Summary
Many BI professionals complete only 3 to 4 machine learning (ML) and artificial intelligence (AI) projects annually, according to a Reddit discussion.
What are the current findings?
In a recent Reddit discussion on the r/datascience forum, a participant shared that he delivers around 3 to 4 ML/AI projects each year with a team of seven. Collaboration is scarce, impacting productivity and analysis diversity. These insights are crucial for companies looking to enhance their AI capabilities.
The broader impact on the BI market
These findings reflect a wider trend in the industry, where teams are often pressured to deliver multiple types of analyses without sufficient resources or collaboration. Competitors like DataRobot and H2O.ai offer solutions addressing these challenges by promoting automation and teamwork. This raises questions about the effectiveness of the current AI implementation model and the potential for investments in tools that facilitate greater collaboration among teams.
What should you do?
BI professionals should assess how their own teams are structured and identify opportunities for collaboration. Mapping workloads and exploring advanced tools can help improve the efficiency and output of ML/AI projects.
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