10 Things to Know When Starting with AI
Planning for success beyond the initial stages of a project is key.
Artificial intelligence (AI) and machine learning (ML) technologies are disrupting virtually all industries globally, and AI technologies are not just being applied within robotics and vehicle automation. Companies in all sectors are seeing business improvements through insights generated by AI and ML, including financial services, retail, manufacturing, health and life sciences, and more.
Digital leaders are also paying attention to this emerging technology. According to the 2019 Digital Business study by IDG, organizations planned to spend $15.3 million on digital initiatives with AI and ML are high on that list. Despite the enthusiasm around the technologies, however, failure rates on AI and ML projects range anywhere from 50% all the way up to 85%.
Reasons given for these failures include not having a plan ahead of time, not getting executive or business leadership buy-in, or failing to find the proper team to execute the project. Chasing the hot technology trend without having a proper strategy often leads companies down the path of failure.
Fortunately, enough lessons have been learned through these failures to give companies a better game plan for their next AI or ML project.