SuperMarketers

If you are a High Growth B2B SaaS, SuperMarketers Is Your Done-For-You Demand Gen That You've Been Needing. 

Our primary goal is to boost your SaaS revenue effortlessly with our expert, done-for-you demand generation services—saving you stress and costs compared to running an in-house marketing team.

Book Your Free 45 Minute Strategy Session To Learn How To Use AI To Scale Your SaaS More Profitably and Efficiently: 

👉 https://tidycal.com/genfurukawa1/45-min-marketing-strategy-session-with-gen-furukawa

Founder

MarketerHire

Course Creator and Lead for MarketerHire's first AI course. 

The course is a 30 Day Intensive on Content & SEO, teaching marketing experts and freelancers in the MarketerHire community.

Marketer in Residence

Content at Scale

Joined Content at Scale as VP of Marketing to build brand awareness in the AI writing space. 

In my short time there: 
- Built Content at Scale's Prompt Library -- created 10k prompts to help entrepreneurs, marketers, business leaders learn how to use AI to accomplish their goals. 
- Helped launch a community for Content at Scale. Educated members on AI use cases for marketing with weekly workshops, webinars, and tutorials. 
- Recorded 14 podcast episodes on AI and Marketing with industry leaders like Brian Dean (Backlinko, Mike King (iPullRank), Travis Jamison (Investing.io).

VP Marketing

Prehook

I co-founded and sold Prehook, a quiz platform for Shopify merchants. 

Our goal was to build a software to help Shopify merchants learn more about their customers with quizzes. 

In just a few minutes, merchants could publish a quiz to ask a few questions, capture an email/SMS, and recommend a product. No coding required. 

Brands like Spikeball, Smile Direct Club, Evolve Skateboards, JOI, Teelixir, Camille Beckman and hundreds grew their audience, captured zero party data, and drove incremental revenue with Prehook's quizzes. 

Created thought leadership around ecommerce quizzes and zero party data in:
- our blog
- weekly newsletter
- podcast (CartOverflow.com)
- industry events (2x eCommerce, AdWorld, ProductLed Growth Summit)
- Guest on industry podcasts (eCommerce Fastlane, $100 MBA, eCommerce Badassery etc)

Co-Founder

CartOverflow.com (podcast)

Learning and sharing ecommerce marketing with smart people doing cool things. Weekly episodes with interesting guests (operators, agencies, service providers, SaaS folks) alongside co-host Jeremy Biron. episodes at www.cartoverflow.com

Co Host

Retainable

Retainable helps B2B companies reduce churn.

Boost your monthly recurring revenue, instantly. Retainable helps B2B software companies create a flywheel — increased retention; higher lifetime value; higher MRR. Email me if you have questions: gen@retainable.com

Jungle Scout

On the founding team and first marketing hire, helped lead growth of the company to over 100k customers. 

Working alongside CEO and executive team, I am responsible for the marketing strategy, recruiting/hiring, and execution of all Jungle Scout products. This includes Jungle Scout, Jump Send, Splitly, and Fetcher. These marketing efforts have helped establish Jungle Scout as the market leader for all Amazon seller software and educational resources. 

Particular focus on customer acquisition and retention. The primary marketing responsibilities include growth from SEO, content, paid, social, email, copywriting, conversion rate optimization, YouTube and more.

Helped lead Jungle Scout's international marketing strategy, particularly the growth in the Chinese market. This includes recruiting and hiring the first marketer focused solely on the Chinese market, and establishing the Go To Market strategy, junglescout.cn site, and helping to manage the growth of the team in China. These efforts have contributed significantly to Jungle Scout's Annual Recurring Revenue.

Vice President of Marketing

Amazon Product Research, Made Easy. 

Leading the digital marketing efforts for the industry-leader in Amazon product research, I focus on strategy and execution of: content, email, SEO, paid acquisition, analytics, split testing, conversion rate optimization, copywriting, and more.

Head Of Marketing

Fetcher.com

Growth

Splitly

Splitly is the only tool to help Amazon sellers maximize profits by running automated split tests.

Jump Send

Building a marketplace for the top Amazon Email Automation and Coupon Distribution Tool. I focus on helping sellers leverage email follow up campaigns to gather product reviews and improve conversion rates.

Done-For-You B2B SaaS Marketing | Founder @ SuperMarketers: Generate More Leads Effortlessly | Let Proven Experts Handle It All | Book A Call To Learn How 👇

Are you a SaaS leader looking to improve your marketing -- more high-quality, inbound leads at scale?  

