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Adam Rek has spent over a decade building his career in industries where trust is the ultimate currency. Now Head of Marketing at FLO, he’s approaching marketing with that same focus on brand trust, precision and authenticity. His is a philosophy that’s particularly important in the AI-driven world of today, where speed is coming at the risk of brand context and meaning.
For Adam, the real breakthrough hasn’t just been in generating content faster, but instead in how AI has reshaped the thinking behind the marketing. Over the years, Adam’s career has always centred around expressing ideas and building messages people can believe in. It’s this background that shapes how he looks at AI, a tool that, when used properly, can look like “borderline magic”.
Even though AI has the potential to be used in a meaningful way, Adam is very aware of the risks. With AI becoming more prominent across social media, it can be hard to distinguish earnest effort to incorporate AI into marketing from what are simply slop content farms. As Adam sees it: “The internet’s already overflowing with AI-generated gibberish, and it’s only going to get worse.”
In Adam’s view, authenticity isn’t about resisting AI necessarily, but about knowing how to use it with intent. “AI won’t take our authenticity,” he explains, “if we understand why we’re doing something, AI simply helps us do it better and faster. And that counts.”
Adam has seen first-hand how AI is reshaping the marketer’s toolkit, he knows where its value lies and crucially where the pitfalls are. With this perspective in mind, we started this interview by asking how the introduction of AI has changed his own approach to marketing.
Everyone’s talking about how AI has changed the speed at which we can produce sophisticated content. Texts, visuals, video, you name it. However, for me and my team, the real shift has been in how quickly we can now tackle the more complex behind-the-scenes tasks. Things that used to take hours, such as research, data wrangling and fine-tuning the tone of voice, can now be done in a fraction of the time. And then there’s structured feedback from multiple angles. Half the time it’s meh. But when it hits, it hits.
That said, all this progress just throws a sharper light on the same bottlenecks we’ve always had – time from specialists and client sign-off. At least now we’ve got a bit more headspace to deal with them. So yes, we’re faster. But that’s not the whole story.
What matters more to me is that AI has changed how we think about trust. For the past decade, I’ve worked in industries where trust, reliability and stability are the currency. First in an investment group, then years in energy and now in digital consulting, where we help clients with CX, branding and innovation, including AI. The game is still the same; I promote things to a relatively narrow audience of decision-makers. And in that game, precision trumps scale every time.
There are still many industries (and a vast number of companies) where even basic AI use cases are a long way off. Step outside the capital or your local tech bubble, and you’ll see what I mean. But even in those places, the shift is happening. Slowly, sure. But it’s there. And you can’t blame them, not until we know for sure that the models can reliably handle context without hallucinating, and until people using them have a bit more experience under their belts.
Right now, the tools are still very much “garbage in, garbage out”. And too many users expect magical results with zero effort. They can’t write a decent prompt, don’t set up a proper project or knowledge base, and treat LLMs like some sort of oracle. So, yes, garbage in and garbage out is a more common pattern than anyone would like. And that’s a tough place to work from.
I don’t believe in revolutionary tools. Some marketers collect AI tools like they’re rare trading cards, but I wouldn’t bet on them knowing how to use them. It’s partly down to the AI hype machine churning out new tools by the dozen every single day. Naturally, most won’t stand the test of time.
For me, it’s simple: less is more. Instead of wasting hours constantly test-driving the latest shiny thing, I’d rather get properly good at using one tool well. I still set aside time now and then to explore what’s new, but my priority is focus. And no one’s going to convince me that being an early adopter of every passing gimmick is going to work miracles. That might work well in fast-paced B2C TikTok marketing, but in enterprise communications? Total nonsense.
When selecting AI tools, begin with what your company truly needs. Don’t fall for the trap of trying to pick “the perfect tool”. What matters is the ecosystem: how your existing stack fits together, how easily a new tool integrates, and whether your team can use it effectively. The best tools are the ones that save time and reduce risk. And if you ask me, the most exciting tools are the ones I can rely on. The ones that help me do my job correctly.
Just scroll through LinkedIn and you’ll see the same big-picture debate playing out again and again: the supposed clash between “creating valuable content” and “creating shareholder value”. There’s an idea that valuable content means crafting everything by hand, slowly, thoughtfully and humanly. That the writer’s worth lies in the act of writing itself, and anything AI-generated leaves a weird aftertaste. Meanwhile, in corporate land, the pressure is all about speed, scale and hyper-targeting—more content, faster, more personalised.
But isn’t that kind of backwards? It all sounds very strategic on paper, but the reality is messier. A smart shareholder knows that it’s the outcome that matters, and that not every market responds to speed or volume. In some places, it’s about trust, reassurance and precision. And that’s not something you brute-force with content mills and a million touchpoints.
I’m not saying AI can’t help. Of course it can. But not just by churning out words. Used wisely, AI tools can help us move faster if we’re pointing them at the right things. But the human touch? That’s still everything. And I reckon it’s only going to become more valuable as the number of avatars everywhere around us rises. Soon enough, authenticity won’t just be appreciated, it’ll be a challenge to spot.
Human-ness is about to become a luxury. These days, a handwritten letter feels more meaningful than a thousand emails, and speaking to an actual person in customer support feels like a VIP experience. That tells you where we’re headed. Anything human will cost more. It’ll become a status symbol. Something rare, not scalable by design. And maybe that’s precisely why it’ll matter more.
The problem arises when a well-informed customer notices something amiss. A dodgy number, a vague phrase, a detail that doesn’t quite add up. They know their business, and they can tell when something isn’t 100%. And if they’re looking for quality, they won’t be impressed.
