Royal Dutch Shell covers the supply chain for oil and gas, from extracting to refining to retailing. Oil demand is expected to peak during the 2030s, and international pressure for reducing carbon emissions is intensifying. Given this situation, Shell developed a strategy to become a cleaner but profitable player in the energy industry. Its core business will remain oil and gas, but to reduce fossil-fuel emissions and benefit from the shift to electricity-fueled vehicles and processes, Shell will pursue greater involvement in the electricity sector, aiming to become the world’s largest electric power company.

To carry out this business transformation, Shell is investing in artificial intelligence. By a recent count, Shell had embarked on about 280 AI projects with potential to increase the efficiency of all areas of business while promoting safety and reducing carbon emissions. 

AI at Shell is speeding up oil exploration and increasing the efficiency of drilling. Exploration relies on surveys of the land under which the company hopes to find oil and gas deposits. Especially for surveys of the ocean floor, imaging can suffer from “noisy data,” or irrelevant inputs such as ocean currents. Shell uses machine learning to create algorithms for filtering out the noise and creating a clearer image. When human workers carried out that work, they took months to interpret images; with AI, they can do it a few weeks, so they can scan more locations and potentially find better options for drilling. 

Many of Shell’s operations involve expensive and complex equipment. AI is helping to keep it running efficiently with applications for predictive maintenance. Wired or wireless sensors gather performance data from the equipment—for example, temperature and pressure of specific parts.

In the retail sector, Shell’s recent acquisitions have included makers of electric-vehicle charging stations. At test sites in California, AI monitors the demand for them, helping Shell plan how to distribute the electrical load and ensure that these services are efficient.

Introducing AI into the business requires talent that is in high demand. Shell’s payroll includes more than 150 data scientists, but it needs more people who can apply the technology. Another management challenge is selecting the projects to fund, given that data analytics and AI have so many possible applications. Shell’s chief technology officer aims to focus on projects that can give the company a competitive advantage.

1. Based on the information given, how well would you say Shell’s move to AI-based information systems provides the attributes of useful information (quality, timeliness, completeness, and relevance)? Briefly explain your assessment.

2. How could cybersecurity and data privacy risks affect Shell as it transitions to greater use of AI in its information systems?

3. If you were a manager of a Shell oil rig or planning the rollout of more electric-vehicle charging stations, would you expect the use of AI to make your work more interesting or less so? Why?