key topics

Design budget and investment visibility

Leadership’s role in design culture

Integrating design into business strategy

takeaways

Design budgets are often scattered and hidden across departments.

The real investment in design can be ten times higher than perceived.

Leadership support is crucial for embedding design as a strategic capability.

Design should be treated as a core function with governance and ownership.

Understanding actual customer perceptions requires direct observation and mapping.

In this episode, he shares insights on measuring the impact of design, building a design center, and navigating organizational politics. Quint also highlights the significance of intuition, creativity, and the ability to say no in design leadership, providing valuable takeaways for aspiring design leaders.

Eric is former Chief Brand and Design Officer at 3M Company (United States) and former Vice President and Head of Design Management and Consulting at Royal Philips (the Netherlands).

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Eric’s Linkedin: https://www.linkedin.com/in/ericquint3mcdo/

Design Leadership Ignited - Elevating Design at Scale: https://www.sup.org/books/business/design-leadership-ignited (also available on Amazon)

Design leadership at scale requires leaders who design the design function, establish a thriving environment for the creative team, and shape the design organization to drive progress, advance innovation, and enhance meaningful customer experiences.

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Eric’s white papers and publications (Linkedin Featured section):

• Foreword for book “Research for Designers” by Gjoko Muratovski (3rd edition, 2024)

• Journal of Innovation Management: “Collaborative Creativity: A Design Approach to Systemic Challenges Navigating the Innovation Ecosystem.”

• Journal of Design and Allied Sciences: “Designing the Future: How Balanced Design Leadership Can Drive Desirable Futures.”

• California Management Review: Leadership to Elevate Design At Scale: Balancing Conflicting Imperatives

• Foreword for book “Futures By Design” by Corà-Fazio-Collura (2023).

  
  

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Takeaways:

Collaboration is essential for effective design leadership.

Design should be viewed as a strategic capability, not just a tactical function.

Engaging stakeholders is crucial for demonstrating design’s value.

Establishing a governance framework for design is necessary for success.

Measuring design impact requires a focus on progress rather than just financial KPIs.

Creating a design center can significantly enhance design’s role in an organization.

Navigating organizational politics is a key skill for design leaders.

Intuition and creativity play vital roles in design leadership.

Aspiring design leaders should focus on building influence and resilience.

Understanding the business language is important for design leaders.

In this episode, Ivo Boniolo shares his journey from academia to entrepreneurship, focusing on the evolution of AI and its potential impact on various industries. He discusses the importance of innovation management, the challenges of technology transfer, and the need for businesses to adapt to the rapidly changing technological landscape. Ivo emphasizes the democratization of AI technology, the significance of human-AI collaboration, and the critical role of critical thinking for future generations.

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Ivo’s Linkedin: https://it.linkedin.com/in/ivo-boniolo-4884979

Watch on Youtube

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Takeaways

AI’s computational power has grown exponentially in recent years.

The potential of AI is vast, especially in automating processes.

Innovation models must be tailored to specific industrial clusters.

AI can enhance manufacturing processes and make businesses more resilient.

The integration of AI into business operations is crucial for efficiency.

Democratization of AI technology allows more people to start businesses.

Managing human and AI collaboration is essential for future success.

There are significant challenges in AI development, including cybersecurity.

Europe faces competition from the US and Asia in AI technology.

Critical thinking is vital for the next generation in a digital world.

Chapters
00:00 Introduction to Keith Teare and His Journey
01:21 Curiosity and the Creator Economy
02:55 Building with AI: Personal Projects and Innovations
05:57 The Evolution of AI Tools and Their Impact
07:06 The Future of Venture Capital and AI
09:17 SignalRank: Scoring Human Judgment in Investments
10:21 The Genesis of SignalRank and Its Mission
13:00 Performance Metrics and Future Plans for SignalRank
15:15 The Shift in Venture Capital Dynamics
16:34 The Role of AI in the Future of Browsers
19:02 The Business Model of the Internet and Its Future
22:13 The Future of Advertising in AI
25:20 Chinese LLMs and Their Impact on the Market
28:51 Opportunities in AI and the Future of Links
30:01 The Value of AI Tools
30:18 Understanding AI’s Role in Business Transformation
31:42 AI’s Impact on Productivity and Cost Savings
33:35 Navigating AI Adoption Challenges
36:38 The Concentration of Capital in AI
39:44 The Future of AI and Global Economic Growth
41:02 AI as a Tool for Empowerment
44:07 AI and Global Cooperation vs. Competition
45:52 The Dual Nature of Globalization and Technology
50:52 The Human End Game in AI Development
56:00 The Challenge of Venture Capital Perception
58:30 Confidence and Cultural Perspectives
01:02:06 AI’s Role in Education and Learning
01:07:44 The Future of Work and Universal Wealth
01:11:14 AI in Governance and Decision Making
01:14:49 Reflections on Tech and Personal Growth

Previous episode with Keith (recorded in Nov 2023)

Customer experience isn’t just about making things look good on the front end. It’s about understanding that physical and digital is the company: the organization, the processes, the way people work together, relate to one another or interact with each other or with your product, service or space.

And if you want to design experiences that truly matter, you need to get your hands dirty with the unglamorous work that happens behind the scenes.

So, we’ve been there. You design a clear, intuitive interface. You test it. It works. But then it goes live, and suddenly, things break.

Not because the design was ‘wrong’_there is no such thing as wrong design. But because the systems behind it weren’t ready. The backend doesn’t talk to the right people. A field doesn’t trigger the right workflow. Data doesn’t land where it should.

And the customer is stuck. Repeating information. Waiting. Dropping off.

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This is what happens when design stops at the surface.

Too many teams still treat design like a final layer. Something that makes things “look good.” But if you’re serious about customer experience, that’s not enough.

And if you want to design experiences that actually work, you need to understand the whole system behind them.

You don’t need to become an engineer or a business person. You do need to know how things move inside the organisation:

• What triggers what

• Who is responsible for what

• Where the friction happens

• What slows things down

• What makes customers/employees/patients/visitors/you name it, tick.

