With the rise of generative AI, businesses are witnessing a transformative shift in operations. According to Sean Clifford, vice president, financial institutions cyber lead at BHSI, adopting such advanced technologies comes with both opportunities and risks.
Generative AI provides companies a chance to reduce costs and enhance competitiveness. However, this implementation necessitates a thorough understanding of potential liabilities. Clifford emphasizes, ‘When operating as a professional service firm, your customers look to you for guidance and rely on your expertise. Any errors, inaccuracies or negligence in the rendering or performance of these professional services could ultimately result in liability.’
The Professional Liability Risks of Generative AI
One significant concern is the potential for AI systems to make errors or produce biased decisions that can adversely affect individuals or businesses. An example Clifford notes is an AI-driven legal aid tool that could inadvertently lead to malpractice due to referencing inaccurate information. Additionally, unintentional algorithmic bias in finance could mean loan denials based on race or gender.
‘What’s also important is to mitigate the overreliance on this technology by having a human in the loop, reviewing and validating the content and services before delivering them to the customer,’ Clifford adds.
AI Risk and Cybersecurity
The cybersecurity landscape is also evolving with AI’s adoption. Clifford articulates the necessity for businesses to recognize the new risks and vulnerabilities it brings. He remarks, ‘The adoption of any new technology, including generative AI, can potentially create new attack surfaces that threat actors can exploit.’ The present era showcases evolving methods of attack, where bad actors can manipulate AI systems, such as chatbots, resulting in potential data leaks.
Developers must maintain awareness and preemptively implement safeguards against these vulnerabilities. ‘There’s always the potential to find a way around,’ Clifford states, urging caution.
Innovation and Data Security Concerns
Generative AI relies heavily on data, and as businesses gather extensive consumer information to refine these models, the risk of data leaks juxtaposes the need for innovation. Clifford explains, ‘As AI models consume vast amounts of data, sensitive consumer information could inadvertently be swept up, raising significant privacy concerns.’ Ensuring compliance with consumer rights related to data retention will be vital.
Strategic Steps for Responsible AI Adoption
Businesses interested in integrating AI into their operations must proceed consideredly. Clifford suggests establishing cross-functional committees to guide AI usage, emphasizing human oversight and staying updated on technological developments and regulatory frameworks. He concludes, ‘I believe the companies that take a long-term view will be the most successful.’
