Al Security Posture Management (AI-SPM)
Over the past 18 months, AI has emerged as one of the fastest-growing technologies, often compared to “cloud on steroids” due to its rapid pace of development and adoption.
We’re discussing AI now because it has reached an inflection point, where applications are no longer just experimental but are becoming essential tools in various industries. Despite being in its early stages, AI has immense potential, and it’s important to prepare for what’s next.
Creating AI-powered applications involves leveraging machine learning algorithms, deep learning, and other forms of artificial intelligence to solve specific business or operational problems.
Unlike previous technologies, AI has broken many barriers in terms of adoption speed and applicability. While cloud technologies were significant, AI’s adoption has been even faster. Every week, cloud service providers (CSPs) introduce new services, APIs, and capabilities, showing the strong and increasing interest in adopting AI solutions.
With AI’s rapid growth, ensuring secure development is essential. Issues like data privacy, model integrity, and biases are increasingly relevant as AI solutions are deployed in sensitive areas. AI’s susceptibility to manipulation (e.g., adversarial attacks), unauthorized access to data, and biases can create ethical and operational risks.
Techniques like differential privacy, model auditing, and adversarial testing are emerging as essential practices. CSPs are continuously rolling out features to help manage these risks, and AI solutions themselves are being developed to detect and mitigate risks. Partnering with CSPs and following industry regulations can help ensure a safer environment for AI development and deployment.
We’re discussing AI now because it has reached an inflection point, where applications are no longer just experimental but are becoming essential tools in various industries. Despite being in its early stages, AI has immense potential, and it’s important to prepare for what’s next.
Creating AI-powered applications involves leveraging machine learning algorithms, deep learning, and other forms of artificial intelligence to solve specific business or operational problems.
Unlike previous technologies, AI has broken many barriers in terms of adoption speed and applicability. While cloud technologies were significant, AI’s adoption has been even faster. Every week, cloud service providers (CSPs) introduce new services, APIs, and capabilities, showing the strong and increasing interest in adopting AI solutions.
With AI’s rapid growth, ensuring secure development is essential. Issues like data privacy, model integrity, and biases are increasingly relevant as AI solutions are deployed in sensitive areas. AI’s susceptibility to manipulation (e.g., adversarial attacks), unauthorized access to data, and biases can create ethical and operational risks.
Techniques like differential privacy, model auditing, and adversarial testing are emerging as essential practices. CSPs are continuously rolling out features to help manage these risks, and AI solutions themselves are being developed to detect and mitigate risks. Partnering with CSPs and following industry regulations can help ensure a safer environment for AI development and deployment.
Tilbyder: Enigma Marketing Pte Ltd | Språk: Engelsk