Patrick Long, Director at Opportune LLP, focuses on assisting companies with business issues and helps create process solutions. And, with so much data generated by companies today, Long noted a desire to utilize this information in a transformative way. Artificial Intelligence (AI) is doing just that. So the question is, as the energy industry adapts to various market needs and advancements in technology, can AI tap into data to play a vital role in this transition, and ultimately, contribute to the energy industry's success?
"One of the biggest data points energy companies have to contend with is, there are so many tools available," Long says. "Software companies are looking to get into new markets, and energy is a great one. Energy's needs are adapting; it's getting more complex. There's a large opportunity for sensors and collecting information. Then there’s the visualization of the data, and the cleanup of the data.”
There’s a myriad of aspects that make the energy sector attractive to AI software developers. The prevailing issue in the energy industry today is getting these options paired down to the right providers, and the solutions that make the most sense for what they want to achieve from the data.
As for which areas solutions such as AI algorithms can improve facets of the energy industry, Long points to linear programming (LP) models to maximize profit or create the lowest cost. “There’s also new and different information coming in and all different types of sensors feeding into the data stream,” Long says. “It’s about taking the data coming in and making the best sense out of it.”
"No matter what the algorithm is generating, there's still a human on the other side who must interpret that data and make sense of it so there can be actionable insight.”
Work continues with or without AI, but Long says energy businesses still need to react to what the rest of the industry is doing. “In place of artificial intelligence comes experience. No matter what the algorithm is generating, there’s still a human on the other side who must interpret that data and make sense of it so there can be actionable insight."