Increasingly, many of us are using ChatGPT and other GenAI tools* for work to help with a diversity of knowledge tasks. We may share with our colleagues how much doing so has improved how we work, for example, saving us time and making us more efficient, while revealing the ways they are helpful, for example, generating ideas, writing or seeking information. However, in many workplaces, it is frowned upon to use them and in some outrightly banned. The main reason given is confidentiality; the need to protect sensitive, personal or proprietary data. Many banks, tech companies and healthcare providers are concerned about the risk of data exposure, where workers might divulge confidential information (e.g. new products or plans for new investments) when using ChatGPT. Instead, they are provided with in-house AI tools, which may not be as good or easy to use.
It is a well-known secret, however, that a number of professionals, who work in organisations where public GenAI tools are banned, may use them furtively on their own devices, while working from home, and without letting their colleagues know. Recognising that the genie is out of the bottle has led to some organisations rethinking their policy on barring the use of ChatGPT. For example, earlier this year, the UK’s Department of Work and Pensions (DWP) reversed its ban. It has recently begun allowing its civil servants to use them for official business or when using government-issued devices (with the exception of DeepSeek). They realised the benefits outweighed the risks. On their website, it now says how it can help employees respond more quickly to queries, while providing their customers with “a more personalised and seamless journey and access support how and when they choose”. Not only does this public acceptance remove the stigma and guilt of using ChatGPT at work for these employees but it might end up triggering a snowball effect, leading to other departments following suit. The question this raises is where should organisations, who have sensitive data and proprietary information, draw the line for what is acceptable practice and what is not?
Consider the healthcare profession where it is important to get this right. Similar to DWP, it is now widely accepted that using ChatGPT at work can be useful and beneficial for clinicians, especially as they have lots of admin tasks, such as note-taking, generating summaries, and treatment plans, which we know ChatGPT is very good at. Most likely, most people, including patients, would not object.
But what about other aspects of general practice where clinicians would like to use it, but where patients might find it unacceptable? To find out, the UK’s NHS is trialling various AI tools in a number of GP practices, where they will be used to summarise consultations with patients (online or in person) that will then be used generate clinical notes and referrals using customised templates. Findings from an initial pilot study run at GOSH, using the ambient AI voice technology called Tortus showed it saved a lot of clinician time. Patients were also very positive, noting how it enabled the cllnicians to give their full attention to them during the consultation.
Where using GenAI tools is clearly unacceptable is when making a decision about a patient’s treatment or surgery. It is considered a no-no for clinicians to ask it to suggest the best course of treatment for one of their cancer patients. What would a patient think, if a clinician said to them, “I just checked with ChatGPT and it recommended we use a new form of cryotherapy that freezes the cancerous tissue within your prostate to destroy the cells rather than opting for the more commonly used High-Intensity Focused Ultrasound (HIFU) that heats and destroys cancer cells within a targeted area of the prostate.” Most would balk at the idea that a machine was deciding their fate. Patients in this situation are highly anxious and want reassurance that the decision that is being made about their treatment is being made by human expert doctors. Even though the AI could be trained to make better and more informed decisions like these, patients will most likely persist with wanting human reassurance and human decision-making.
What other aspects of clinical decision-making might patients be more willing to accept for the AI to do if it helps the clinician in their work? What about the research clinicians need to do to keep up to date and discover the latest procedures? Rather than looking up information in online medical journals (e.g. PubMed), themselves, why not ask ChatGPT? It could speed up the research process for them in the way many of us now regularly use ChatGPT to get started on a project. It might also suggest alternative types of surgery or care plans that the clinician might not have thought about or discovered by themselves. Would this use of ChatGPT as a research assistant be acceptable by the medical practice, if it was increasingly found that clinicians were already doing this but without letting on?
Besides the various ethical reasons that have been espoused for not using AI at work, human nature, itself, can play a role in determining what is acceptable and what is not. Our propensity to judge each other all the time about what we do, what we eat, what we like, our appearance and so on is also shaping our perceptions of whether it is OK to use GenAI. Some people will shake their head in disapproval when discovering one of their colleagues has been using ChatGPT at work for tasks that were previously ‘done by hand’, for example, using it to write a farewell note for someone’s leaving card, composing a welcoming speech for new employees, or summarising feedback following an appraisal. It seems disrespectful for those on the receiving end, to the extent, some of us might feel shame if we were found out to have done this.
Another growing complaint is the output from AI tools is bland, homogenous, and lacking personality. A new term that has caught the public’s imagination is sycophancy, which refers to how AI appears to always want to please the user, agreeing with them, giving them positive feedback while avoiding providing criticism. To be human is often far from being sycophantic – we like to be different, funny, critical and at times we can’t help being sarcastic – qualities that AI has yet to demonstrate in any human-like way.
So, where do we draw the line between what is acceptable and what is not when using GenAI for work? As new versions of AI tools materialise that are smarter with more safeguards in place, it will probably end up being a case of moving the goalposts. Furthermore, as people start using them for a wider range of work tasks, it may have the knock-on effect of changing their opinions and perceptions; they may become less concerned about professionals (e.g. teachers, doctors, lawyers, financial advisors, pilots, and politicians) using them in their work.
Current research is also discovering there is a shift in professional’s perception of using AI to help them with their work. For example, radiologists have begun to value more AI assistance for certain tasks such as gathering relevant data to inform their decisions. Pilots, likewise, are also more willing to have AI at hand to assist them for certain tasks; for example, presenting seminal information clearly and highlighting constraints at nearby airports. They draw the line, however, for when the AI suggests a course of action they should take. That is their prerogative.
In sum, so long as the role of GenAI is to assist, i.e., to inform us, enable us to complete our tasks more effectively, suggest alternatives we might not have come up with ourselves or extend what we can do, then it will continue to be increasingly adopted in all manner of workplaces. It is only if it starts to be used to take over complex and sensitive human tasks that it will be concerning and troubling, Many people will very likely want humans to continue to do them.
* I use ChatGPT here as an umbrella term for all GenAI tools. The image was generated using ChatGPT-5





























Why is there so much hype about the Metaverse these days? It has even taken over from AI as the hottest tech topic. Last week when I asked Matthew Ball, the author of a forthcoming book about it, if I could take a peak inside he told me unfortunately no since the publishers want to keep it under wraps until it actually comes out in print. According to the blurb on






































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