving thought leadership to accelerate digital transformation across the energy sector. He is a trusted advisor to Microsoft’s top energy partners, identifying and generating new business opportunities and developing competitive solution strategies that solve customers’ business challenges to deliver the next generation of energy. Jon previously launched and led the worldwide energy vertical at Amazon Web Services and vertical partner ecosystems at Google Cloud for Energy and Marketing Analytics. Jon has over 10 years of direct experience in energy across utility-scale renewables, renewable energy trading, and oil & gas. He completed Harvard Business School’s Leadership and Change Management program, Rice University’s graduate certificate in Finance & Accounting, and earned a BA in International Relations from The George Washington University. 

Sessions With Jon Guidroz

Monday, 7 March

  • 04:00pm - 04:40pm (CST) / 07/mar/2022 10:00 pm - 07/mar/2022 10:40 pm

    AI in the Energy Production Process: Unlocking energy transition opportunities

    Panel Digitalization/AI/Machine Learning/Robotics/Cybersecurity

    The world is pursuing a lower-carbon energy mix with great intent and energy companies are grasping new opportunities that encompass much more of the energy value chain than old business models, including closer engagement with end-use customers. Headwinds exist in the form of high costs, the pace of change and ever-changing regulatory burdens. All companies are embracing digitalization and artificial intelligence (AI) seems set to have a significant role in a rapidly changing, data-intense energy value chain. How might AI help unlock new and enhanced opportunities? What methods can help manage the mix of weather-dependent renewable energy and traditional energy sources to ensure low-carbon reliable supplies? How can we navigate and derive advantages from the new proximity between producers and end-users to drive efficiency and reduce cost? What risks or challenges remain to be mitigated or solved in applying AI to energy production? How quickly can we overcome them?