This is where design becomes strategy

It’s about asking different questions from the start… and keep asking:

• What happens next?

• Who else is involved in this step?

• Where can this break?

• What’s going to slow this down?

Because if your design can’t survive the real-life processes behind it, then it’s not going to deliver the experience you intended.

This is why collaboration matters. Design, legal, tech, compliance, ops—everyone needs to be in the same room. Otherwise, the experience is built on assumptions.

And assumptions are what break things.

Written here.

AI is not new. GenAI isn’t… that new either given all the noise it’s still doing.

But the way we work with it is what’s changing everything.

Small parenthesis: the term “artificial intelligence” was first coined in a workshop proposal titled “A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence”. July and August 1956 *when the workshop took place), is considered the official birthdate of the field of AI in its infancy.

We’ve reached a point where AI isn’t sitting in the background of our workflows. It’s becoming a thinking partner. Not another digital assistant to automate tasks, but something that ‘mirrors’ how we think, decide, and create. Even if it’s still very different. It learns differently for instance, but it gives us the illusion that it thinks like us, because the way we communicate with it resembles how we communicate with humans, not software. Not CMD+RETURN+START AGAIN.

That’s the part most organizations miss. Everyone’s talking about best practices, use cases, tools, or productivity boosts. But very few are talking about the way of thinking that links it all together.

That’s where I spend most of my time: unpacking not the “how” of AI, not the “what”.
Because the real business value of GenAI is not in prompts, technology or platforms.
It’s in how people think when they use it. Before the use it, while they are using it and after.

When they shift from control to curiosity. From reaction to reflection. From asking “What can this tool do?” to “What can we do differently with it?”

I see lots of synergies with creativity and design here, with being ok with the unknown and discomfort.

That’s where transformation actually starts. That’s where leadership kicks in.

Everyone’s asking for GenAI tools.

What they’re really asking for is: maturity, mindset, and creativity.

These are the foundations of value creation.

They may not say it like that though. But it’s there, in every conversation. It’s harder to justify as it’s not tangible, measurable results. Because it’s human results.

• “We want to integrate AI across teams.”

• “We’re looking for AI use cases that actually stick.”

• “We’ve invested in licenses but not using them and haven’t told you clients just yet”

It sounds like a tooling problem. But it’s a thinking problem.

What they’re really saying is:

We don’t know how to shift our way of working.
We’re unsure how to build confidence and capability.
We need help making AI meaningful, not just available.

That’s where mindset comes in. That’s where creative and strategic thinking become core skills, not just “nice to have.” You gain nothing by giving or having access to GenAI. You get a lot when you have clarity, curiosity, context… and courage. Yes, courage. To make the leap and experiment.

GenAI (literally, like creative thinking) rewards people who know how to explore, reflect, reframe, and do it consistently. This is mindset. A way of thinking, doing, and operating.

Quick note here: that’s not about software. That’s about people. Only.

The real transformation is about behaviour. Not software.

Most GenAI conversations are still around platforms, agents, features. But ask someone how their teams are actually using it, day to day, and the room goes quiet.

Because real transformation comes from changing how people think and act. Not more access. Deloitte just deployed Anthropic to over 470k employees. (I should’ve kept my badge to sneak in and see how it’s being done.) But on a more serious note: I can’t see this being just a tech roll-out. Because that’s change management, behaviour design, and a cultural shift that needs time.

And that’s how it can manifest:

• When someone pauses before writing and thinks, “Can I do this with AI first?”

• When a team compares versions, reflects, and makes a better decision… together.

• When leaders model exploration instead of asking for polished, finalized outputs.

That’s the shift.

It doesn’t happen by accident. You need intention. You need the space to try, get it wrong, and try again. You need small rituals. You need play.

And that only happens when organisations stop focusing on tech and start focusing on people.

GenAI doesn’t plug into workflows. It plugs into habits.
No habit = no value.

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Capability ≠ Access.

Giving people access to AI doesn’t mean they’ll know what to do with it.
Just like giving someone a pipe wrenches doesn’t make them a plumber.

That’s what’s happening across organisations right now. Big or small.
Licenses are being bought but usage is low. This starts at the top. Because you know what, you can’t always expect people to spend their free time learning new stuff. Many do it, but many more don’t… and won’t. (not that I agree with it but it is the way it is, especially in companies where you know you kind of have a job for life).

Access is not capability. Capability is built. Through exposure, experimentation, and shared learning. Again, starting from the top, in small teams, by giving time, training and a safe space.

It’s the difference between checking a box and building a muscle.
And that muscle is creative, contextual, and strategic.

It’s knowing what questions to ask.
What “good” looks like. And knowing when to pause, stop or push.

Digital transformation did not happen in minutes. Or in a year. It’s an ongoing investment. From this point of view, this is not different.

You can’t copy-paste capability.
It has to be earned, through play, reflection, and feedback loops.

Teams need more than tools.
They need the mindset to work with AI… just like they need the mindset to work with humans (what we call collaboration and co-creation). And with humans + AI.

And that’s where most orgs are underinvesting… by far.

Maturity shows up in small behaviours. Mindset is the multiplier.

If there’s one thing GenAI reveals, it’s how ready your people actually are.

Strategically. Creatively. Not technically.
How they ask. How they think. How they decide.

Again, so much to take from creativity, design and entrepreneurship here.

I’ve seen teams with zero tech background do incredible things, because they stayed curious and had the space to test.

And I’ve seen others, fully trained, stall, because no one wanted to look “wrong” in front of each other. But maybe because they had the training I would not recommend: endless prompting hours.

We are talking about something that is being shaped as we speak, so training with this in mind makes a difference. Not to kill retraining but to set the tone right, and then deep dive, zoom in and out when it matters, if needed.

Let’s wrap up, maturity and mindset are not measured in dashboards or licences.

It’s in small things:

• Someone asks “What if we tried it this way?”

• A junior runs a version past AI to stretch their thinking.

• A leader shows their own rough prompt to start a dialogue.

