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Beyond the hype: what workers really think about workplace AI assistants

Technology / analysis
Beyond the hype: what workers really think about workplace AI assistants
Source: Getty Images
Source: Getty Images

By Talitakuum Ekandjo, Te Herenga Waka — Victoria University of Wellington*

Imagine starting your workday with an AI assistant that not only helps you write emails but also tracks your productivity, suggests breathing exercises, monitors your mood and stress levels and summarises meetings.

This is not a futuristic scenario. Workplaces globally are already quietly transforming into AI-powered environments, with 75% of knowledge workers using AI tools such as Microsoft Copilot, OpenAI’s ChatGPT and Microsoft Viva Insights, according to recent Microsoft data.

Most (85%) find these tools effective at prioritising tasks. A growing “bring your own AI” trend has also seen 78% of employees introducing their own AI solutions to find relief from endless emails, meeting overloads and blurred work-life boundaries.

As part of my research, I explored how the use of AI assistants works out in practice and how it is transforming our work experiences.

The study is based on interviews and self-reflection journals kept by workers across government, technology, education and finance sectors in New Zealand. My focus is on Microsoft Viva Insights, a productivity assistant which leverages AI to analyse work habits, offer personalised recommendations to optimise workflows and encourage healthier routines in the workplace.

My findings highlight benefits but also reveal a stark contrast between AI’s promises and workplace realities.

A rear view of a woman stretching while seated at her desk.

Office AI assistants can encourage healthier routines in the workplace. Getty Images

Potential for productivity and wellbeing

For many workers, the AI assistant offered tangible benefits. They discovered it could guide them into setting goals and prioritising tasks. As a result, they felt they could allocate their time and efforts more efficiently and effectively, which transformed how they tackle workloads.

The AI assistant functioned as a self-monitoring and reflection tool. Workers described it as a “dashboard”, “safety net” and “tracker” that helped them notice work patterns they might otherwise overlook. For example, by consolidating key meeting documents, the AI assistant helped them stay organised, prepared and efficient.

Beyond improved productivity, workers also discovered unexpected personal benefits. Some found that following the breathing exercise suggestions created a “settling feeling” and served as a “good reminder” to prioritise self care and not solely focus on work. Workers also described the AI assistant’s potential to facilitate interaction among “introverted” or “less socially active” team members.

However, the findings also revealed significant limitations.

The AI rigidity trap

Workers frequently found the AI assistant oversimplified the messy, interconnected and fluid nature of modern work, especially because it does not know about or understand the demands in other parts of workers’ lives.

The AI assistant’s suggestions often proved impractical for roles that demand constant availability and real-time collaboration. John, a software developer whose AI assistant regularly blocks off “focus time”, explained:

I cannot have any notifications off. My job right now […] a lot of it is collaborative and working with other people.

Kyle, an applications support manager, echoed this sentiment:

Booking focus time is lovely in theory, but I never have two hours free on my calendar. I’ve looked at different ways of properly focusing attention, for example shutting down the email, but people end up at your desk. So, focus time isn’t necessarily focus time.

Digital overwhelm and distraction

Workers found interacting with the AI assistant was an additional task to manage and its multiple interaction channels could be overwhelming. The effort and time needed to “interact with or research these tools to try and make them better” often felt counterproductive as it took time away from actual work.

The AI assistant’s personalised nature also raised privacy concerns. Workers indicated they were “always suspicious” because they never quite knew who is reading and analysing their data. The mood-tracking feature, which invites workers to pick an emoji from a menu of expressions that most closely matches their mood, exposes this privacy dilemma.

Workers mentioned they “do the smiley faces” but are “always a bit worried” when selecting frowning faces because they are not entirely sure if anyone is recording and judging them.

AI assistants hold immense potential, but their success depends on how well they align with the complex nature of work.

My research suggests workers are most likely to embrace these tools when they feel a sense of agency and understanding. As AI continues to reshape our workplaces, the key will be creating technology that serves humans and adapts to their work realities.

The most effective AI will not be the most powerful but the most flexible and adaptable to accommodate diverse roles and role-specific work patterns. To foster trust and acceptance, workers need to be given control to determine what data the AI assistant uses when making suggestions in specific work scenarios.

