Dun & Bradstreet Executive Discusses AI Adoption
AI adoption is hindered by data quality, according to Dun & Bradstreet's Gary Kotovets. This issue affects returns on investments.
Original reporting · ciodive.com
Original: “AI readiness remains scarce, blocking returns on investments”
Read “AI readiness remains scarce, blocking returns on investments” at CIO Dive →
How this was written. Diagnosis Forward wrote this article with a language model from CIO Dive’s reporting (model: @cf/meta/llama-3.3-70b-instruct-fp8-fast); it describes that reporting rather than adding to it. The original, linked above, is the full story.
Key points from CIO Dive’s report
- AI adoption is shifting towards a focus on data quality.
- The quality of information AI models use is crucial for effective AI systems.
- Access to AI models is no longer the primary concern.
Dun & Bradstreet's Gary Kotovets commented on the next phase of AI adoption, stating it will be defined by the quality of information AI models can use.
The quality of the information those models can use is a crucial factor in AI adoption, as it directly impacts the effectiveness of AI systems.
Gary Kotovets noted that access to models is no longer the primary concern, but rather the quality of the data that fuels them. This article is based on reporting by CIO Dive.
Questions and answers
What is the next phase of AI adoption defined by?
The next phase of AI adoption will be defined by the quality of the information those models can use.
What is the primary concern for AI adoption now?
The primary concern is no longer access to models, but rather the quality of the data that fuels them.