That’s where GenAI starts to integrate as a co-thinker. That shift comes from mindset. From behaviour. From the culture you build inside-out.

If you’re still asking “How do we get value from GenAI?”
Maybe the better question is:

“How ready are we to change the way we think?”

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Elevate your employees’ skills (in🇬🇧🇮🇹):

Gen AI adoption starts with maturity and the right mindset. If you want to lead with creativity in the age of AI. Not just stack tools, our Human-AI Leadership education helps your team. Message me or check GGUTT.

Accenture to ‘exit’ staff that cannot be retrained for age of AI.

(Why can’t they be retrained is another conversation)

Accenture CEO Julie Sweet said:

“Gen AI seems so simple, right? And then the reality is it’s not the technology that is the biggest barrier, it is actually being able to get the mindset re-organized around how best to use it, the ability to do the change management, the process reinvention.”

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This is mindset change, maturity and behavior change as I have been saying for a while now.

This is change management. Not tools. Not tech.

This is adapting. This is re-skilling.

It impacts consultants, sure, but not only. Every person in every industry. In almost any job.

Microsoft AI CEO Mustafa Suleyman, believes that technological advancements over the next several years will change what most jobs look like across nearly every industry, and have a “hugely destabilizing” impact on the workforce.

The thing is, being hands-on with AI is the best way to learn and start thinking about it. From my experience, confidence and fear from even getting started is a big step to overcome. But being hands-on needs to be encountered with taking a step back to reflect, assess and understand.

Because hands-on implies tools, and tools come and go, many will remain, evolve, and many will die. Understanding, along with maturity, mindset, behavior and creativity is what will set the stage for AI Leadership and action.

Anthony Tan, co-founder and CEO of Grab hosted a company-wide AI sprint.
Grab is Southeast Asia’s leading superapp. It provides everyday services like deliveries, mobility, financial services, and more.

On Rapid Response Podcast, he acknowledged that “mindset change is tough” in a 9,000+ person company, and set a clear expectation: “every Grabber has to be a technologist.”

Things are not only moving fast, but changing fast.

Adapt now… or die (not literally).

What I mean is that transformation may feel slow, but it will hit home faster than we think, so better be prepared and ready, rather than play the catchup game.

On that note, The EU AI Act article 4 is a regulation that requires businesses to ensure their employees are AI literate. Non-compliance could lead to significant penalties.

Yes, companies have a huge responsibility, but individuals need to make the leap too, and not expect magic to happen with minimum effort. They need to get hands on, and start taking the matter in their own hand, one step at a time.

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In this episode, I share my journey into AI, emphasizing the importance of mindset, creativity, and human judgment in the adoption of AI. I highlight the transformative potential of generative AI while addressing the fears and misconceptions surrounding it, the collaborative approach to AI where human intuition and critical thinking play a crucial role in decision-making. I also explores the ethical implications of AI, the competitive landscape between the US and China, and the necessity of creating safe spaces for experimentation and learning within organizations.

Key Takeaways

• AI adoption is more about mindset than technical skills.

• Generative AI has transformed the way we interact with technology.

• Human judgment is essential in AI decision-making.

• Fear of new technology is a natural human response.

• Creating safe spaces fosters creativity and experimentation.

• Expectations around AI need to be managed carefully.

• Investing in AI tools does not guarantee their effective use.

• Collaboration between humans and AI is crucial for success.

• Ethics in AI is a significant concern for businesses.

• The competitive landscape of tech is constantly evolving, especially between the US and China.

Chapters

• 00:00 Introduction to AI and Creative Thinking

• 02:16 The Shift to Generative AI

• 05:35 Mindset and Maturity in AI Adoption

• 09:28 Human Judgment vs AI Confidence

• 12:18 Fear and Acceptance of New Technology

• 15:45 The Role of Humans in AI Decision Making

• 19:06 Ethics and Trust in AI

• 23:33 Creating Safe Spaces for AI Experimentation

• 25:58 China vs. US in AI Development

• 34:02 The Future of AI and Human Collaboration

When we talk about leadership, we usually talk about direction, delivery, performance.

But rarely do we talk about creativity.

It’s a patterns I’ve seen over and over, even though I don’t think we should “talk” about creativity, but do it, live it.

However, when we do talk about creativity, it’s usually about campaigns, design, branding, or ‘brainstorming’.

Creativity in leadership is not a nice-to-have nor a luxury. It’s a core capability.

The best leaders out there talk about it, or mention it a lot. Many live by it. Think Indra Nooyi, Daniel Lamarre, Marc Benieoff, and even the Big 4 and Harvard…

I’m not talking about talent - it has nothing to do with it.

I’m talking about a way of operating as John Cleese says. The way of thinking that kicks in when someone is open to something completely new and potentially unexpected…

What defines a great leader is how long they can stay in the question. Not how fast they answer. They don’t jump into the solution space as fast as they can.

Creativity not about how many slides can be presented either. But rather how they create space. For themselves and for others to think, explore, and figure things out.

I remember a time when I started noticing that the way I approached things was different. I asked more questions. I waited longer. I listened more than I talked. And I slept on what I grasped and allowed thoughts and interpretations to come in... and even interrupt me at times.

And for a while, I thought: what am I doing? Am I doing what I am supposed to do? Why do I think the way I do?

For a long time, I internalized it. But this way of operating started long before I had a job title. Even as a kid, I’d observe everything. Spend my time between the lines. Probably way too much.

It took time, but I realized that this was my mode. I just had to find a way to work with others, to help us align, without losing that way of thinking.

That shift, from trying to be right, to being open, is the real creative leap.

Curiosity comes first. Just before creativity. And during. It’s actually part of it. Curiosity is all about listening with your eyes, reading with the voice.

Creativity is about connecting the dots. (if have to stick to a few words)

It’s not just about asking a bunch of questions. It’s about staying with them. Questions like:

• “What if it’s not this?”

• “What are we not seeing?”

• “Why does this exist at all?”

Curiosity is what stops us from repeating the same answers with a new look. Curiosity is the seed. Creativity is what helps us grow it.

