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# 3 Compliance from beginning
In the State of Generative AI in the Enterprise report from Deloitte , 2,800 executives were asked about their Generative AI risk-management capabilities . Only 25 % said their organisations are highly ready to deal with Generative AI governance and risk issues . Governance concerns include lack of confidence in results ; intellectual property issues ; data misuse ; regulatory compliance ; and lack of transparency .
The European Union recently finalised the Artificial Intelligence Act , marking a significant regulatory step in managing AI technologies within the 27-nation bloc . The law aims to ensure AI developments are humancentric , enhancing societal and economic growth .
Adopting AI securely and compliantly requires organisations to establish clear boundaries , implementing acceptable usage policies , establishing responsible AI policies for developers , creating AI procurement policies , and identifying possible misuse scenarios . Regular data audits to show how data is being collected and stored are also recommended .
By integrating privacy-by-design principles in AI initiatives from the beginning , the enterprise can focus on the importance of data privacy and lower the risk of data exposure .
# 4 Employee training
Consumer applications for AI like ChatGPT have caught on very quickly as millions of people embrace
these tools . But the surge in interest poses a challenge for business leaders . Accenture notes that the majority of workers are self-educating on the technology through social media and various news outlets , which could lead to a spread of inaccurate information about the use of AI tools .
Lacking a reliable source to distinguish correct from incorrect information , employees might contribute to the creation of shadow IT . By using these apps on their personal devices , they are ushering in fresh cybersecurity risks . Another study from Salesforce finds more than half of employees are using AI without employer permission .
To safeguard against cybersecurity threats posed by Generative AI technologies , enterprises need to establish comprehensive training programmes .
Policies should be clear about the types of data that are permissible to be shared with AI-powered systems . Sensitive data , such as intellectual property , personally identifiable information , protected health information , and copyrighted materials , should be forbidden from being input into the AI system .
With so many diverse stakeholders , team play and collaboration is also important for successful outcomes around the ethical and secure use of AI .
For this , encourage communication and collaboration among the organisation ’ s data science , IT infrastructure and cybersecurity teams to address risks and other concerns jointly . p
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