IDC's Artificial Intelligence and Machine Learning Life-Cycle analyzes the tools, technologies, and platforms for building, training, tuning, running, and scaling the end-to-end life cycle for AI/ML solutions from experimentation to production. Across the themes of AI build, MLOps, data labeling, and trustworthy AI, this research program analyzes machine learning data pipelines, ML data platforms, model build platforms, model pipelines, model monitoring, and governance. By providing actionable insights into buyer behavior, this research also helps vendors understand the end-user needs, gain competitive insights, and differentiate themselves in the market.
IDC's research indicates that while AI/ML adoption is on the rise, cost, lack of expertise, and the lack of life-cycle management tools are among the top 3 inhibitors to realizing AI and ML at scale. This research aims at providing recommendations and best practices to end users to overcome these challenges in their journey of AI-enabled digital transformations.