Both are innate. But both need development. And space.

Now here’s the reality of most workplaces: someone sends you an email at 2pm.

“Urgent brainstorm at 3pm. Can you join?”

No brief. No context. Just the word “creative.”

You show up. Five minutes in: “How about this? What about that?”

And you think… why am I even here?

I call it death by design. The room wasn’t designed for thinking. It was designed for performance. And for feeling good about contributing something… to anything.

And I experienced such a thing, the person calling for the ‘brainstorm’ just wanted to feel good. Nothing more. Nothing less. A pointless exercise and time wasted for everyone.

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Ideas get thrown out before anyone’s even taken a moment to define the problem.

That’s not creativity. That’s choreography.

That’s not leadership. That’s direction without listening.

And then… someone dares to ask a better question. Everything freezes. Because real questions bring real uncertainty. And for many, that’s the nightmare.

But that’s where creativity lives.

In the not knowing. In the discomfort.

I will end it here. Hope you will tinker on this.

To be continued for sure.

I want to get back to that. It was meant to be a clarification but my fingers kept on typing. Initially I didn’t plan to have this parenthesis on China / USA expanded. But a comment sent to me on the word ‘safety’ got me thinking.

First things first, I would like you to read this with an open mind.

It’s not about right or wrong, good or bad. It’s about taking a step back. Looking at technology, adoption, integration and human judgement. Outside of finger pointing, threats and fear.

It is about being positive, and merging mindsets. To build something good for humanity, or good at a smaller, personal scale, beyond politics.

In this post, I am leaving Europe behind. It's not prominent in the AI space. Yes, there is Mistral, and some other startups. But on an infrastructure level and mindset level, it's still behind. Besides being the first to regulate and try to control. There is no tolerance or acceptance for risk. Which is bad from an innovation standpoint. But that's not the point. Europe follows the USA... until it gives sanctions, then keeps going.

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Anyway.

I have been reconsidering the word ‘safety’ from my previous post. Safety when mentioning Chinese or American AI. I am not sure it is the right word for it. The word "trust" fits better.

• Here are some questions:

• Everyone (in the west) fears China. Is China a threat?

• Is it still and always copying and stealing innovation?

• Why is it a belief that China is bad, because it’s China?

• Why is it a gut reaction to be scared of Chinese technology?

• How is our rational personal experience pointing to the fact that China is actually bad?

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A bit of context.

Many of the conversations I’ve had (during sessions and general conversations) occur with rejection and fear, intrigue and confusion whenever mentioning any Chinsese LLM. Sometimes, the facial expression says it all. These conversations tend to continue with a comment on democracy and dictatorship.

I have no issue with debate, as long as there are strong facts, arguments or at least some sort of common sense.

I don’t speak mandarin or any other Chinese dialect to understand what is going on there in the AI space over there. I rely on what is on hand in the languages I understand, from sources of information we can access.

I have nothing for or against China or not China. In particular Chinese LLMs and technology. I am only looking at people’s behaviors, beliefs, culture and critical thinking capabilities.

In a recent communication, Jensen Huang, the CEO of Nvidia said that 50% of AI Researchers Are Chinese. He insisted on the importance of understanding competitive advantages in the AI race. Let’s look no further than the top AI hires (ripped off) from Apple, OpenAI and ScaleAI. Imagine how many top notch AI researchers there are in China.

We know from a socio-economic-political standpoint the USA wants to stop China. Why?

I am not going into geopolitics here. But here is a small parenthesis, and I don’t know if this was by design or a consequence.

It is fundamental to remember that China owns significant natural resource wealth, from rare earths and other minerals. You can’t build technology without that. They control the vast majority, way beyond USA. This means that implementing the trending tariffs that Trump boasted about would have been a massive blow to the US. But it doesn’t start or end here.

China has an advantage over the US in the cloud space which is about behavioral modification. Think TikTok, Alibaba, etc… bringing in creators, builders, viewers, businesses, where everyone congregates for different reasons. The algorithms are often... unique. And impact behavior. China is becoming a big competitor to the USA in terms of cloud capital (words of Yianni Varoufakis) which is giving max power to whoever owns it. Chinese banks and Chinese Big Tech work together, they are one in a way: you pay with WeChat and don’t give a cut to anyone whereas in the west, you do. It’s different systems and beliefs. This makes such a difference at scale. Just look at wars. General opinions are based on beliefs, not facts. Check my short episode on this (apple,spotify, youtube from the Abrahamic Family in Abu Dhabi).

Here's a parenthesis, because many will be thinking and saying: but wait a second, all these fashion brands (forget iPhones and co) are manufacturing in China. China is copying… what about human rights? This is beyond the scope of this post. If they learned from other countries, if they got inspired and progressed, congratulations for contributing to this.

The other question is, how can any AI, not matter its origin be safe anyway?

Generative AI cannot be controlled. Not my words, Mark Cuban’s words. I am not going to get into the EU AI act, as it is not my area of focus. However, between the regulation, the progress and the implementation or enforcement, I am not sure how we can ‘protect’ citizens. I am not sure either about how we can contextualize every single scenario and make decisions. Leaving this to people focused on AI ethics, policies and responsibility.

What is China doing?

If I want to take a step back and look at some of the experiments and advancements, one of the things that made me dither is the world’s first AI-powered hospital initiative, developed by researchers at Tsinghua University with a Large Language Model at its core, trained on medical literature, patient interaction and diagnostics protocols (14 AI doctors and 4 AI nurses who are capable of managing up to 3,000 patient interactions per day). It seems that the focus in China is on China, to focus on improving people’s lives by experimenting with new systems and exploring new ideas, ahead of time. In healthcare, the worst nightmare at the moment in the west. China is piloting such a project in Saudi Arabia too.

Meanwhile in Europe, the co-founder and CEO of Spotify invests in AI-powered weapons... to make more wars... and money (don't tell me defense or convince me of anything else)

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Let’s think this through too, before the hype around AI.

Is Meta (Instagram, Facebook, Whatsapp, Llama...) more trustworthy than Tiktok?

