Tom McLeod, are we starting to see the affects of AI on knowledge industries?

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Tom McLeod, are we starting to see the affects of AI on knowledge industries? It’s not just coders that are feeling the pain, as demonstrated by the enclosed article. Knowledge workers such as Human Resources are also starting to come under increased strain. As AI starts to bite into roles that some may have thought will not be replaced. Add to this the current levels of global uncertainty and challenges with the jobs market.

“What’s happening is there’s a huge white collar slowdown,” said Jane. “I think jobs are going away.”

One does not believe it’s simply jobs are going away, AI is providing the tools to reallocate resources. Through our own work adopting AI for education we demonstrated the ability to remove over 60% of the effort to develop cyber and AI education programs. Where once you needed a person to record a video to deliver a cyber or AI e-learning program, you can use Avatars. For our cyber audit work, where you needed an auditor to evaluate cybersecurity control artefacts for persuasiveness and quality. Then complete an audit. We did this at reduced risk, without sampling. AI did both of these exercises in hours rather than days.

In each case it didn’t remove the person-in-the-middle, it enabled the redistribution of effort and required different skills. In the case of audit, AI enabled the reallocation of resources, facilitating the completion of more audits. Certainly an opportunity, as cyber assurance is required by companies that have to comply with EU NIS 2 and DORA. In ones opinion the role of AI is complex and not about removing resources. Its about the reallocation of resource and the reallocation of low value high volume tasks.

LLMs have not yet captured all the information necessary to replace all knowledge workers. Just those that undertake more menial tasks, to which there’s an information publicly available. Even then, as a recent exercise proved you can’t, shouldn’t, always believe what you’re told by AI. When checking the output of AI against reality, AI was wrong in 30% of cases one examined. But it did remove a significant amount of analysis effort.

https://lnkd.in/enpdS7z7

@Thaddeus Dziekanowski Brian D. McCarthy Faisal Khan Dan Miles

Veritas GRC Aegis Labs

#artificalintelligence #cybersecurity #cyberriskmanagement

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