Proven Ways Generative AI Can Boost Your Productivity as a Knowledge Worker
If you are a productivity enthusiast like me and you didn’t live behind the moon for the last couple of months you surely have had contact with generative AI. It has transformed the way we consume and create content and people (and markets) see enormous potential in it.
Is it a hype?
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| Photo by Windows on Unsplash |
I’d say so.
But just partially. Indeed generative AI has a huge potential to supercharge personal productivity.
Where it’s not quite there yet (in my humble opinion) is replacing entire jobs. However, even small changes to your workflows can easily double your productivity.
In today’s article, I’ll share how I use generative AI in my role as an IT and Digitalization Manager.
Let’s dive into it.
Why generative AI matters for productivity (and where it doesn’t)
The most common form of generative AI are text-based large language models (or LLMs in short). This means they can do one thing: predict a word based on the previous word.
But LLMs can do it with such good accuracy that it can seem as if it had a conciousness. It surely is intelligent, but if it really has a consciousness is a different discussion (I discussed it in my article on Nexus, if you are interested).
So what can a text-based LLM do that can improve your productivity?
Read, analyze and create text.
According to a study by McKinsey employees in an office environment spend about 47 % of their work on such tasks: reading and answering emails as well as searching and gathering information.
If generative AI could just half the time for these tasks, it would mean a productivity increase of more than 20 %.
Generative AI is powerful, but it’s not (yet) a one-size-fits-all solution. There are still areas where it falls short. For example, most corporate IT landscapes are a mix of modern, AI-ready tools and legacy systems that remain critical to business operations. These older systems often just lack the flexibility for AI integration and need manual intervention.
The same applies to creativity.
Generative AI can help you brainstorm and produce impressive content, but it doesn’t truly invent something new. It recombines what already exists. Real innovation still requires human imagination and judgment.
And when it comes to repetitive tasks, AI isn’t always the best answer. While automation with AI works in certain niches, classic automation methods are often more accurate and, most importantly, more reliable.
But I don’t want to dwell on the limitations.
Let’s focus on where generative AI shines, because in the right areas, it can supercharge your productivity like nothing else.
My top use cases for generative AI
Working with text
This is the most obvious use-case for generative AI and for most people the first touching point with it. Generative AI is extremely good and fast at …
- Drafting emails, reports and documentation
- Translating text
- Creating summaries for complex topics
- Text synthesis
But you’ve surely read those AI drafted emails. In many cases you can identify AI-created content quite quickly. Especially if you know the people you communicate with and they are suddenly starting to use phrases you wouldn’t expect them to use.
I do use it for drafting (or improving) emails, but I always change the wording to a more natural formulation. In my opinion generative AI can be a good tool for critical emails (that go out to a lot of recipients, where each formulation will be judged, …).
But let’s be honest you won’t win a war by shortening email tasks by a few percent.
My biggest productivity boost came from using generative AI to summarize content. As an IT and Digitalization Manager, I deal with numerous documents: often in foreign languages or filled with legal jargon. Instead of skimming pages, I let AI summarize and highlight critical passages for focused reading. Chatting with a document is equally powerful and let’s you focus your time on the more critical aspects.
This becomes invaluable when cross-referencing regulations or multiple documents. Generative AI excels at synthesizing content. For example, checking a new supplier contract against cybersecurity regulations: in corporate environments, these regulations are sprawling, versioned, and full of add-ons. With AI, you can compare the contract to the regulations and flag deviations. It works best when you brief the chatbot with a persona, such as a cybersecurity expert.
And then, if you have to write a report, AI can sum it up for you or act as a professional editor by optimizing the text you’ve created (as I did with the last paragraph).
Search content
Are you still using search engines, or do you belong to the group of people who use generative AI tools such as ChatGPT as a search engine?
I currently use both.
For highly targeted searches, I still prefer Google. It just feels more precise. But when it comes to exploratory searches, I lean toward ChatGPT and similar tools because they offer richer capabilities and context-aware results.
Where generative AI truly shines is in searching your own content. Thanks to its integration with the Microsoft ecosystem, Microsoft Copilot makes finding documents effortless - even those buried deep in a folder structure with 5+ subfolders. Weeks later, when you’ve forgotten the exact title, Copilot can still locate the file. Either with its index, context-awareness or by searching within the document itself.
