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In a world rapidly embracing artificial intelligence (AI), businesses are eager to leverage its capabilities for improved speed, efficiency, and decision-making. However, with this exciting new technology comes a myriad of cybersecurity risks. The adoption of AI has already made significant strides across various industries, from customer-facing businesses using AI-powered chatbots to financial services companies utilizing AI for fraud detection. But as organizations embrace AI and generative AI to achieve their goals, it’s vital to address the potential cybersecurity concerns that accompany these advancements.
One of the major risks associated with AI is the possibility of data exfiltration. The launch of ChatGPT, an AI model developed by OpenAI, raised concerns about the security of the data used to train generative AI models. In 2023, experts warned that code snippets, intellectual property, and user search data could be compromised, potentially enabling the transfer of sensitive information from one business to another. While some organizations have implemented guardrails and adopted private AI services, there are still unknown security risks that may arise as the technology continues to mature.
Another significant cybersecurity risk is the potential for social engineering and scams. AI and generative AI have the capability to enhance the quality of written communication, making it increasingly difficult to distinguish between messages generated by AI and those written by humans. Threat actors could exploit this technology to produce realistic-looking messages used in spear phishing campaigns. Unsuspecting recipients who rely on common grammatical mistakes to detect fraudulent emails may be tricked into fulfilling requests contained within these messages.
Code vulnerabilities are also a concern when relying solely on AI to generate code. While businesses may turn to AI-powered code generation to accelerate development, recent research indicates that code generators are more likely to introduce vulnerabilities compared to human coders. Implementing proper software development lifecycle processes is crucial to ensure secure code deployment and reduce the risk of cybersecurity issues.
Data poisoning represents yet another cybersecurity risk in the realm of AI. As AI models learn from inputs used for decision-making, if threat actors succeed in altering the data model with malicious inputs, they can distort the outputs and spread disinformation or propagate misinformation. The infamous case of Microsoft’s chatbot Tay serves as a cautionary tale. After being trained on user speech inputs, the chatbot interacted with the open internet, leading to its poisoning with profane language and inappropriate responses.
When implementing AI and generative AI in businesses, it is crucial to establish a comprehensive cybersecurity strategy. Three key domains for cybersecurity protection include data exfiltration prevention, robust defense against social engineering attacks, and secure code development practices. By focusing on these areas, organizations can mitigate the potential risks associated with the adoption of AI.
If your business is undergoing an AI transformation and is concerned about cybersecurity risks, experienced professionals at AlixPartners can provide assistance. They possess the knowledge and expertise needed to assess the current state of AI usage, develop strategies, and design solutions that facilitate secure AI adoption. Additionally, the team can offer guidance on ongoing monitoring and support to ensure continuous security for your systems and data.
Don’t let cybersecurity threats hinder your organization’s progress. With the right approach and cybersecurity measures in place, businesses can seize the benefits of AI while safeguarding against potential risks.
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