SuperMarketers is a Done-For-You marketing agency that handles everything: Strategy, Execution, Marketing Ops, and Growth. 

We can do this more efficiently, and with greater impact, with our proprietary AI-driven marketing system. 

At a fraction of the cost of growing your in-house team or working with traditional agencies. 

I can do this because I've been in your shoes. 

I was a bootstrapped co-founder of an eCommerce SaaS, called Prehook. 

We sold in April 2023. 

It was a six figure sale. 

I know that it would have been a bigger outcome if I had the SuperMarketers growth system. 

I am deep in the AI and marketing space: 

I teach AI and marketing (for MarketerHire, a global network of top tier digital marketers). 

I podcast about AI and marketing (podcast is called SuperMarketers of course).

Helping write a book on AI and marketing (with Jon Nordmark, CEO of Iterate.ai).

And of course I help B2B SaaS brands grow profitably leveraging AI and automation--market leaders like Octane AI, Iterate.ai, Pipio.ai, and more.  

Previously I was part of the founding team and VP of Marketing at Jungle Scout, leading a team of 25 marketers through the $110M fund raise lead by Summit Partners. 

Book a 1 on 1 Strategy Call With Me To Learn Exactly How You Can Use Ai To Scale Your Marketing More Profitably and Efficiently, Without Spending Any Money. 

➡️ Book It Now: https://tidycal.com/genfurukawa1/45-min-marketing-strategy-session-with-gen-furukawa

🌷 Gen Furukawa

Ross Hudgens analyzed 200 websites to see what's working in search.

1️⃣ ChatGPT traffic is flattening. 

2️⃣ Google traffic is growing.

But the type of content that ranks has completely changed.

For most B2B companies, pipeline is steady or growing even if topline traffic is soft.

The shift is in what kind of content actually drives results, specifically: 

✅ Guides and playbooks still get the most traffic.
✅ Comparison pages are holding strong.
✅ Pricing and cost pages are performing well.
✅ Case studies saw a lift in engagement.
✅ Trend content is getting attention.

What's dying:
🟥 "How to" posts are losing visibility.
🟥 "What is" definitions are getting buried.
🟥 Anything that can be answered in a single snippet isn't getting clicks anymore.

If an LLM can summarize it in one sentence, users never hit your site.

Some suggestions that Ross suggests: 
1. Move resources toward bottom funnel. 
2. Build out pricing pages. 
3. Create detailed comparisons. 
4. Add interactive tools like calculators or templates. 
5. Refresh your case studies.

And if you're going top funnel, make it complex, like use visuals, embed video, add proprietary data. 

Just make it multimodal enough that it can't be compressed into a snippet.

The main takeaway is that search is definitely going away, simply the bar for content is just getting higher.

Done-For-You B2B SaaS Marketing | Founder @ SuperMarketers: Generate More Leads Effortlessly | 1x SaaS Founder & Exit | Book A Call To Learn How 👇

A lot of AI content still seems AI and robotic because people give the model way too much freedom.

AI writes by choosing the most predictable next phrase. 

This pattern creates the same rhythm, the structures, and the same “AI cadence” everyone can spot instantly.... (ie "it's not X, it's Y").

But if you tell the LLM to “sound human”, it is ineffective because the model simply picks more predictable language that fits that request.

So if you want the writing to feel human, you have to break the model’s probability loop.

You can start by forcing a specific voice instead of adjectives, ideally your own! 

Specifically named styles collapse the generic phrase pool and push the model out of autopilot.

Also, add oddly specific details that only a real person would mention.

Humans anchor to moments and specifics, while models default to generalities unless you pin them down.

Another tip is to create a running list of common phrases and structures that models lean on.

The goal is to eliminate the smooth, symmetrical phrasing that gives away AI-generated work.

In short, don’t ask the model to “be human.”

You give it constraints that make predictability impossible.

I’ve been rebuilding my content workflow inside Claude Code, and it’s already changing how I work.

I'm not technical, and kinda regret the initial apprehension about using a "coding" tool....ChatGPT and Claude are definitely sufficient to bridge that gap. 

The screenshot shows part of the system I’m building to turn raw transcripts into structured insight...it can be for a podcast, sales transcript, internal call, etc. 

The folders on the left are not code projects, but just steps in a system that turns raw thinking into structured content.

This is probably how we will all work in the near future, creating small agents to handle a specific part of the process. 

Using this repeatable logic saves time and creates consistency.

For example, one agent takes a podcast transcript and turns it into the things I actually need, like Title, description, time stamps, etc. 

