Security Concerns in AI’s Rapid Growth
While the industry acknowledges the need for robust security measures, research from PSA Certified suggests that investment and best practices are struggling to keep pace with AI’s rapid growth.
Rapid Growth Outpacing Security Measures
The survey of 1,260 global technology decision-makers revealed that two-thirds (68%) are concerned that the speed of AI advancements is outstripping the industry’s ability to safeguard products, devices, and services. This apprehension is driving a surge in edge computing adoption, with 85% believing that security concerns will push more AI use cases to the edge.
Edge Computing: A Solution?
Edge computing – which processes data locally on devices instead of relying on centralised cloud systems – offers inherent advantages in efficiency, security, and privacy. However, this shift to the edge necessitates a heightened focus on device security.
Disconnect Between Awareness and Action
“There is an important interconnect between AI and security: one doesn’t scale without the other,” cautions David Maidment, Senior Director, Market Strategy at Arm (a PSA Certified co-founder). “While AI is a huge opportunity, its proliferation also offers that same opportunity to bad actors.”
Despite recognising security as paramount, a significant disconnect exists between awareness and action. Only half (50%) of those surveyed believe their current security investments are sufficient. Furthermore, essential security practices, such as independent certifications and threat modelling, are being neglected by a substantial portion of respondents.
A Holistic Approach to Security
“It’s more imperative than ever that those in the connected device ecosystem don’t skip best practice security in the hunt for AI features,” emphasises Maidment. “The entire value chain needs to take collective responsibility and ensure that consumer trust in AI-driven services is maintained.”
The report highlights the need for a holistic approach to security, embedded throughout the entire AI lifecycle, from device deployment to the management of AI models operating at the edge. This proactive approach, incorporating security-by-design principles, is deemed essential to building consumer trust and mitigating the escalating security risks.
A Sense of Optimism Prevails
Despite the concerns, a sense of optimism prevails within the industry. A majority (67%) of decision-makers believe their organisations are equipped to handle the potential security risks associated with AI’s surge. There is a growing recognition of the need to prioritise security investment – 46% are focused on bolstering security, compared to 39% prioritising AI readiness.
Conclusion
AI’s rapid growth presents significant security concerns, and the industry must adapt to address these challenges. A holistic approach to security, embedded throughout the AI lifecycle, is crucial for building consumer trust and mitigating the escalating security risks. As the industry continues to embrace AI, it is essential to prioritise security investment and best practices to ensure a secure and trustworthy AI ecosystem.
FAQs
Q: What is the main concern in the AI industry?
A: The main concern is the rapid growth of AI outpacing security measures.
Q: What is edge computing?
A: Edge computing is a solution that processes data locally on devices instead of relying on centralised cloud systems.
Q: What is the disconnect between awareness and action in the AI industry?
A: The disconnect lies in the fact that despite recognising security as paramount, a significant portion of respondents do not believe their current security investments are sufficient, and essential security practices are being neglected.
Q: What is the key to a secure AI ecosystem?
A: A holistic approach to security, embedded throughout the entire AI lifecycle, is deemed essential to building consumer trust and mitigating the escalating security risks.
