U+, a leading global digital innovation company, announces the release of its report “How AI Can Save the Energy Industry Billions in 2022 and Beyond,” which outlines specific artificial intelligence (AI) tech solutions that can significantly reduce the costs of transitioning to clean energy. Analysts view AI as vital to ensuring efficient and cost-effective transition, and predict AI applications will save investors $1.3 trillion over the next 30 years.

Key methods for achieving greater efficiency, accelerating transition and reducing costs include:

  • Renewable power generation and demand forecasting.
  • Energy demand management.
  • Grid operation and optimization.

“Transitioning to cleaner energy is an ongoing innovative process by itself, and the successful management of existing and future energy solutions requires powerful, intelligent technology,” said U+ Founder and CEO Jan Beránek. “To switch to cleaner energy, I see the need for innovative applications that will help manage renewables-based systems, like powered grids and wind farms.”

Governing, designing and enabling AI’s deployment must involve collaboration across multiple energy-associated industries, like power, transportation and construction. In addition, consumers must also do their part to reduce the global carbon footprint.

U+ has a successful record of working with companies that are using AI for cleaner energy. Examples include building a smart home app connected to smart energy meters and a virtual solar battery concept for mass-market consumers for the European energy supplier E.ON.

Click here to read “How AI Can Save the Energy Industry Billions in 2022 and Beyond,” which details how AI can be a primary cost-saving mechanism for the transition to cleaner energy. Also see the companies U+ highlights as this year’s Top Energy Innovators.

U+ selected its Top Energy Innovators after extensive market research, leveraging databases including CB Insights and Crunchbase. Market share, along with the amount and date of funds raised, were also considered as selection criteria.