Another agent applies the AEO lens. It looks at what parts of that transcript are extractable, highlights ideas that match the patterns LLMs tend to surface and the pieces that help a concept travel into AI search.

Another agent turns those insights into outlines and content plans. This is near automated and instantaneous, with better quality because the inputs are structured.

In short, Claude Code forces any repeatable task intoa workflow that runs the same way every time.

Still early, but this approach already produces clearer insights and cleaner AEO structure. It also gives me more confidence in the content I deliver for clients.

Google just dropped Gemini 3 and it finally understands the world the way we do.

It reads video, audio, images, movement, and text together as one coherent input.

It goes beyond pattern matching and actually reasons through what is happening in a clip.

You can upload any video and get a true breakdown of what is happening frame by frame.

I tested it by uploading a video of my basketball shot to see if it could analyze motion, timing, pace, and mechanics.

It gave me strengths, weaknesses, corrections, and a plan based only on a few short clips.

But if you want more helpful applications as a marketer: 

👉 You can upload your top ads and ask Gemini why they land, why others flop, and where creative fatigue is creeping in.

👉  You can upload competitor ads to get a precise breakdown of hooks, pacing, messaging gaps, and unique angles they are winning with.

👉  You can record your landing page and ask Gemini to identify friction points, confusing copy, layout issues, and missed opportunities.

👉  You can pair video with analytics and ask which frames or moments likely cause drop-off or bounce.

👉  You can upload sales call recordings and transcripts to surface objections, tone shifts, emotional cues, and coaching moments.

👉  You can upload a product demo from a competitor and get a structured comparison of positioning, missing claims, and angles you should counter.

This is the first time marketers can turn raw video into structured insights without manual review.

This is also a preview of how search and discovery will evolve as multimodal understanding becomes the default.

And yes, I have a long way to go to improve my basketball shot...when asked who my shot resembles, one name was Kevin Martin, historically one of the funkiest shots in league history 😂

I built a small AI agent this week that does something I used to do manually.

It watches what’s being posted on LinkedIn in a niche. 

It captures what gets engagement. 

Then it analyzes the post the way an LLM would. 

Topics, hooks, angle, and how the idea is structured.

The output lives in Airtable, so it’s not just “inspiration”, but actually queryable intelligence.

How it works: 
	•	Pulls posts from specific thought leaders in a topic area, for me that was AEO and AI marketing.
	•	Stores the original post link and basic context.
	•	Adds structured metadata so you can filter and learn patterns fast:
	•	topic cluster
	•	hook type
	•	content format
	•	angle
	•	engagement proxy

This "intelligence hub" is actually a way to build leverage too. 

I’m not a developer. The build is mostly just clarity on inputs and outputs.

The setup for this: 
	•	Apify collects the posts.
	•	Claude Code is the control layer. I describe what I want in natural language, and it generates the logic plus the structure.
	•	Airtable is memory. The hub gets smarter every time new posts land.

One underrated move: 

I asked Claude Code to design the Airtable schema first. It gave me the fields and field types. I pasted it into Airtable and the table was basically done in under a minute.

AI doesn't generate more net new content, but is used to replace: 
	•	manual research
	•	random ideation
	•	low-signal posting

With:
	•	a living dataset of what the market is rewarding
	•	repeatable patterns you can actually see and filter
	•	direction that compounds over time

Oh and also inside the agent, there is a sub-agent for things like:
	•	hook optimization
	•	voice consistency checks
	•	banned phrases and banned structures

That’s how you keep outputs on-brand instead of generic.

WHat other agents would be helpful to build out for marketers?

LLMs do not read your article in its entirety.

It slices it into small chunks and only keep the chunks that express a single idea with absolute clarity.

If a chunk is scattered, the model drops it. and conversely, if a chunk is clear, it becomes part of an answer.

Here are five simple ways to create content chunks that are valued by LLMs: 

- A definition.
- A set of steps.
- A comparison.
- A direct question and answer.
- A real example.

These formats survive chunking, get reused in answers, and scale your ideas without extra effort.

Long rambling paragraphs that feel smart but break into unusable pieces....this was my (cringey) writing style in college, seemed to make sense but is not valuable then, or now. 

Write in a way that makes your ideas easily extractable, for LLMs and your readers. 

One idea per chunk.
One chunk per format.
Five formats that consistently show up in AI answers.

That is the blueprint.

Google just made a quiet but important change to AI search.

When you search something in AI Mode, Google now includes WHY certain sources are relevant.... before it shows the links.

