The reality of artificial intelligence and machine learning (AI/ML) is being made possible by the evolution of technologies associated with big data, analytics, advanced analytics, operations research, data science, cloud computing, microservices, and decision science. AI and ML are just the most recent chapters in the amalgamation of computer science, mathematics, data management, and decision science.
This research demonstrates that most large enterprises see AI/ML as important priorities and strategies are already in place to leverage AL/ML capabilities. AI/ML expectations at large enterprises are lofty, which could lead to inflated expectations followed by a trough of disillusionment. EMA does not see this as likely because much of the heavy lifting in AI/ML is now in the past. EMA sees AI/ML unfolding in DevOps and workload automation first as machine learning avenues to provide feedback on decisions made and actions taken. This feedback loop provides an opportunity for the continuous improvement of which decisions and actions are taken, thereby driving a wide array of improvements in quality.