Future of work: AI employees, tech trends and AI tools
Future of work is no longer some distant conference topic or consulting report buzzword. It’s already clocking in every day for people working with tech, content, and digital business. One of the most interesting and talked-about examples lately comes from China, with the story of Vivi Mengjie Xiao, highlighted in a Business Insider feature.
Vivi is an AI product manager and works directly with AI-based products. Outside her day job, she keeps a pretty intense routine as a content creator on Rednote, where she shares AI tools, workflows, and insights on automation and productivity with more than 45,000 followers. All focused on an audience that wants to understand, in a practical way, how to get real value from new technologies at work.
Before building her AI automation setup, Vivi used to spend an average of four hours a day just hunting for news and updates on the AI industry. She read posts on X (formerly Twitter), newsletters, specialized blogs, reports, and also bridged the language gap, translating content from English to Chinese, filtering what made sense, and organizing everything into materials her audience could actually consume without drowning in information.
At some point, she asked herself the question a lot of people in tech are repeating these days: if it is repetitive and follows a pattern, why not automate it? From there, instead of just randomly testing tools, Vivi decided to go further and create a kind of mini digital team: six AI employees, each with a clear role, split between tasks in her professional and personal life.
This experiment became the subject of a Business Insider article, showing a very realistic side of automation: everything gets faster, but the workload and expectations on those who master these tools also go up. In other words, she is still working a lot, maybe even more, just with a different kind of effort.
Who is Vivi Mengjie Xiao and what changed in her routine
Vivi is not just a casual AI user. She works directly with artificial intelligence products and lives at the intersection of technology, business, and user experience. As a product manager, she needs to keep up with tech trends, understand how new solutions can be applied in the Chinese market, and turn that into features, improvements, and strategies.
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In parallel, as a content creator on Rednote, she shares:
- AI tools that can help professionals in different fields;
- Automation workflows to save time in daily routines;
- Insights on the impact of AI on the future of work;
- Summaries of global news and trends adapted to the local context.
The problem is that this curation work demanded an almost industrial level of effort. She says she spent hours every day consuming content in English, translating, reviewing, and adapting it into Chinese. It was not exactly a creative task, but it was essential to keep the quality of what she delivered to her audience.
That is where the decision came from: instead of accepting that workload as inevitable, she started to design AI agents capable of doing a big part of this heavy lifting. Each of the six AI employees was created to solve a specific, concrete problem in her routine, not just to fulfill some abstract idea.
What AI employees really are
In the original Business Insider piece, the term AI employees is used to describe AI agents configured to handle specific tasks, as if they were digital members of a team. They are not employees in the legal sense, of course, but they act as virtual collaborators that:
- Monitor information sources;
- Pull news from different channels;
- Translate content from English to Chinese;
- Do an initial triage of what is relevant or not;
- Organize everything into formats that are easier to review.
In Vivi’s case, these agents are split between work-related and personal life activities. Some help with AI content curation, others support everyday routines. The logic is simple: anything that follows a pattern, repeats similar steps, or depends on searching and organizing data became ideal territory for these AI employees.
It is important to highlight that, according to her account, they do not make final decisions on their own. Their role is to speed up the mechanical steps, leaving Vivi with the higher-value part: interpreting, contextualizing, and turning that material into useful content for her audience and into strategic input for her work with AI products.
The tech trends behind this story
Vivi’s routine is only possible because a few key tech trends have matured in recent years and moved from the lab into everyday use. Among them:
- Advanced language models that can understand and generate text in multiple languages with solid quality;
- Platforms that let you create and orchestrate specialized autonomous agents;
- Automation tools that connect with social networks, newsletters, blogs, and other content channels;
- Increasingly simple API integrations between AI, corporate systems, and productivity apps.
These trends do not appear in isolation. They combine to create a scenario where one person, without being a software engineer, can build an ecosystem of AI tools that automates large chunks of their routine.
In her case, automation covers steps such as:
- Monitoring English-language news sources;
- Selecting topics related to artificial intelligence and the future of work;
- Translating this content into Chinese with good readability;
- Organizing everything into blocks that later become posts, articles, or threads.
This is exactly where the concept of future of work stops being theory: it shows up in calendars, inboxes, shared docs, and routines that used to take up half the day and now run in the background with support from these digital agents.
AI tools and automation: less manual effort, more curation
Behind the AI employees Business Insider talks about, there is always a stack of AI tools that make everything viable. They can include:
- Tools to read and summarize long texts;
- AI-powered machine translation solutions;
- Systems for topic and keyword classification;
- Platforms that let you configure agents with clearly defined roles.
The benefit is not only speed but the kind of effort left to humans. Instead of spending hours copying, reading, and translating raw content, the person starts acting like an editor-in-chief: validating what agents suggest, adjusting tone, organizing the narrative, and bringing local, cultural, and strategic context that no AI can safely generate on its own.
This kind of automation also reduces the risk of information overload. In areas like AI and technology, where new stuff pops up all the time, keeping up manually is almost impossible. With smart filters and automated routines, the data flow becomes more manageable. It is still intense, but it is organized instead of completely chaotic.
Automation does not mean working less
One interesting point that the Business Insider piece highlights is that even with six AI employees, Vivi is not exactly working less. She admits she is still on a fast pace and feels quite tired. What changed is the nature of the work.
Before, the exhaustion came from mechanical, repetitive tasks: reading a lot, translating, cutting, pasting, organizing. Now, it comes from heavier decisions: choosing what really matters, interpreting complex trends, creating original content, and keeping up with a landscape that changes very quickly.
This helps clarify the future of work that is already taking shape:
- Machines handle volume, patterns, and repetition;
- People handle context, judgment, narrative, and relationships.
In practice, the workday can still be long, but the kind of outcome delivered levels up. The person stops being a manual task operator and moves closer to strategist, curator, and communicator. This shift is not necessarily easier, but it is more aligned with what creates value in a world dominated by data and automation.
What this story says about the future of work
The experience of Vivi Mengjie Xiao, shared in the Business Insider article, is a very concrete snapshot of how AI employees, tech trends, and AI tools are actually coming together. Instead of abstract debates about total job replacement, what appears is a hybrid model where:
- AI agents act as the operational base, handling structured tasks;
- Human professionals focus their energy on analysis, decisions, and creation;
- Automation reduces friction in daily processes but increases the expectation for more sophisticated results;
- The need to learn, adapt workflows, and review what AI produces becomes a permanent part of the job.
In the end, her case reinforces an idea that keeps coming up in the more serious future of work discussions: AI’s impact is not just about how many people will be needed, but about what kind of work each person will do. Professionals who handle these tools well tend to take on a more central role, precisely because they can orchestrate mixed teams of humans and systems, like Vivi does with her six AI employees.
The office of the future is not a place full of physical robots walking down the hallways, but an environment where most of the heavy lifting is done by invisible processes running on servers, integrated into platforms and apps. On this side of the screen are people making decisions, telling stories, connecting dots, and explaining to other humans what all of this means in practice.
Vivi’s story starts with a simple question – if it is repetitive, can it be automated? – and ends in a scenario where that automation became a structural part of her routine, without taking away her leading role, but completely changing how her time and energy are spent. And it is exactly through this kind of adjustment, repeated across thousands of different professions, that the future of work is being built, one automation flow at a time.
