According to a Gartner report, “by 2026, organizations that do not build AI model observability capability will see a 20% decrease in the number of models running in production due to maintenance overheads.”
As AI technologies continue to become mainstream in enterprises, IT leaders must differentiate their organizations by implementing simulation platforms that integrate advanced analytics and realigning their teams with a cognitive science focus. This approach will enable companies to address the significant challenges associated with developing AI models, such as collecting enough data and validating models’ accuracy.
Moreover, IT leaders can benefit more from their AI investments by modernizing AI practices. For example, simulation can enable IT leaders to develop more sophisticated and intelligent systems tailored to specific use cases.
Combining simulation with advanced analytics also helps organizations identify patterns and insights to optimize both AI models and business processes. To capitalize on these benefits, IT leaders must develop a cognitive science focus emphasizing the critical skills required to build and deploy intelligent systems, including data science, machine learning, and natural language processing. By doing so, organizations can stay at the forefront of AI innovation, helping them remain competitive in increasingly crowded markets.