This is important and relevant because AI search is no longer just about ranking, or being mentioned or cited, but being explainable is now important. 

Google’s AI is literally telling users “Here’s why I trust these sources.”

Content that wins now is:
 • clearly scoped
 • structurally organized
 • explicit about the problem it solves
 • easy for an AI to summarize and justify

And generic content is harder to explain. Death to AI slop 😅 

So when creating content: 
- Write content AI can summarize in one sentence.
- Use definitions, steps, examples, and FAQs.
- Build content systems, not one-off posts.

Structure matters a lot for visibility in AI search, and this is one more step in that direction.

AI-driven strategies for your business. I helped Fortune 500 companies to scale their marketing with data-driven insights.

For years, I helped Fortune 500 companies optimize strategy with data. But behind the dashboards and models, I saw the same problem everywhere: brilliant people buried in manual work, overwhelmed by complexity, and disconnected from impact.

That’s what pushed me to pivot — from analytical consulting to empowering businesses with AI that’s practical and human-centered.

Through my company AIMS (AI Made Simple), I now help forward-thinking teams turn AI from a buzzword into real, everyday results.

You can work with us in two ways:

1. Bespoke AI Training for Companies
We design custom learning journeys that empower your teams to solve real problems with AI — from prompting for better insights, to building custom AI assistants, setting up automated workflows, or deploying agents that handle repetitive work. Ideal for business like Marketing, Sales, Ops, L&D and beyond — no technical background needed.

2. AI Revenue Accelerator (for SMBs)
A 6-week program for small business owners who want to use AI to scale sales, marketing, and operations with plug-and-play AI systems. Zero fluff. No coding. Just proven results and step-by-step guidance.

Whether I’m on stage speaking at industry events or building AI workflows with your team — my mission is simple: Make AI accessible, practical, and profitable.

Valeriya Pilkevich

How much money do I actually spend on AI subscriptions each month? And… what’s the real ROI? ⬎

Yesterday I audited all my AI subscriptions.

Not because I'm a financial wizard (I'm clearly not).

But because after months of testing tools for trainings and running my own AI workflows, I wanted to see: what's actually pulling its weight?

So here's the breakdown - what I pay, what I use, and what ROI I'm actually getting:

→ ChatGPT (€17/month): 10 hours saved weekly mostly on brainstorming, research and as a strategy copilot. Though when I asked ChatGPT itself how much time it saves me based on my usage patterns, it claimed 20-25 hours weekly. You choose who to believe 😁 

→ Claude (€17/month): 2 hours weekly, I’m heavily using new Claude skills (esp. for copywriting and Notion workflows)

→ Gemini in Google Workspace (€13.60/month - needed for client trainings): 1 hour weekly, NotebookLM is my secret weapon for synthesizing research papers and prepping trainings. 

→ Microsoft (€10/month): not a Microsoft ecosystem person, need it for client trainings.

→ Zapier (€0): 5 hours weekly with Zapier agents that repurpose conversations into content and research prospects before discovery calls.

→ Make (€9/month): 3 hours weekly on business automations of very manual tasks.

→ Jotform agents (€0): 2 hours weekly with one Gmail agent that auto-labels and drafts replies in my style.

→ Descript (€20/month): 3 hours weekly on video editing (I do record a lot of training videos for companies). The new Underlord AI agent streamlines the whole process. 

→ Fathom (€0) - AI notetaker: 1 hour weekly on meeting notes and follow-ups (plus all the things you can do with these transcripts, from content to proposal creation to sales coaching).

→ Gamma (€10/month): 4 hours weekly creating or adjusting training slides for different clients.

Total monthly spend: €96.60.
Total hours saved monthly: ~124 hours

ROI: ~1,3 hours saved for every €1 I spend
And since my hourly rate is far above €1… the math is almost unfair.

But here's what matters more than the time savings: I'm not just doing MORE work. I'm buying back capacity to work ON the business instead of IN it.

P.S. Do you audit your AI subscriptions? What AI tool brings you the highest ROI? 

P.P.S. I didn't include HubSpot, La Growth Machine, Notion, Calendly, Butter, Tally, Mailerlite or Slack - these are daily business tools but either not AI-focused or I'm not using AI features.

Upskilling teams in AI | Certified AI Trainer | Keynote Speaker

I was so happy to have found my passion for teaching AI
until I realized it came with a baggage ⬎

Non-stop. Video. Editing.

