Where 99% Of People ACTUALLY Find Value From AI At Work

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 TODAY’S THOUGHTS ☠️

Hey there 👋,

Spending the last 2- 3 years experimenting, exploring and helping companies make sense of Generative AI has given me a lot of useful insights.

Stuff like how people behave, what creates barriers to adoption, and what are the unknowns in all of this.

One of the biggest insights is how people are actually using AI for work beyond the gimmicks we see online.

What I continue to be pleasantly surprised by with AI use at work is that its the boring and basic stuff that’s most effective. For some reason, social media doesn’t like to tell us that.

Still, I’ve seen the most productivity, cost savings and quality of work improvements fall into this category.

Today, we’re exploring where 99% of people ACTUALLY find value from AI at Work and 3 standout use cases for everyone.

Oh, one more thing before we begin, I’ve just refreshed my AI Prompt Writing For Busy Professionals online course for 2025. You can learn more and get a special newsletter only 48 hour discount now.

Get your tea or beverage of choice ready, 🍵.

We've got lots to discuss!

 TL;DR 📰

• Finding real value with AI at work

• How to distill insights and humanize what you learn for an audience

• The systems for asking better questions

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 THE BIG THOUGHT 👀

Where 99% Of People ACTUALLY Find Value From AI At Work

One of the most common questions I’m asked by teams is: Where can AI REALLY help me at work?

That’s a question I like to hear.

Many people make the mistake of jumping to tools first instead of defining a problem.

I totally understand when a transformational technology like generative AI emerges, everyone wants to try it. And that’s great! One of the best ways to discover how these tools can be useful is through experimentation.

But, what we can do is apply a decision-making framework to structure that experimentation and ensure you’re using AI effectively.

The goal? Not bloody finding more use cases to create content - stop it!

Instead, I’ll focus on saving time, improving quality, and focus on more human things that matter. I like to class this as the boring and basic but HUGELY effective applications of AI in your work.

Not everything needs to be a huge multi-workflow project that takes more time to build and maintain than the ROI it provides.

Start with Tasks

Everything starts with tasks.

We use our skills to complete tasks. With AI tools, we can identify specific areas where they can provide meaningful support.

In relation to tasks, we should ask:

• How long do they take to complete?

• What is the output, and does it justify the effort required?

• What does ‘x’ task enable you to do?

• Is it repeatable and low margin for error?

This is by no means a complete list.

If we assess these and add the lens of AI assistance, we can find potential opportunities to work smarter.

Identifying opportunities

I’m certainly not the first to propose this.

LinkedIn CEO, Ryan Roslansky proposed a similar model back in early 2023.

This idea originates from Ryan’s Redefining Work article, where he explores how AI will accelerate workforce learning and amplify the importance of skills.

Ryan suggests moving away from viewing jobs as titles, and instead, seeing them as a collection of tasks. These tasks will inevitably evolve alongside AI and other technological advancements. He recommends breaking your job down into its primary daily tasks.

You can bucket those tasks in this format:

1. Tasks AI can fully take on for you, like summarising meeting notes or email chains.

2. Tasks AI can help improve your work and efficiency, like help writing code or content.

3. Tasks that require your unique skills – your people skills – like creativity and collaboration.

This sets the stage for how I currently recommend working with AI.

You could say my framework is the process before Ryan’s.

Without understanding your tasks, it’s hard to say if/how AI can support.

Let’s unpack three real-world examples from my own work where I’ve identified tasks that fall into this category, how I use AI to support me and why.

1/ AI in Meetings

I spend a significant part of my week talking to different teams and individuals about how AI and technology can solve their problems, especially in learning and development (L&D).

Many teams still think of AI primarily in terms of content creation, but there’s so much more it can do.

Most of my meetings range from 15 to 45 minutes. Like many of us, I scribble quick notes in a doc or on a notepad, but they’re often fragmented and hard to revisit later.

But I really want to focus on the conversation rather than taking detailed notes.

It’s super distracting for me when I’m like “I should write down what they just said” yet, that means breaking off mid-convo, too unnatural for me. By the time there is a break, I’ve usually forgotten what I was supposed to write down.

To solve this, I use an AI meeting assistant to join calls, record transcripts, and summarise key insights (if participants are cool with that of course - always ask!). This might seem basic, but as I always say, boring and basic is sexy because it’s efficient.

We all go to meetings, we all need notes and we all forget important insights and useful ideas.

