The latest advances in artificial intelligence (AI) can be a game changer for energy, resources, and utilities.
The TCS AI for Business Study shows that over half of senior executives in energy, resources, and utilities companies are optimistic about the potential impact of AI on their organization, especially as they seek to transition to a cleaner and greener future. This report provides this and other unique insights about how these companies are moving forward to create effective AI strategies for their enterprise. This report investigates:
Many energy and resources executives surveyed have a positive sentiment toward AI.
And most energy and resources companies and utilities are preparing for AI.
Yet there’s no consensus on AI adoption strategies and not enough metrics to measure success.
Yet there is a gap between aspiration and reality:
What is hampering AI progress in energy, resources, and utilities?
When it comes to concerns about AI, especially with the hype around generative AI (GenAI), five strategic challenges are apparent.
For energy and resources companies, they are:
For utilities companies, they are:
As the integration of AI into business processes accelerates, expected financial return on such an investment becomes increasingly significant. But only 20% of energy and resources, and only 21% of utilities said they have "good enough" metrics and KPIs for their current stage of AI deployments. Without adequate KPIs for AI-enabled operations, proving ROI and getting future buy-in will be challenging.
Most energy, resources, and utilities executives believe AI will augment and enhance human capabilities.
As AI becomes more advanced and part of “business as usual,” the role of humans in the workplace will evolve.
63% of energy and resources companies and 68% of utilities think human strategic decision-making and creativity will remain essential to their competitive advantage.
46% of energy and resources companies, and 47% of utilities expect up to half of their employees will use GenAI daily in the next three years.
Innovation and revenue growth will be a focus for future AI implementations.
82% of pacesetters (the more financially successful companies in the survey) in energy and resources, and 83% of utilities pacesetters are primarily focused on using AI to spur innovation.
For energy, resources, and utilities companies to get the most from AI, they will require a multi-layered strategy that creates a foundation designed for accelerated productivity, innovation, and performance.
It will be prudent to consider a short-term, mid-term, and long-term approach for implementation.
Programs need to focus on an enterprise’s core markets and existing customers where business model and capabilities already present need to be improved.
Can take into account the same core markets and existing customers but can take advantage of AI autonomy to experiment with new and bold business models. A slightly different mid-term symbiotic approach can focus on adjacent markets and acquiring new customers, while maintaining the current business model intact.
Has the time advantage to go after blue sky themes. Enterprises can afford to experiment with both markets and customers as well as new business models.
TCS’ Thought Leadership Institute conducted an anonymous study of approximately 1,272 senior executives with P&L responsibilities in 12 industry sectors across Asia, Europe, Nordics, LATAM, North America, and the United Kingdom and Ireland, with respondents having an annual revenue of $5 billion to $100 billion. The energy, resources, and utilities industry findings are based on feedback received from 90 energy and resources companies and 95 utilities.
This global study examines how CEOs, LOBs, directors, and business line managers are preparing their business to be AI-ready, focusing on aspects such as their strategy around operations, talent, and future implementation plans. The study also provides best practice recommendations based on these insights.
