Barriers to AI Adoption

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Artificial intelligence (AI) has rapidly become an aspect of everyday life, ranging in use from simple tasks, such as asking a personal assistant a question on a phone, to more complex tasks, such as analyzing vast swathes of data. For the bio/pharma industry, the use of AI and machine learning (ML) has the potential to provide some key benefits; however, there are still significant barriers to the implementation of these advanced technologies.

A survey performed by the Pistoia Alliance and Open Pharma Research, the results of which were presented at the Lab of the Future Congress on 1–2 Oct. 2024, has found that a greater proportion of the global R&D community are adopting AI and ML as compared to 2023. However, while adoption rates are on the rise, other concerns are coming to the fore (1).

According to the survey results, 68% of the 200 experts interviewed are currently using AI and ML in their work, which has increased from 54% from the 2023 survey. Additionally, 62% of the survey respondents specified that their company will be investing in AI and ML tech over the course of the next two years (1).

However, 52% of the respondents to the survey cited “low quality and poorly curated datasets as the biggest barrier to AI implementation” (1). Concerns were also raised over data privacy and security issues, with 41% of respondents in 2024 citing this as a concern compared with 34% in 2023. Furthermore, over a third of the respondents (38%) specified concern that data will not be findable, accessible, interoperable, and reuseable (1).

“The good news is that cultural barriers to AI adoption are falling as organizations realize the benefits of the technology for accelerating scientific innovation,” said Becky Upton, president of the Pistoia Alliance, in a press release about the report (2). “But the survey shows a sizeable number of respondents are still facing data issues, and fresh concerns are arising around privacy and security, perhaps due to the ambiguities surrounding new legislation including the EU [European Union] AI Act.”

References

1. Pistoia Alliance. What Will the Labs of 2030 Look Like? A Global Survey May–August 2024. Report (October 2024).
2. Pistoia Alliance. Lab of the Future Survey 2024. Press Release, 25 Sep. 2024.

About the author

Felicity Thomas is associate editorial director of Pharmaceutical Technology® Group, FThomas@mjhlifesciences.com.

Article details

Pharmaceutical Technology® Europe
Vol. 36, No. 9
October 2024
Pages: 6

Citation

When referring to this article, please cite it as Thomas, F. Barriers to AI Adoption. Pharmaceutical Technology Europe 2024 36 (9).