If so, why?

I am not understanding the fear and lack of rationalism. I have never been to China anyway.

The way I think is to think the opposite of what we are told. I keep an open mind and I don't jump into conclusions stating that we should trust X not Y, based on sexy statements about good and evil.

I question everything (part of my creative brain). One way of doing this is asking WHY. More than once.

Just like we do with LLMs. Do we trust blindly or do we use our own judgement? Gen AI is not the curator. We are.

My point from this parenthesis in the wider post is to focus on critical thinking skills, and not take anything we hear or are told for an answer. If in doubt, ask yourself: Why. 5 times.

The question is. Who do we trust?

The minute we became online, we have been giving away our data. directly or indirectly. Every single second.

I will leave you with this. In an ideal world, technology should be about co-creation and collaboration to serve humanity, not about dominance. Investments in tech is here to compete, overtake and overthrow. This is the world we live in. Let’s be realistic.

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Thank you for reading this! I read and reply to all comments and emails. So feel free to share your experience and thoughts.

—

Elevate your employees' skills (in🇬🇧🇮🇹):

If you want to lead with creativity in the age of AI. Not just stack tools, our Human-AI Leadership experience helps reprogram mindset at scale. Message me or check GGUTT.

In case you missed the post that led to this one:

Let's get going.

AI is not new but let's not go into this. Generative AI is... life-changing. Any new technology exacerbates fear. Anything new is welcomed with fear.. by our brain. It's a human thing.

Don’t let the fear of any new wave of technology reject it. Electricity gave us access to many unthinkable things. So did the internet and smartphones. AI is the same. A new revolution.

But here's the thing. Generative AI is not magic. It can feel like it upon discovery. This is why we must draw the line between what makes sense, and what doesn’t. No matter what the type of content we work with.

People have weird expectations.

Expectations with AI can be weird, high and delusional. Expectation of miracles with little understanding of how to interact with it happens. Because changing the perception around AI and changing behavior doesn't happen overnight.

But with practice and will, it can. I like to compare this to creative thinking. The difference is that creativity is innate and developed, or 'wiped out' in time. It all starts with the mindset.

Hearing people say ‘we tried AI and it did not give us good results’ or 'it did not work for us' is too vague and makes you question what they tried and how.

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Fluff is in the DNA.

With no context, direction and proper instructions given, LLMS (and multimodal tools) will invent context. Great for ideation, bad for nuanced 'answers'. What we call hallucation, (even though all AI does is hallucinate) is okay. But not for people with little or no experience, no clear expectations and goals. This can be a dangerous game to play. It can be detrimental not only for a single individual, but for a team and an entire organization. This is why we need to keep developing creative and critical thinking capabilities. It's not a one off exercise. It's the only way to boost judgement, look at nuances and curate.

You are the decider.

Humans are the sole decision-makers. Not AI. This is why thinking matters. You cannot and should not rely on AI to decide for you.

Let’s pause a second.

Can you hold it accountable for the outcome of that decision? Think twice. For now, you are the master. You control. You put in your ask. You instruct. You set the goals and expectations. You help refine. You provide feedback. You can ask AI to help you, but not to decide for you. Humans need to stay humans. This means think.

You've screamed at the washing machine!

It does feel natural to assume that AI should think first. Even if it comes across that way because of natural language. But there's a but. Talking to machines? It’s been happening. Remember the last time you screamed at your radio in your bedroom, or at your car that wouldn't switch on? Humans can talk… to anyone. To animals and to machines.

AI does not behave like software. Software as we know it is: command > response or command > flow > response. With AI, it is iterative. Not sure how it will evolve the more AI gets to know us. And when new ways of communication will be released. At the moment, the user experience still feels clunky. We are at the very beginning. But for now, it is about conversation. Or description in multimodal text to image/video/audio generation. With agents, it’s about goals. Le’ts not fall in the trap of automation only, and delegation. There is more to it, like orchestration and harmonious integration where there is a fusion of humans and AI.

Will it get more intelligent... (than us)?

More intelligent than some of us? Definitely (according to yours truly, so take it with a pinch of salt, and potentially to most of us). Will it surpass human intelligence? According to Jeffrey Hinton known as the Godfather of AI (Nobel Prize in Physics, ex Google Brain...), these things will be smarter than us. They will have the ability to reason. It's machine intelligence over biological intelligence. It will happen unless we do something about it. That's his fear.

Let's take note of the word "superintelligence", which is the next buzzword after AGI (artificial general intelligence). Which means that it will be better than us at most things. This could have drastic existential consequences.

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Is it okay to be scared?

Ethics around AI is a key consideration for any business leveraging AI. Beyond bias (here again, who is feeding the data, and which data). It is not only about what you feed into the systems, data privacy and security. It's also about which systems you use, trust, and the whole governance. Starting with AI can and should be messy early on to explore, experiment and learn.

Before it scales in an organization, it is fundamental to look into companies you will work with, from trust, to data protection, to support. Do your own due diligence and if you are using data, control the quality if you can, or test it.

Make sure you don't fall into the nitty gritty details and stay behind with experimentation. This is why adoption is not the same as experimentation. Because the latter is the only way to learn, while ensuring transparency and proactivity. Ignoring AI ethics can have serious consequences.

Safe space

Giving a respectful learning environment to experiment and learn, without fear of judgement or critics is what will allow creativity to flourish. Open conversations will happen, and new ideas to explore will emerge.

You will then decide how to move forward as individuals, teams and an organization as a whole. Safe spaces should exist in every company, and not only for AI.

A one off activity is not a thing.

Maintenance of people, systems and processes should take place. No matter the size of the organization. We cannot educate employees 1000 employees and then a year later decide that we have to start again. Education should happen with a safe space to experiment, learn and grow.

I've heard so many times (beyond AI by the way): "we have training sessions, we sit, listen and what gets past the ear gets out of it as soon as we leave the room".

There are three options for this to happen:

• You trained them on tooling only, and ignored mindset.

• You ticked the box of training and did not give them space to apply.

