Generative Artificial Intelligence (Generative AI) is poised to revolutionise industries, offering new interactive, multimodal experiences that can reshape how people engage with information and brands. Tech giants like Google, Microsoft, IBM, and Amazon Web Services (AWS) are heavily investing in generative AI, simplifying its creation and scaling with a focus on security and privacy.
The generative AI market is on an upward trajectory, projected to reach $44.89 billion in 2023 and grow at an annual rate of 24.40% from 2023 to 2030, resulting in a market volume of $207.00 billion by 2030. The United States is expected to lead with a share of $16.14 billion in 2023.
Generative AI is already making a significant impact, allowing immediate access to the wealth of knowledge within organisations. Large enterprises like Google, Amazon, Deloitte, and IBM have embraced generative AI, utilising it for insights, fraud detection, data protection, and audience targeting, among other applications.
However, the evolution of generative AI has raised concerns, particularly in the realm of cybersecurity. While it offers promising possibilities, it can also be exploited for cyber-attacks. One of the most concerning threats is the creation of deepfakes and social engineering content, which poses new challenges for enterprises. Security concerns extend to data breaches, prompt injections, and supply chain vulnerabilities. Social engineering attacks, facilitated by generative AI, are becoming a significant cyber threat, requiring a combination of awareness, processes, policies, and technology for defense.
However, there are real-world example of generative AI”s potential and cybersecurity risks. An organisation used generative AI for a virtual board meeting, reducing the need for travel by providing insights through AI. However, during the meeting, a threat actor used a deep fake to send misleading information to participants, revealing the risks associated with generative AI, including identity theft, disinformation, and privacy violations.
Scaling generative AI programs is essential for realising their benefits. To do so, organisations need insights into market demands, internal and external adoption, and a comprehensive assessment of associated risks. Cybersecurity risks are a significant factor that must be addressed to foster the growth of emerging technologies.
To stay ahead in risk management amid the rapid evolution of generative AI, organisations should invest in AI programs, emphasising their responsible and ethical use. They should collaborate with various partners within an ecosystem to manage risks effectively. To mitigate generative AI- risks, businesses should define a clear purpose, develop internal processes for program development, identify key risks and mitigation strategies, establish governance, and maintain vigilant monitoring.
Generative AI holds immense promise for transforming industries but requires a proactive approach to address the cybersecurity challenges it presents.
