The ability to observe, monitor, and if necessary, intervene in AI-driven processes in real time has become the most pronounced challenge for enterprises of all sizes in the months and years ahead.
Are organizations ready for the need for real-time observability and intervention in their rapidly emerging AI systems? A new survey of 1,896 IT leaders says there is a lot of work ahead to manage these capabilities in real time.
The survey, released by Ponemon Institute in partnership with OpenText, finds that while executives recognize the transformative potential of AI, a gap in information readiness is causing their organizations to struggle in securing, governing, and aligning AI initiatives across business.
Almost three-quarters (73%) of CIOs, CISOs, and other IT leaders believe reducing information complexity is key to AI readiness.
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Supporting real-time business proves challenging
Real-time responsiveness is cited as a leading use case for genAI, the survey shows. The top use case is to support security operations such as analyzing alerts and generating playbooks, cited by 39% of respondents. Thirty-four percent also look to genAI to accelerate threat detection or incident response.
A top priority of IT leaders is ensuring the high availability of IT services to support the business innovation sought through AI. Almost half, 47% of respondents, point to ensuring high availability of IT services as the best path to innovation. Another 43% say it is recruiting and retaining qualified personnel.
IT needs the agility to support all-too-frequent shifts in business strategies, which means constantly chasing a moving target. Fifty-three percent of respondents say it is very difficult to support business goals and transformation. An additional challenge is to be able to secure source code, mentioned by 44%, and custom data, cited by 44%.
The survey also finds that organizations are having difficulties in reducing insider or malicious data loss incidents without jeopardizing trust. Respondents were asked to rate their organizations’ effectiveness in monitoring insider activity across hybrid or remote environments and in creating trust while taking steps to reduce data loss incidents caused by negligent or malicious insiders.
Almost half, 49% of respondents, say their organizations are not effective in their ability to monitor insider activity across hybrid and or remote environments. At the same time, 59% respondents report their organizations are not effective in creating trust while taking steps to reduce data loss incidents caused by negligent or malicious insiders.
The Ponemon-OpenText survey also reveals what needs to be done to achieve AI readiness based on the experiences of the 50% of organizations that have invested in AI. These include preventing the exposure of sensitive information, strengthening encryption practices, and reducing the risk of poor or misconfigured systems due to over-reliance on AI for cyber risk management.
“When deploying, organizations should develop an AI data security program, use tools to validate AI prompts and their responses, train teams to spot AI-generated behavior patterns or threat actors, use data cleansing and governance, and identify and mitigate bias in AI models for safe and responsible use,” according to the survey’s authors.
This study illustrates the emerging wave of challenges that organizations face as they increasingly rely on AI and GenAI to complete tasks, provide insights, and even run parts of their businesses. The ability to observe, monitor, and if necessary, intervene in AI-driven processes in real time has become the most pronounced challenge for enterprises of all sizes in the months and years ahead.
