How AI is improving operational efficiencies across oil and gas, healthcare, and more
Arificial intelligence is being used in many industries today, and it’s only expanding. Here are some use cases to explain the challenges and benefits of AI adoption.
Artificial intelligence (AI) is serving companies across a broad array of industries. It’s not about replacing human workers with machine counterparts but rather helping businesses operate more effectively in their fields and expand to new horizons and capabilities. I spoke with CEO and founder AJ Abdallat of Beyond Limits, an enterprise AI solution provider, to see how AI has been fulfilling its promise in the business realm.
Scott Matteson: How is AI playing a role in operational efficiency in the oil and gas, energy, manufacturing, and healthcare fields?
AJ Abdallat: AI is playing a critical role in operational efficiency across the energy value chain to optimize resource production, democratize domain expert knowledge, and increase value while reducing environmental risk. In the oil and gas sector, AI is enabling companies to optimize their production and improve asset maintenance in many ways, such as pinpointing drilling opportunities, inspecting pipes for problems with self-navigating robots, and predicting equipment wear and tear.
For example, AI-powered sensors are often installed within permanent downhole gauges inside oil wells to monitor well pressure, temperature and integrity. AI is also helping companies in the sector better predict changing global demand to streamline supply chains and distribution. Companies can use AI to predict how an oversupply of resources or upcoming weather conditions in a certain region could impact the market there.
Energy production has become so difficult to predict and manage that California used to pay Arizona to take excess solar power they’d created. Challenges like these have spurred significant investment in AI to improve operational efficiencies by helping energy providers better balance loads, predict supply and demand, and otherwise optimize energy production, storage, and distribution. Additionally, AI is helping utilities providers better manage hazardous situations, such as with maintenance recommendations and scheduling, trip and fault prevention, outage prevention, and root cause analysis. This is particularly critical now as utilities providers are taking an increasingly conservative approach to hazardous situations, especially since PG&E’s landmark criminal conviction in March for its faulty power line igniting California’s deadly 2018 Camp Fire.
In healthcare, AI is improving efficiencies at both the public health level and individual level. At the public health level, AI-powered forecasting models are helping to predict the impact of COVID-19 on medical facilities and their patients while enabling facilities to determine logistical responses despite challenges with insufficient and continually-changing data.
For example, a lack of homogenous data has made it difficult for hospitals to predict resource allocation needs, particularly for personal protective equipment. Beyond Limits’ AI forecasting model is helping them better determine the percentage of patients that may need ventilators and extracorporeal membrane oxygenation (ECMO) in the ICU and dialysis units. A few other similar examples include Penn Medicine’s COVID-19 capacity planning tool, CHIME; and Washington State’s predictive dashboard, a COVID-19 risk assessment tool. At the individual level, AI is being used to equip patient monitoring patches with AI technologies. Deploying these AI-assisted diagnostics algorithms in edge environments allows for real-time analysis of patients’ vital signs and recommended actions.
