In an article published on Business Reporter, Vincent KorstanjeKigen CEO, highlights for business leaders continued investments in cybersecurity at the edge with embedded SIM (iSIM) and eSIM Secure Elements which already form the foundation of cellular IoT identity management, act as critical trust anchors to unlock business data-driven innovation on AI and plan for long-term AI adoption success.
Kigen predicts that given the current pace of companies’ efforts to improve AI models, developers could run out of data between 2026 and 2032, according to a study published in June 2024 by research group Epoch AI.
Over the past year, many of the most crucial web sources have been used to train AI. Models have restricted the use of their data, according to a study published in July 2024 by the Data Provenance Initiative, a research group led by MIT.
The real breakthrough that will allow humanity to move to the next S-curve is data produced at work said a July 2024 article featured by Emergence Capital on Fast Company.
To overcome the limitations and hallucinations of generative AI and the large language models (LLMs) that underpin them, businesses need more control over their data and guidance to prepare for how it will play into the future evolution of AI models. That’s the focus of cybersecurity firm Kigen’s comprehensive guide for business leaders to equip their organizations Cyberintelligence for AI.
Explaining why security is a top priority for businesses, Vincent Korstanje said: “In a world where artificial intelligence reigns, security is not a feature, it is a necessity.”
By 2028, it is estimated that 50% of AI workloads could move to the edge. Only 4% of enterprises say their business data is ready for AI applications. 71% of business leaders consider the security of their data and intellectual property as a major concern for AI strategy.
The immediate starting point is secure edge AI, which is the local processing of data from your sensors, devices, and products directly rather than in centralized LLMs. AI is tailored to the unique needs of a business with data specific to that business in the context of its industry.
Sensor-driven data is the most effective way to detect, verify, and improve data integrity based on AI inferences. Additionally, Kigen’s approach, which extends the GSMA loT SAFE standard to secure enterprise credentials, allows each data element to be cryptographically signed and sealed, better addressing the growing need for data provenance and model explainability.
A refreshing change from the hype and concerns surrounding AI, Vincent’s article shows how achieving it is within reach for most companies considering digital transformation. Read the article in Business Reporter’s Digital Transformation special edition or access the full report on Cyber Intelligence for AI.
See the cover of Vincent’s article in the premium French economic newspaper Le Figaro.
