This report looks at the AI lifecycle management companies serving enterprise IT and data science teams.
CB Insights identified 100+ AI lifecycle management companies addressing 11 technology priorities, from data annotation to AI model monitoring, that data science and IT teams face. The purpose of the analysis is to provide technology buyers with an overview of the technology landscape and its market participants.
Key themes explored in this report include:
- Data preparation: Given that AI data plumbing and curation take up ~80% of a team’s time and resources, a number of companies have developed solutions to streamline the process. Many are leveraging AI to remain competitive in an overcrowded market.
- Low- and no-code AI: Tools targeted at teams without in-depth AI expertise are growing to address the talent shortage. AutoML, for example, can be used to automate aspects of the AI development process.
- Auditing and governance: The demand for explainability and bias monitoring tools is increasing, in large part due to the institution of tighter regulations by the EU, FTC, and others.
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