Let me explain:

Most of my trainings are virtual (live) but there still around 50% that are recorded:

→ companies that want recordings for their LMS
→ pre-work or short explainer videos for students
→ our AI Revenue Accelerator (now 100% self-paced)

Back in May, I recorded and edited 30+ videos for AI Revenue Accelerator within just a few weeks (each 20+ minutes long). By the end of it, I couldn’t even look at a timeline or open another recording app. 

That is until recently I discovered the Descript’s update Underlord - a smart AI agent that helps you edit videos with simple, conversational commands.

And suddenly, editing didn’t feel like punishment anymore.

Here’s my 2 favorite ways to use it (and 3 others where it excels):

→ Record directly in Descript and let Underlord clean everything i.e. “Clean audio, remove background noise, cut filler words, add captions”

→ Turn slide decks into full, narrated videos i.e. “Take this PDF of my deck and turn it into a video about my company strategy.”

→ Transform long-form content (i.e. webinar or podcast recordings) into engaging social media clips i.e. “Make a TikTok-style explainer with subtitles, music, and a hook in the first 5 seconds.”

→ Add B-roll using stock libraries i.e. “Fill in all the media placeholders with stock video, based on my camera recording.”

→ Use templates to find more pre-built use cases: explainer, social clip, slides-to-video, and more.

If you want to give Descript a try, check it out here: https://lnkd.in/eqZBbVrr

P.S. What would you ask Underlord to do first? Clean audio? Pick the best cuts? Turn a deck into video?

#DescriptPartner #ad

"Where are all the women?"
Many of you asked me last time I posted about AI Meetup in Bangkok.

Yesterday I discussed this with James Devonport, co-founder of the largest UK’s AI conference and community Create With (with 50:50 male and female speakers btw). 

And we might have found an answer (keep reading).

Yesterday’s event was all about practical AI solutions - the kind non-techies can build with no-code tools:
→ Jake Hissitt emphasized human-centered AI adoption and reminded us that AI is an amplifier (read: if your content is weak, AI & Automation will only make it worse)
→ Boriwat Chanruang showed us how he alone identified and implemented 20+ AI use cases inside a 600-employee company - saving tens of thousands of euros.
→ Then Nattaphorn Natteerapong gave us the security reality check: "Don’t let AI tools code your business logic (if you don’t understand the code)"

(Unfortunately I was stuck in traffic 1h instead of planned 15 minutes - so yes, I missed the first two talks. And no, I’m not taking a motorbike next time 😅)

So, back to the “why so few women?” question.

After enough AI & tech events, I’m convinced:

It’s not a pipeline problem.
It’s a visibility problem.

Women are in tech. Women are in AI. Women are building workflows, leading transformations, and pushing innovation.

But they’re often:
 → not the ones representing the company 
 → not the ones sharing their work publicly
 → not the ones taking the mic
And in Asia, this gap feels even wider.

To make my point stronger: last week I attended a completely different event - a panel “Future of Talent & Al in HR”. 

The discussion went deep into the psychology, ethics, and safety of AI: how it shapes organizational decision-making today and what it means for the future workforce. We talked about the real blockers to adoption, the guardrails companies need, and how to use AI in a way that’s safe, human-centric, and performance-driven.

A completely different crowd - HR, L&D, leadership.
Industries where women dominate.

Still guess who was the audience? Mostly men.
(Except for two brilliant women on stage: Mila Devenport and January Jidapa P.)

So here’s my takeaway: we need more women
 → showing up
 → sharing their wins
 → being the face of AI, not the hidden engine behind it
 → stepping into the conversations that shape the future of work

P.S. What’s your take - is it visibility, culture, or something else entirely?

P.P.S. This time I took a more representative photo with James and Paphasanun - taken right after she told us this winter is extremely cold (25 °C at night and 32 °C during the day) we couldn't stop laughing 😂

Different continent. Different companies. Same AI adoption blockers ⬎

Last week I attended an exclusive AI event hosted by Dexian Asia Pacific – and honestly, it felt like walking a red carpet at Crown Plaza Bangkok.

But the real spotlight?

The conversations happening between sessions.

Because whether in Frankfurt or Bangkok… leaders are wrestling with the exact same 3 blockers: 
→ Scattered data 
→ Unclear use cases 
→ Cultural resistance

Different markets. Same patterns.

Let me share a few standout moments:


1️⃣ “Data is still 80% of the consulting work”

Everyone wants “advanced agents”.

But here’s the truth: for real AI transformation – whether that's rich insights, proprietary models, or agentic AI – you need data foundation first.