Personally, I easily save several hours every month by using Copilot to search files and documents.
Coach for decisions
A few years ago, I came across a simple idea that completely changed how I think: if you want to structure your thoughts, write them down.
So I started writing - a lot. This blog was born from that habit and even at work, jotting things down became my secret weapon for clarity. Whenever I faced a tough decision or an uncertain situation, I’d sit down at my keyboard and brain-dump everything (fast writing with 10 finger system helped).
It worked, but here’s the catch: after a while, I’d have pages of notes and still no clear picture. That’s when I started experimenting with generative AI.
I feed my messy thoughts to AI and ask it to play the role of a coach. Sometimes I told it to be a business coach, sometimes a mindset coach, depending on the problem. Honestly, I expected nothing more than a brief summary.
But the results blew me away.
It didn’t just organize my ideas. It helped me reflect, challenged my assumptions, and even sparked new directions.
Writing will always be powerful tool for structuring thoughts, but pairing it with AI? That can become next-level thinking.
Idea generation & Problem solving
AI isn’t inherently creative. It doesn’t invent ideas from scratch. It recombines what already exists.
But here’s the thing: most innovation works the same way - by connecting existing concepts in new ways.
That’s also where AI shines.
When you feed it your own ideas, AI becomes an exceptional brainstorming buddy. It can surface related fields, suggest fresh angles and give you instant access to vast knowledge (and the internet if it’s connected). With just a few keystrokes, you tap into the collective intelligence of the internet without the need of moving on to Google search.
Personally, I use AI to generate multiple solution paths. By adding my own input, I create a solid decision framework. After a few back-and-forth iterations, AI delivers a well-structured set of options - each evaluated against different metrics for easy comparison.
The final decision, however?
That’s mine.
And for the foreseeable future, it will stay that way.
Tools I use daily
Today, the AI landscape is vast and evolving at lightning speed. While ChatGPT is arguably the most recognized name, it’s far from the only option. Multi-purpose AI solutions like Google’s Gemini, Claude, and Microsoft Copilot are gaining traction, alongside specialized tools such as Grammarly for text refinement or Suno for music creation.
So, which tools should you use?
The answer depends on two key factors: your profession and the ecosystem you already work in.
For office-based work: start with multi-purpose solutions
If your day-to-day revolves around text-based communication, multi-purpose AI platforms are often the best fit. But with so many choices, how do you decide?
Personally, I use Microsoft Copilot.
Why? Because my organization is deeply integrated into the Microsoft ecosystem with MS 365. Copilot fits seamlessly into this environment, making it a natural choice.
Your situation might differ. If you’re working within Google’s ecosystem, Gemini could be the better option.
Connect AI to your knowledge base
In my experience, the true power of AI in office work lies in its ability to connect with your knowledge base.
When AI has access to your documents, workflows, and context, it transforms from a simple assistant into a second brain on steroids.
Practical Tips for Getting Started
I’ve spoken with two types of people in my organization (and beyond): those who use AI heavily and those still wondering if they should try it. If you’re in the first group, feel free to skip this part.
If you’re unsure whether generative AI is worth your time, here’s my advice: give it a try. Most tools are free to start with, and you don’t need a complex plan. Begin with simple tasks like:
- Summarizing a text or webpage
- Translating between languages
These are great entry points that show AI’s practical value without overwhelming you.
Don’t overthink how to integrate AI into your workflows. Start small. Use it for specific tasks like translations. Trust me, once you see the benefits, AI will naturally become part of your productivity toolkit.
As you start using AI more, remember two things:
- Combine AI with human judgment. Never blindly trust its outputs.
- Keep security and compliance in mind. This is critical if you handle confidential documents.
If you follow these principles, generative AI can become your secret productivity supercharger.
Conclusion
There’s no shortage of memes claiming that generative AI will replace most jobs in the next few years. In my view, that’s far from reality.
While AI can dramatically boost personal productivity, without seamless integration and true agentic capabilities, we’re still a long way from replacing entire roles in knowledge work.
Instead of fearing disruption, focus on leveraging AI as a powerful assistant. One that amplifies your skills rather than replaces them.
Thank you for reading! What’s your perspective on AI? Do you see it as even more transformational? Let’s continue the conversation, connect with me on LinkedIn!