Artificial Intelligence (AI) has become an integrated part of our society and economy, with AI-based systems or applications navigating decision-making, data collection, usage analysis, and much more. AI technologies hold the potential to assist diverse industries such as manufacturing, FMCG, transport, healthcare, education, oil and gas, utilities, and the energy sector achieve disruptive transformations, strengthen workforce productivity and boost production efficiency, thereby ensuring higher profits for an organization.

Role of AI in the Energy/Utilities Sector

Globally, the energy sector faces challenges of rising demand, efficiency, changing demand and supply patterns and a lack of analytics needed for optimal management. Enterprises today are looking towards leveraging artificial intelligence and related technologies to solve these. This has helped improve power management, efficiency and transparency, lower energy costs and has led to a greater adaptation of new technologies. AI has also helped to deal with complex challenges faced during power generation, transmission, distribution and consumption.

Utilities have to manage massive infrastructure networks, including substations, transmission and distribution lines, etc., spanning thousands of miles and across the country. Meanwhile, vegetation management around a structure and breakdowns as a result of natural phenomena must also be monitored as part of maintenance and quality control. This is where AI and ML algorithms are revolutionizing data collection and analysis to present speedy solutions. 

Training the Workforce in AI Management

AI, ML, cognitive computing and robotics are helping to create new jobs, boost productivity, and allow workers to focus on the human aspects of work such as customer experience, employee engagement and workplace culture. AI can handle mundane and repetitive functions, freeing the workforce across the company vertical to exercise creativity, solve complex problems and focus on getting work done. 

While automation is a fairly obvious use for AI in a power plant, there is a more pressing case where AI can pitch in. All plants depend on their subject matter experts to diagnose, pinpoint the root cause and resolve issues that are not solvable by their less experienced engineers. Such individuals are a pool of knowledge and experience, capable of presenting solutions in remarkable time, thereby saving the company billions of dollars. So, what happens when they decide to move on or retire? The loss of such individuals can adversely impact the productivity and efficiency of the plant and cause a huge dent in profits.

How can the enterprise make sure that the young workforce joining can achieve proper knowledge transfer without putting the experts through long repetitive training sessions every time?  Also, one expert may have in-depth knowledge about maybe one sub-process/machine, so how do you bring in the domain knowledge for your entire plant in your knowledge transfer process?


These concerns and more about an impending talent crisis in the power industry are picking up. The industry is already globally mobile, with more skilled workers, particularly engineering and technical specialists with 10-15 years of experience, willing to relocate for career progression. Additionally, there is the problem of an aging trained workforce that chooses to retire after a grueling career, creating a void that is difficult to fill. Power companies are now beginning to feel the pinch of the skills shortage.

The only way out for employers is to build resilience into the business, with an emphasis on sustainable knowledge transfer.

How AI can pitch in

This is where an AI-powered technology like UptimeAI can play an important role: first by taking up the non-creative tasks like diagnosing and analyzing machine issues, leaving the engineers to learn and perform critical decision-making tasks centered around solving problems creatively, strategizing, extrapolating their impact for overall plant reliability and efficiency, risk assessment, and weighing the benefits and trade-offs of making a particular decision. Second, bringing your own Virtual Plant Expert to the plant provides a bank of knowledge and learning that grows and learns with every new experience and can serve as the vessel for knowledge transfer of these fundamental skills, which will always stay with the organization, increasing the productivity of your workforce multi-fold. The built-in domain knowledge and failure modes that are specific to your industry and faced by your peers globally ensure that you don’t have to worry about unplanned downtimes and wasted productivity anymore.

In the fast-paced world of cut-throat competition and increasing customer demands, manufacturing plants & the workforce needs to be performing at their best from the get-go. AI can ensure that you don’t lose out on valuable domain knowledge when a subject matter expert leaves and that a new workforce gets a seamless knowledge transfer. The AI-driven knowledge base that keeps on learning & growing with experiences can emerge as a formidable competitive advantage for your enterprise, ensuring productivity & efficiency like never before.