• You focused on the wrong thing, because there is lack of empathy and understanding.

This happens. People in charge of deciding what a teams need often don't have a clear picture and end up making assumptions. In all 3 scenarios, it's a waste of time and money for everyone. People being up to speed is like software maintenance. New updates require maintenance. With humans, it's beyond updates. It starts with mindset and maturity.

Investing doesn't mean using.

Investing in tools and access to systems does not guarantee adoption. In this case, there is no guarantee that AI will be used in an intelligent way. First, there is individual work to be done, before it can scale to the organization. And the more leadership can share the ups and downs of their own exploration, the more the top-down approach will work (i like to call it visibility in). This is part of the culture. Because you don't tell the power of AI to people. You show it. This is what makes the difference between temporary engagement and culture.

How to start.

With play. Fun. One of the things I do is I get people to create art with AI. It gets people engaged. And we stir the conversation into something more meaningful and start with a laugh. If you want to start on your own, play. Try things, even if they don't make sense. You will make sense of them later.

Thank you for reading the hole thing. See you next time.

I’d appreciate you sharing this with friends or colleagues. I am trying to grow my newsletter. More subscribers would mean you want more posts.

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Elevate your employees' skills (in🇬🇧🇮🇹):

Gen AI adoption starts with maturity and the right mindset. If you want to lead with creativity in the age of AI. Not just stack tools, our Human-AI Leadership education helps reprogram mindset at scale. Message me or check GGUTT.

I’ve released a ChatGPT < 30min crash course last week. I also added a section afterwards to cover the latest ChatGPT update - agent mode. Basically this course is about all you need to know to make the most out of ChatGPT beyond search and summarization.

It’s not a demo. I tried to package it in the way I do things and look at things, but less interactive obviously as it’s pre-recorded.

If you already use ChatGPT, this might give you some additional ideas or knowledge.

You will find an 18min long video overview with a quick intro, a story and key functionalities. I tried to keep the video short and focussed. Start with the video. Then look at the screenshots and accompanying tips and observations. Don’t skip any.

Why am I doing this? I don’t run standalone ChatGPT sessions. My goal is for this to answer most of the frequently asked questions I’ve been asked.

For those who believe AI is not for them. Or if they don’t need more technology in their life… they will be left behind. It’s like deciding not to use the internet! This technology is available to anyone with internet access. And it’s not going anywhere.

I urge anyone who hasn’t played with AI enough to get started. And think & do beyond the obvious.

Enjoy! If you find it helpful, give me a like or a leave comment. It would be great feedback!

Sharing with friends / colleagues would be awesome! 🤩

—

I recorded this on July 16th. On July 17th, OpenAI announced the introduction of ChatGPT agent; it will do work for you using your computer. More here. And an update below.

Jargon

• LLM = Large Language Model

• Prompt = the request sent to the LLM

• GPT= Generative Pre-training Transformers

The acronym GPT is no exclusively for chatGPT. It’s also a technical word. (for us users, it doesn’t change anything and it doesn’t matter). GPTs are popular in ChatGPT, that are design to be used as assistants.

• Prompt engineering (design) = designing prompts.

Context Engineering = preparing and providing necessary background information to large language models in a dynamic way.

*Keep in mind what you read under the prompt box: “ChatGPT can make mistakes. Check important info. See Cookie Preferences.”

For me, prompt engineering and context engineering are buzzwords that basically mean clear communication.

• Hallucination = incorrect or misleading results that AI models generate.

• Token = the smallest pieces of text, words or parts of words, that the models work with.

• Agent = an agent interacts with its environment to perform self-determined tasks for a given goal. (Agent ≠ Assistant - don’t get confused)

Deep Search (discussed in the video) is an agent integrated into ChatGPT. ChatGPT Operator (comes with Pro at USD200/month) is an agent. Here you can find many agents by category, outside of ChatGPT.

• Context window = the amount of text, measured in tokens, that the model can grasp at once when generating a response.

• Generative AI = artificial intelligence systems capable of creating new content, such as text, images, audio, and video, in response to natural language.

  

• Memory in chatGPT = works in two ways: saved memories and chat history. But the bottom line is, with memory enabled, it remembers your preferences. It stores certain information about you that may be important and relevant for future conversations. More here on reference chat history and reference memory.

• Model = Neural network that has been trained on massive amounts of text data, essentially complex algorithms that have learned statistical patterns from massive datasets of text. After training, these models can generate new data points that are similar to the original data. More on ChatGPT models but the one selected by default is what you will probably use most.

Key Functionalities.

This is where you can edit or modify your prompts within the interface after submission, by making changes to the text.

I personally don’t use ChatGPT for image generation, I find other tools better for what I need for now, however, I do every now and then for ideation.

Note: ‘Search’ is search. It’s not Deep Search (or ‘Research’).

There will probably be more… this is what you have to date.

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I personally don’t use these features a lot, i tend to dictate the changes I want to make.

It is not necessary to add a knowledge base when creating your GPT, unless you need it to start with your documents before going on the internet. It depends on what you are trying to do. Always TEST TEST TEST.

I like to have my instructions in sections with a title for each, to keep it organized.

Projects are in the paid version. Use them beyond basic folders and move conversations over. You can do this in 2 ways:

In the conversations panel on the left (sidebar), hover over the conversation, click on the 3 dots, click on ‘add to projects’ then select the project you want to add your conversation to.

Alternatively, you can be inside a conversation, click on the 3 dots on the top right next to the share button, and follow the same flow.

A few verbs:

A few to get started, but the sky is the limit. Remember, when prompting, give it a role ‘act as' or ‘you are’…

Things you need to know about LLMs:

• They have no self-awareness.

• They have so much knowledge.

• They don't replace your judgement.

• They have NO emotional intelligence.

• They have no world experience, at all.

• They rely on patterns and instructions.

• They have no common sense or real world.

• They don't know you, your emotions and thoughts.

• Their understanding of humor and sarcasm is limited.

• They hallucinate and may not remember everything you said.

• They can tell you anything, right or wrong with unseen confidence.

