The rapid adoption of AI in various sectors faces significant challenges, particularly regarding data security, integration with legacy systems, and legal uncertainties. Data security is the foremost concern, with 55% of organizations highlighting risks associated with sensitive information such as patient records. Effective strategies include minimizing sensitive data handling, implementing encryption, and limiting third-party access. Additionally, integrating AI tools with outdated systems poses a hurdle for 39% of respondents, while 38% cite costs and skills gaps as barriers. Legal issues, especially around patient privacy and intellectual property (IP), are acute, with 66% expressing concerns about legal risks in AI implementation. Companies are increasingly establishing training programs, particularly in compliance with the EU AI Act, which mandates appropriate training for personnel handling high-risk AI systems. As legal frameworks evolve, firms must adopt flexible and clear documentation processes to navigate the complexities of AI governance and tight regulatory landscapes.
Source link
Share
Read more