Removing the Barriers to AI and Machine Learning
To learn more about how organizations are managing and modernizing their data as enterprise interest in AI scales up, we surveyed 1,870 IT leaders in a range of industries and from around the world. Our findings, which discovered widespread challenges arising from underlying issues with data quality and infrastructure, have been captured in this white paper.
Our respondents self-identified into three categories of AI and machine learning maturity: exploring, formalizing and innovating. Data points of note include:
- All three maturity levels list talent gaps in their top three challenges
- One in fivealso cite legal concerns, risk and compliance, regardless of maturity
- 63% of ‘Innovating’ and 62% of ‘Exploring’ organizations say data pipelines need major work before they can support AI and machine learning initiatives
Download the report for the full findings, including critical insights into the role of people and operations in modernizing your data.