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Additional tips when prompting or talking to AI as I like to say:

• Give examples.

• "Great point about X"

• "Show your reasoning"

• "My 'life' depends on X"

• Ask follow-up questions

• A LLM won’t read your mind

• "Walk me through your approach"

• "That's not so great, let's change number 3"

• "Ask me clarifying questions before you start"

• "Take a deep breath and work on this problem step by step. (Explain each step clearly)"

• Remember, I am human and I can't process information as you do. Give me only what matters.

• "I'm going to ask several follow-up questions as we go, so please keep helping me refine this".

• Check my latest posts (and here) and podcast episodes. There are more. And more to come.

Some of the words of my banlist (i.e. words it uses A LOT):

• Poised

• Notably

• Embark

• Unlock

• Poised

• Unlock

• Embark

• Vibrant

• Bustling

• Depicted

• Weighing

• Demystify

• Grappling

• Harnessing

• Entanglement

• Game changing

• Unprecedented

• Insurmountable

• Unveiling the power

ChatGPT Agent mode

The latest update that I finally got my hands on. It combines ChatGPT Operator, Deep Research and ‘regular’ ChatGPT. Agents do things for you.

Here our behavior and mindset change... big time.

It books, orders, catches up, researches, analyzes, compares, audits, buys, creates, builds, retrieves, develops…

Basically it starts a virtual computer that it can launch a browser on. We can see the preview in real time. And we can review what it’s done or take over to insert login info for example.

I don’t plan to give ChatGPT access to my card details to acquire anything at the point in time but seeing it in action reminded me of the AI Agent test I did with Claude earlier this year.

I tested it to book a glamping holiday with constraints I have given it and to make a presentation (I don’t see why we need this agent when I could do that without the agent, and it is still meh in my opinion).

It’s incredible to see it in action: how a machine is doing what a human would have done… faster. They can think, research, reason. They click things, fill out boxes. They get over roadblocks and cookies, cloudflare verification, finding other ways to get to where they need to get to and even check the calendar availabilities on each site.

The agent asked me if I wanted to take over to insert payment details from the chatGPT window itself. Definitely exciting… it’s what I bought Rabbit R1 for (that I used for once for half an hour only and yes I was an early adopter and ordered it upon its presentation at CES in January 2024). Not giving it my login info either… just yet, but soon for sure.

On the security front, the last step before proceeding to payment, when you are asked to take over and just before you can insert your credit card information, it says loud and clear, “this may put your data at risk” makes you wonder. How? It’s a virtual broswer, not your computer but anyway… so for now, I am nervous.

Will I use the agent mode? To research or analyze for example, I am not sure at this point. It seems in some instances, and based on my 3 hour long testing, like a glorified version of ChatGPT. But I will keep exploring as it will certainly evolve over time.

Also, depending on the prompt (the more specific the better) it can take 40 minutes to perform a research to get to the booking page, when ‘regular’ ChatGPT can take a minute or less to the research and present it in a table without you asking for it.

So, let’s recap; you can give it access to pretty much anything, your calendar for example and ask it to perform a specific task like observations based on your activities in a structured way.

Elevate your employees' skills (in 🇬🇧🇮🇹🇫🇷):

Gen AI adoption starts with maturity and the right mindset. If you want to lead with creativity in the age of AI. Not just stack tools, our Human-AI Leadership education helps reprogram mindset at scale. Message me or check GGUTT.

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Thanks for watching/reading! If you learned something new or if it made you think, sharing it with friends / colleagues who could benefit from this would be awesome! 🤩

By fostering curiosity, context, and creativity, leaders can leverage AI to enhance organizational culture and drive tangible results. Watch it on youtube.

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I have been intrigued by “traditional” AI (meaning not Gen AI) since 2017 or so, as I was working with lots of startups outside of my corporate job, where tons of ideas were on the table all the time. But obviously, I was limited with what I could do, I could only read about it and get into conversations on data, ML, analytics. I then started reading more and took a couple of online courses. But the shift happened when Dalle came about, i got to play with it a bit then went on mute until ChatGPT came in November 2022. That’s where everything changed for me. It became my focus day in day out, learning, experimenting, reading and constantly discovering, with others, and alone.

I am writing this newsletter, longer than the usual one, and might turn it into a podcast episode too.

Today I want to try and help anyone already working with AI or interested in starting, by sharing my findings in helping others work with AI. We help teams build the creativity, maturity, and mindset needed to make AI a lasting part of their day-to-day. And this requires change, transformation and intuition.

Now let’s dive in.

First things first.

Let’s set the expectation straight.

You don’t need a Phd or background in computer science or tech to use AI or to work with it. I am the perfect example. Background in design. 100%, from service, product and going back in time to my days in interior architecture. More on this here (youtube) or here (spotify) or here (substack).

If you can communicate, then you can probably help others discover and get excited about AI, they can then take it to the next level.

We have all used AI whether we realised it or not. We have shared our data whether we like it or not. The moment we got a mobile phone and Google Maps (not to mention platform logins, emails, socials, ecomms…) AI was has been with us in the background. We, humans also became data.

Every person, team or organization has to find their own way of using AI. There isn’t one workflow, one way, or a right way. There are basics, but there is appropriation… adaptation. Electricity allowed humans to extend the ‘daylight’ but did not dictate to work longer or party more. Gen AI allows us to do more independently or with other brains. More of so many things.

But here’s the thing. Time. Training. Experimentation.

These are not buzzwords, but what is essential to increase adoption. To drive maturity and change the mindset and behavior.

Training is essential. You can definitely learn about AI by yourself, but nothing beats learning with people, inside and outside your company. Not everyone’s got the time, appetite and capabiltiy to learn outside office hours. To many, a job is a job and they have other responsibilities after. A safe environment to allow employees to learn, and test and giving them a safe space to experiment to figure out what works for them is fundamental.

No one can know all the tools. And AI is not about tools first and foremost. It starts with the tools to break the ice, but it doesn’t end there. This is about maturity, creativity and mindset. Also intuition. AI adoption starts with exploration, experimentation, sharing and reporting. Just like creativity. It’s a way of doing, thinking… and being.