This sounded very familiar: when I worked at Kantar, we needed historical weekly data (marketing, sales, competitive landscape) for marketing mix models.

Do you know how often that data existed in one place?

Almost never.

It was scattered across teams, agencies, tools… or simply didn’t exist.

That's why data literacy must come before AI literacy – especially as we move toward agentic future.


2️⃣ Many companies are stuck in “Optimize” mode

Cutting costs.
Cleaning up workflows.
Automating the obvious.

Important? Yes.
Transformational? No.

The real value lies in:
→ Redesigning entire workflows
→ Using AI to create new revenue streams
→ Innovating business models instead of polishing old ones

You don't get there by dumping GenAI tools into an organization and hoping for magic.


3️⃣ Culture is the real bottleneck

Speakers reiterated something I see in every corporate training:
Expectations shape success.

Teams hear "AI boosts productivity" and immediately wonder:
What happens to the time we save? What happens to us?

AI-first isn’t a tool strategy.
It’s a people strategy.

Your employees storing the data in Excel tables today (and yes, this came up multiple times – many companies are still running their business in Excel) won't magically become AI-fluent tomorrow.

The gap is real. And it requires intentional bridging.

--

And my personal highlight: an inisghtful conversation with Ashu Bhatia (ex-Accenture US, author of "Value Creation"). I also convinced him to be a guest on my new podcast (more on that soon 😉).

P.S. What's blocking AI transformation in your organization – is it data, culture, or strategy?

Are you buying the drill to make more holes? 
Or to fix that crooked shelf? 

Many people I talk to don't know where to start with AI.
So they start by buying tools.

My advise: "Always start with a problem".

Ask yourself:
“What are my biggest bottlenecks? Time drainers? Things I’d happily outsource if I could.”

Here were mine:
→ Living in my inbox: organising and replying to emails 
→ Jumping on discovery calls unprepared (or spending hell lot of time researching somebody)
→ Complaining about no ideas & no time to post on Linkedin… while sitting on hours of webinars, podcasts, and client calls full of gold

So I built 3 agents:
→ One to research prospects & companies before the calls
→ One to repurpose my conversations into content 
→ One to organize my emails and draft replies

And if you’re thinking: “Of course she did - she’s an AI expert.”
I can guarantee you can replicate this entire set up in under 30 minutes. 

How? I will show you this Friday during the Lunch&Learn session organized by wonderful James Cameron from BigRock Intelligence.

[Updated] Recording here: https://lnkd.in/eWraeyns

3 AI Agents I actually use - and you can too!

"Will AI make us dumber?" I addressed this question yesterday at Fraport's Speakers Corner ⬎

A few weeks ago, Arthur Michael Seidel reached out to chat about AI adoption. 

We instantly clicked - he's built something special at Fraport AG: a platform for dialogue around the future of work.

When he invited me to run a session, I wanted to genuinely shift perspectives.

So I took the three biggest concerns I hear everywhere:
→ "AI makes less sharp" 
→ "AI will take our jobs" 
→ "We need to completely reskill"

And flipped them: 
→ AI can enhance our thinking 
→ AI can increase our job satisfaction 
→ AI makes uniquely human skills more relevant

So, does AI make us dumber or stronger?

The research is clear - it depends on how we use it.
→ Passive AI use (just consuming answers) = weaker thinking 
→ Active AI use (as a sparring partner) = enhanced judgment

I showed NotebookLM as an example - not just for summarization, but as a learning companion that explains, questions, and adapts to your learning style.

On job loss:
AI is transforming jobs - it makes us do more meaningful and strategic work.

World Economic Forum projects 90 million jobs will disappear by 2030, but 170 million new ones will emerge.
→ Less data entry and admin
→ More problem-solving and strategic thinking

I did a live Power Automate x Copilot demo showing how one simple workflow can free up mental space for work that actually matters.

And that third concern about needing to reskill in STEM?

The most valuable skills through 2030 aren't coding - they're analytical thinking, resilience, creativity, and the ability to work with AI systems as collaborators.

Think agent management skills: communication, delegation, orchestration.

The reality?
Teams that combine human judgment with AI fluency don't just get faster - they get better.

Big thanks to Arthur and the Fraport AG team for creating spaces where these conversations happen.

P.S. If you're building long-term AI capability in your organisation and want a strategic partner on that journey, let’s talk.

P.P.S. When it comes to the latest research on behavioral science x AI, metacognition, Human-AI collaboration Fendi Tsim is my trusted source. Highly recommend to follow him.

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