AI
If AI agents were to act unpredictably – say, infiltrating the internet or another company’ s systems – how would certification help reduce that risk? You would need a definitive AI policy so your staff members understand which AI to use – ChatGPT, Copilot, Claude, or Gemini and so on. Then you ' ll need to install appropriate agents on all laptops to monitor the prompts employees are feeding the AI and the info they ' re loading – and to block the harmful ones.
Employees sometimes unwittingly run a company policy through, or take source code from, say OpenAI or Anthropic. Through machine learning, the algorithm can identify the vulnerabilities in your organisation, and could then use agentic AI to attack your systems.
To prevent that, have the right policies in place; create awareness of the risks, and finally, the all-important third tier is installing the above-mentioned tools to prevent employees from sending out personal or sensitive company information unwittingly.
As an ISO AI consultant, how would you educate a client on the risks and solutions, and who would you be talking to? To the CFO. First, you need corporate buy-in, which to date, they’ ve considered a grudge cost. When presenting to the C-Suite, you need to demonstrate the risks with a simulation so they can“ experience” them. They need to know their risk appetite and determine how they want to mitigate it. Once there’ s buy-in, it becomes easier to create awareness programmes and gain adoption by the entire staff.
How could AI technology disrupt an entire business ecosystem? Take WWISE, as an example. Without the right governance or tools in place, many employees would use AI to look for errors in policies. Developers would use AI to identify errors in the code while developing a system, or use AI to get its interpretation or comments on a specific solution. The algorithm is biased based due to the weight source values of the datasets and algorithm sets they’ ve been trained on. The risk? We might develop a policy that has no real understanding of the human, empathetic aspect of the organisation and its ecosystem, and this might affect the adaptability of both the company and its staff. And as stated, running a source through AI ultimately leaves the company vulnerable to malware and rogue AI. If my decision-making team relies solely on AI for stats and facts, the disinformation and misinformation AI is prone to would ultimately cause a loss of trust in my company throughout our business ecosystem.
Will employees eventually trust AI more than their own managers or colleagues? In narrow domains, many already do, because AI doesn’ t posture, get defensive, or have political incentives. The risk isn’ t trust itself, but substitution of trust for verification: outsourcing judgment calls that should stay human because AI’ s confidence reads as neutrality when it’ s often just fluency. If you’ re looking for empathy, managers will always supersede AI. However, employees who work with facts and are not empathetic could trust AI over managers or colleagues.
Could we eventually see an AI failure become as significant as a major financial crisis or cyberattack in the coming years? Plausibly yes, and the mechanism is correlation, not any single model going rogue. It can precipitate a major financial crisis, too. When many organisations lean on similar foundation models, similar training data and similar automated decision pipelines, a shared flaw can propagate simultaneously across an economy the way mortgage-backed securities did in 2008 with the global financial crisis; same principle, faster propagation.
Are businesses preparing people to work with AI, or simply teaching AI to replace people? Upskilling initiatives are common, but headcount and budget decisions increasingly assume attrition-byautomation. The honest answer is, it’ s role-dependent – augmentation for high-judgment work, substitution for high-volume routine work.
Would younger employees be more likely to trust AI than experienced employees? Likely yes, but not simply; younger workers have lower switching costs and less accumulated patternrecognition to be threatened by, so AI reads as an ally rather than a challenge. Experienced employees often distrust AI ' s outputs less than its opacity because they ' ve built careers on being able to explain their reasoning, and a“ black box” violates that norm.
54 sabusinessintegrator. co. za