IDC's Machine Learning Life-Cycle Tools and Technologies analyzes the tools, technologies, and platforms for building, training, tuning, running, and scaling the end-to-end life cycle for artificial intelligence and machine learning (AI/ML) solutions from experimentation to production. Across the themes of AI build, machine learning operations (MLOps), data labeling, and trustworthy AI, this research program analyzes ML data pipelines, ML data platforms, model build platforms, model pipelines and model monitoring. 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.