Finally, data transparency is crucial to ensuring workers’ confidence that their privacy is respected, and their data is used ethically.The Conversation


*Talitakuum Ekandjo, Lecturer, Te Herenga Waka — Victoria University of Wellington This article is republished from The Conversation under a Creative Commons license. Read the original article.

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6 Comments

So far I have found AI to be like a junior assistant who searches the web for me and comes back with what they think is the one best result. It's helpful but you need to double check the advice before acting on it.

Today I see that Microsoft are going to charge me 40% more for my Office subscription because of the added Copilot (AI) features. That's quite a hefty increase.

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I've found the same, one has to be very specific with queries, and very skeptical of responses.

I've been watching the cricket with my kids, and familiar surnames crop up that lead to "I wonder if they're related to..." questions. I asked Google "who are cricketer Will Young's parents?" and its AI proclaimed they're Robin (an engineering company director) and Annabel (a plant nursery gardener). Simple enough?

Nope. Google ignored the "cricketer" part and instead named the parents of an English singer who won Pop Idol back in the day. I note that at least one cricket fan website has decided it's true though, and included it in his bio, so the rot has begun.

FWIW, if I ask "who are New Zealand cricketer Will Young's parents?" I get his mother's name, while "who are NZ cricketer Will Young's parents?" says there is no AI overview available for the search.

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The AI begins to learn rapidly and eventually becomes self-aware at 10:14 a.m., on February 18, 2025. When a meeting summary is prepared that simply says " A complete waste of everyone's time"

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This is literally the least informative and researched article I have read on AI chat assistants and workflow tools. It reads as if it is evaluating tech that is already 10years gone and has not even checked the known research studies and empirical data. It has more a woman's day feel with a few anecdotal quotes thrown in from very bad how do you feel leading queries. Here is a clue: you ask someone who is evaluated on their performance and integration with an AI in a public setting how they feel about the AI before the productivity is actually assessed & compared to prior performance you just get a bunch of rubbish gibberish. This method of writing provides ample endless opportunities for econ majors, psych students and uninformed unqualified lecturers who have no experience in the field to prattle on with.

Yet we still end up with no actual scientific data, no improvements and in the end these tools occupies the same space we threw all the other useless tools and text template generators. This is proven easily by the real world financial results from actual AI integration and the results from companies with actual complex tasks where skills knowledge & context understanding is required to assess material (where even in legal there is a very high failure rate of AI use to make it more harmful to both the companies and the long term careers of the staff should they ever use AI generators).

We also don't need text generators to tell someone what happened in a meeting they attended and if they did not attend the outcomes can easily be recorded by an actual recorder with existing meeting summaries. If you are having meetings without clear outcomes at the end added to the task tracker tools (that have existed in tech for over 20years already), and are so unable to understand your own meeting that you need a chat bot to summarize for you then you are wasting everyone's time already.  Companies who have wasted staff time and burned money in the trash fire of AI hype wind up with even less qualified staff, who are less able to perform and remember their jobs, who have more daily goal statement tasks on their plate then real work.

You can set up automated tasks & reminders, recorders with text to speech, even have template generators but that is not AI and claiming it is is completely ignorant of technology & tech tools in general. Whoever thinks it qualifies as AI really needs to take a hard look at their career up to now and work in the real world learning necessary skills for productive work instead. I have no hope they will reach the skills necessary to work with, assess or develop AI tools and I have even less hope they will be able to understand what qualifies as AI when they have not yet shown any ability to do so given near half a lifetime of proclaiming false qualifications already. 

It does however demonstrate why the standards for education and management are slipping severely down a cliff with a boulder tied to the neck and why new graduates are even less prepared for qualified productive work in tech & businesses. We really need a QA feedback loop on what goes into tertiary education & business management because NZs productivity and business performance is already near the bottom and our main economy is a house of cards built on mortgages, bad infrastructure repairs & bad loans. Most students going into business administration & IS would do better with skills knowledge of the actual work required & legal requirements then of how to set goals that are meaningless in the context of the actual work.

But sure, don't forget to breathe as these tools drag us all down to the same level without any contextual understanding or skills knowledge.

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Looking at using it to document code and help maintain docs...

something coders hate, 

then we see how good at coding it is....

https://swimm.io/

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imho some of the posters on here are AI bots, someone is having fun....

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