It’s a shared pain.

Instead of spending hours sifting through notes, I can quickly review key takeaways and action points compield by my AI friend. Nothing gets lost too because I can see the original transcript if I sense AI is off base with anything. Like that one time it thought I recommended unicorns as a solution - another story for another time.

This allows me to focus on human conversations without worrying about missing important details.

It genuinely improves my life.

A few tools to explore:

• Read AI

• SANA (as part of their AI platform)

• Granola (a new one I’ve been testing)

If your organisation already has approved AI tools, use those. Microsoft Teams and Google Workspace both have built-in meeting assistant functionalities. Never use anything outside your companies infrastructure.

TL;DR:

Not only does this save time, but it enables better human connection and helps keep track of discussions from weeks or months ago without relying on memory or notebook doodles (why do I always draw skulls? Question for a therapist 🤔).

You won’t find a billboard that reads “My AI meeting assistant saves me time, enables greater social connection and improves my work” but maybe it should.

2/ AI for Insights & Summaries

For most of us, reports are part of our jobs.

You might read short articles, while others (like me) deal with 250+ page research papers.

But let’s be honest - who has time to read all that in depth?

What we actually need is a way to synthesise key insights quickly while maintaining depth where it matters. Kinda like being your own Harvard Business Review.

A lot reports and research are a lot of fluff, an underrated skill is to distill, humanise and share the best bits for action with your audience. No one needs you to regurgitate what the report said.

One tool I really like for analysis is Notebook LM, I have a separate ‘How to’ video of NotebookLM, which you can check out if you're interested.

It allows me to upload multiple documents (up to 300 🤯), analyse them together, and extract meaningful summaries.

Other AI tools help provide quick summaries, surface key insights, and even answer questions about reports and research too. NotebookLM is just my preference.

To be clear this isn’t about replacing critical thinking.

Instead, AI helps get that first layer of understanding:

• What is this report about?

• Why is it important?

• How can it help me?

This approach allows me to decide which sections deserve deeper human analysis rather than blindly committing hours to reading everything.

Something I find incredibly useful as these tasks eat up about 10 hours + of my week.

TL;DR:

AI summaries prevent wasted time on unnecessary deep dives, ensuring you focus only on the most impactful parts, and become better-informed vs overwhelmed with useless insights.

3/ AI in Data Analysis

We all deal with data in some form.

You don’t have to be an analyst to benefit from AI-powered support.

Whether it’s customer trends, sales numbers, content engagement, or HR reports, AI can help surface patterns that might otherwise take hours to uncover.

You can fire up literally any tools like ChatGPT, Claude, and Copilot to ask:

• Explain this data to me?

• How can I use it?

• What are the key insights and what are the actions I can explore?

Beyond data crunching, AI can even help you think more broadly by highlighting blind spots.

Again, helping you think critically in the process by working with AI to uncover:

• What you’ve missed

• What else could I consider (aka devils advocate)?

TL;DR:

Mostly, we look at AI to provide answers, but it can unearth better questions too. As always, the tools are only as good as the human using them.

Final Thoughts

If you’re sitting there thinking, I’d love to start using AI, but I don’t know where to begin, start with your tasks.

• ⏰ What tasks take up the most time?

• 🥊 Which ones require effort disproportionate to the value they create?

• 🤖 What processes could be improved with AI-assisted support?

Never forget, AI isn’t about automating everything.

It’s about enhancing your work so you can focus on higher-value, human-centred work.

→ If you’ve found this helpful, please consider sharing it wherever you hang out online, tag me in and share your thoughts.

👀 ICYMI (In case you missed it!)

• Using AI to distill and humanize what you learn

• Catchup on last weeks conversation about thinking like a human with AI

• My friends at Offbeat are hosting the learning festival you need to be at this summer. Forget packed exhibition halls and the same old speakers, this is about practical case studies and meaningful connection. And…I’ve even managed to bag a 10% discount on tickets for you, just use code: ROSS10 at checkout.

Till next time, you stay classy, learning friend!

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1. Ideas you’d like covered in future editions

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 TECH THOUGHTS 💾

How To Ask Better Questions

In this video, I get all fancy in exploring the psychology of designing a useful learning experience.

One thing I’m determined not to lose with more tech is the art of asking thoughtful and contextual questions with other humans. It is a skill that always needs sharpened. To do this well, you need to broaden your viewpoint.

Here’s a few strategies I find useful for that.

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