Several issues are now at the forefront when it comes to artificial intelligence (AI) applications in the energy industry, with security, privacy, and scalability being the three main areas of concern.

Cybersecurity Risks: The probability of cyberattacks rises with the increased connectivity and integration of AI systems into the energy infrastructure. Malicious actors might interrupt vital energy operations by taking advantage of flaws in AI algorithms or manipulating data inputs. Strong cybersecurity defenses are essential to fending off these ever-changing attacks.

Interoperability Challenges: Scalability involves more than just managing massive data sets; it also involves ensuring that AI systems are compatible with current technology. For AI implementation to be effective and scalable, it presents obstacles to achieving seamless integration across many energy platforms, sensors, and devices. These problems must be solved.

Protection of Personal Data: When AI is used, a lot of personal data is collected and analyzed. This data can include employee information and patterns of energy consumption by consumers. It can be difficult to strike a compromise between protecting people’s right to privacy and using this data for optimization. To solve this risk, it is imperative to implement privacy-preserving AI approaches and comply with strict data protection standards.