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OpenAI has released a report, The State of Enterprise AI, showing that the healthcare industry has become one of the fastest-growing sectors for enterprise AI adoption.
Healthcare has had 8x year-over-year growth, slightly below the technology industry's 11x YOY growth and just above the manufacturing industry's 7x YOY growth.
The report, which used de-identified and aggregated enterprise usage data from customers of OpenAI and 9,000 workers from across almost 100 enterprises who participated in an OpenAI survey, noted four key findings:
- Enterprise usage is scaling with deeper workflow integration.
- Enterprises that leverage AI are experiencing measurable productivity and business impact.
- Enterprise growth is global and rapidly accelerating across industries.
- A widening gap is emerging between leaders and laggards.
The report noted that even though healthcare started from a smaller base compared to other sectors, such as finance or technology, its growth rate is now closing the gap.
The sector is increasingly deploying AI not only in isolated pilots but for custom GPTs and workflow automation, including operational and administrative processes, according to the report.
"AI is beginning to change who performs certain types of technical work. Coding and analytical tasks are increasingly showing up outside of traditional specialist roles, expanding what some non-technical teams are able to do. At the same time, industry patterns remain distinct, reflecting different operational needs across technology, professional services, finance, healthcare, manufacturing, and more," the report reads.
"Despite a growing divide in AI adoption, enterprise AI is still in the early innings. Firms have an opportunity to catch up by adopting the patterns of frontier workers and organizations. As enterprise AI matures, firms will increasingly translate AI capabilities into products and services that deliver new sources of value through faster iteration, deeper personalization and new experiences. Organizations that succeed in bringing these capabilities into market-facing workflows will use AI not merely as a productivity tool, but as a durable engine of revenue growth and competitive advantage."
THE LARGER TREND
In a Health Science Reports analysis published in September, researchers analyzed the advantages and limitations of ChatGPT use in healthcare.
The researchers gathered 4,982 articles using relevant keywords ("ChatGPT," "Health," "Advantage" and "Limitation") and, of those, 28 articles were included in the analysis.
The researchers identified several ways in which ChatGPT has advantages in healthcare, including its use in clinical decision support, improved medical education, enhanced diagnostic accuracy, use as a research assistant, summarization and self-learning.
Limitations existed, however, with ChatGPT use in healthcare, with inaccurate content due to hallucinations, limited knowledge of specific medical areas, misleading responses due to variations in prompts, a lack of up-to-date training data, wrong references and data privacy risks.
The report noted that ChatGPT struggled with complex prescriptions and patient medication education and cannot replace human doctors in primary care.
"While the model shows significant promise in enhancing clinical decision support and improving medical education, it is essential that its limitations in accuracy and reliability must be addressed. The findings underscore the need for careful integration of ChatGPT into healthcare practices, ensuring that its use is complemented by professional oversight and verification," the report's authors wrote.
"Future research should focus on improving the model's knowledge base, reducing hallucinations and enhancing its ability to handle uncertainty. By addressing these challenges, ChatGPT could become a valuable tool in clinical decision support, medical education and health science research."