Fear is human. Anything new in general is met with fear (by default) and questions by our brain. AI adoption requires way more than AI training.

One thing that I find super valuable is untriggered, spontaneous conversations, even off topic (directly) that lead the way to dive into scenarios and potential use cases.

When someone is in doubt and gets seriously curious, you are off to a win.

People have their reservations on anything new. This is human nature. This is why people train on uncertainty, be it AI or not. Creativity is uncertain. Walking for toddlers is uncertain. Sometimes a little push, a small ‘creation’ or win will unlock curiosity, you will see it in their eyes, the AHA moment will happen. which can be all it takes to gage someone’s interest to go further.

As long as conversations occur, along with cross-company contamination and inspiration, executive level people tend to focus on the unimaginable future and forget to focus on the immediate availability. AI is evolving, but we cannot let our ideas evolve without getting our hands dirty in workflow discovery, experimentation and integration seriously.

Buying AI licences and making it available to everyone in an organisation is not what adoption is about.

Most people don’t even know what to do with these licences. Yes, it happens more than we think - the typical top-down approach with 0 or very little onboarding - or a focus on tooling, when tools evolve faster than usual software updates - not comparable.

I’ve never met anyone as confident as a LLM. It knows it all, spits it out, whether it’s right or wrong. Whether it makes sense or not. But it makes you feel you hit the jackpot.

AI gives tells you anything you want it to hear with confidence. Then can tell you the exact opposite with the same level of confidence. Nothing beats human judgement. Nothing beats your experience. AI has no context and follows your ask… and is sometimes guided by your nuanced communication, sensing you have a slight preference. Now the new buzzword is context engineering, but come on (that’s for another time.)

On China vs USA

Is American AI safer than Chinese AI? Is Chinese AI safer than American AI? Not sure how to ask the question. I am not mentioning any other geographies for the simple reason is that most companies that are making noise are primarily from USA, and China.

Here’s how I look at it. Is Instagram safer than Tiktok? Free usage is control. Even if you pay for your AI, terms and conditions change. What about countries? To me at least, it doesn’t matter. None is safer than we think, but following this logic, we might al live off the grid. Unless you want to spend your time reading terms and conditions.

Let’s be safe rather than sorry and filter sensitive data. Let’s use our human judgement in how we use AI. My sensitive data might not be your sensitive data.

Working together. Interacting together. Being together.

It’s about looking at how people work in teams and individually over looking at technology. Because this technology is about behaviour change. Not just integration. And certainly not just about tools. It is and was never about tools. It’s about rewiring the way we think and do. How we collaborate, lead, participate and offload work and tasks. And about critical thinking, judgement and curation. However you want to call it. I would add your gut too, as mentioned earlier. Which comes from your experience.

Coming up next:

• Gen AI is not Magic

• How to start

• Making decisions

& more… (incl. more podcasts)

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There’s a shift happening.

Quietly, then suddenly.

AI is no longer just a tool sitting on the side of your desk.
It’s becoming part of the team. A creative partner. Beyond a core skill.

Shopify and Duolingo recently said it out loud:
If you want to hire new people, you’ll need to prove AI can’t do the job first.

I see teams wasting weeks deciding if AI fits their workflow.
But the real question is: Why haven’t you made it standard yet?
There are questions, there are fears, and trust concerns, inside-out. Meaning inside the company and beyond, with customers for instance…

AI doesn’t replace people who know their stuff. Who add value.
It reveals where you’re spending energy on the wrong things.

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Here’s the key: AI can assist, but it doesn’t lead.
Humans curate. Humans decide. Humans design the experience.
AI can generate. But it’s your judgment, your questions, your edits that shape the result.

I’ve seen this play out in creative work, writing brand stories, designing workshops, facilitating strategy sessions.
We drop rough drafts into AI, not to get answers, but to get provoked.
To go beyond what’s obvious.
To sharpen what matters.

The magic isn’t the tool. The magic is how we use it. With purpose and precision.

This is the moment we stop asking, “Should we use AI?”
And start asking, “How do we embed this into how we think, decide, and build?”

Using AI doesn’t mean is AI in charge.
It means people-first, with AI as a capable assistant.

What would change in your team if AI wasn’t optional… but expected?

—

If you’re new here… lsay hello~

Stay Creative 🩵
M.

CEOs of key players in AI say one thing to the public and another behind the scenes. Should we be scared? I also heard Gary Vee who believes that humans will have AI girlfriends and boyfriends in 2 generations.

So here’s the thing. I read an article that got me thinking.

We talk about innovation, AI, and the future of work all the time.
But what about the future of not working?

What happens when the meetings stop, the kids move on, and the phone stays quiet?

The loneliness that hits in later life isn’t just emotional. It’s systemic.
Social circles shrink. Health gets complicated. The world moves fast.
And connection gets harder.

This is a human issue, not a tech one.
But increasingly, AI is stepping into the space where friends, community, and care used to be.

AI chatbots are now being used to fill the silence.

Not to solve loneliness, but to take the edge off.
Is that good design?
Is it ethical?
Is it enough?

We’re entering a moment where designers, leaders, and organizations need to ask harder questions about what support really means. Especially for aging populations.

Tech can be a tool. But it can’t be the touch.

Let’s not confuse presence with presence.

Here's a recent article worth reading:
Can Chatbots Solve the Loneliness Epidemic Among Older Adults? (Fortune)
It raises important questions, and avoids easy answers.

I’d love to know what you thought of this newsletter and any feedback you have for me. Feel free to hit reply.

Stay Creative,
Maria 🩵

Links

• Speaking > here

• Let’s work together: AI Maturity, Creative Thinking > here
  

• Podcast > here

• Access the Vault > here
  
  
  

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• Newsletter: mariamatloub.com
  

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00:00 Introduction to AI for Small Businesses

03:03 Mindset Shifts for AI Adoption

07:05 Practical Applications of AI in Business

10:00 Overcoming Challenges in AI Implementation