English lets you hide a lot. It’s spoken by people from all over the world, with endless shades and nuances. But in other languages? That mask slips fast. The closer you get to your audience’s native tongue, the more you need to earn their trust through accuracy and clarity.
The internet’s already overflowing with AI-generated gibberish, and it’s only going to get worse. We’ll all have to get better at distinguishing signal from noise, which will become increasingly difficult by the day.
That’s why brand matters more than ever. It becomes a trustmark, a signal of credibility in a sea of content. But that raises a tough question: is your brand distinctive enough to stand out? Is it unique enough not to be mimicked, muddled, or copied?
Because when anything and everything can be generated, the only things that hold real value are the ones people believe are original. And let’s not kid ourselves, this isn’t just a problem for the Disneys and Apples of the world. It affects everyone who builds a business on brand strength.
AI can already generate logos, visual systems, tone of voice, product imagery – no problem. And whether we like it or not, our brands are likely already present in some training dataset somewhere. That’s why conversations about originality and trust need to take centre stage. Otherwise, we may not even notice when we lose control of what’s “real”.
This cuts across every industry. It doesn’t matter if you’re selling cars, banking, skincare, or SaaS. Sure, most customers still make decisions based on price, emotion and convenience. But that’s exactly why strong brands, especially in B2B and enterprise, will stand or fall on their ability to signal real quality, real trust, real originality.
The more content AI creates, the more valuable the original becomes. And the bigger the mess, the less we know where that original resides.
AI offers us numerous new possibilities, fresh formats, playful stylisation, clever twists and word games. However, all of that only works if you’ve the time and space to play with the tools and explore new angles. In our creative process, the real magic often happens in the background.
Take information handling, for example. At FLO, we realised that for AI agents to be genuinely helpful, it’s not just about what the model can do; it needs to know your business. The trouble is, most company knowledge is fragmented and hard to access. It’s buried in docs, scattered across tools, or sitting in people’s heads.
We developed something we call Knowledge Intelligence – a framework used by our tool – that gives AI the context it needs to understand what matters. Where traditional Business Intelligence helps you build dashboards from data, Knowledge Intelligence takes it a step further. It connects internal know-how, cleans it up, structures it and makes it usable by AI for real-world decisions. Less guessing, more understanding. That’s how companies can unlock the power of AI with confidence, speed and relevance.
Or look at naming. We built an AI tool that helps us create names and trademarks. Sure, anyone can throw prompts into ChatGPT and get a list of catchy names, but that’s all they’ll be: catchy. No brand architecture, no long-term consistency, no deeper rationale.
That’s why we developed a naming process that blends AI with proper human input. It begins with a well-crafted brief, rich in context and constraints, which is then passed to AI, and the output is refined manually. We’ve integrated it with several data sources, including the world’s largest trademark database and domain availability checks, and layered in tools such as phonetic transcription for multiple languages and general linguistic validation.
The approach works especially well for us in industries like pharma, where naming a new drug isn’t just a branding challenge; it’s also a regulatory minefield, or automotive, where brand and product architecture are tightly defined. And that’s where this combination of AI muscle and human judgment really shines.
It’s not that AI is coming to take your job – not yet, anyway. But the person who knows how to use AI? They absolutely will. They’ll be faster, sharper and more capable. I don’t see entire teams being replaced just yet, but the gap between those who can work with AI and those who can’t is already massive.
One area where it’s becoming really obvious is writing and the ability to shape an idea, to give it form. I wouldn’t be surprised if we soon end up with two groups of people: those who can write well, and those who basically can’t write at all.
And here’s the real kicker. This divide is opening up most clearly between seniors and juniors. A senior professional with the right AI tools can do borderline magic. These are dream hires, especially in marketing, where people are already expected to wear five hats at once. AI just amplifies those superpowers. When everyone’s got the same tools, context, judgement and taste are all you’ve got left. Does your junior have that?
Which raises a tricky question… Is this sustainable? Are we heading for a world where junior people get fewer and fewer chances to do junior work, and, as a result, never develop the senior skills they’ll need later?
People say AI will take jobs from the average. I think that’s half true – what it’s doing is taking jobs from the junior end of the market. There’s a recent MIT study that looked into this, focusing on how LLMs like ChatGPT affect cognitive performance. The findings suggest that relying on AI for writing can impact memory, brain activity and language skills, especially in younger people. So we might be training ourselves into a problem that’ll hit us harder down the road.
It all starts and ends with people. For me, the biggest challenge right now is the lack of skills among those who are not yet accustomed to working with generative AI in a marketing context. What I struggle with most is when I need input from an expert colleague – say, a developer or analyst. They’re not accustomed to shaping their thoughts into a written form suitable for marketing communication, so they simply dump something into ChatGPT and hope it does the trick.
Even if they’re technically brilliant and know AI inside out, they often lack the promotion context, and so the output ends up being painfully generic. That creates a feedback loop where a poor input leads to a worse output, and suddenly my team has to dig through layers of half-baked, pseudo-smart content just to get to the actual expertise hidden underneath.
We genuinely try to do our work correctly, probably more so than most. In our line of work, quality always beats quantity. You can already see the consequences of getting this wrong all over the internet. Every piece of low-effort AI sludge we push into the world makes the next one worse. We’re polluting the ecosystem. That’s why AI needs to be used with intention, and its output constantly reviewed.
Fergal Glynn said in the first interview of this series that “the role of human marketers is shifting from execution to judgment” – and I agree entirely. I think a new role is about to become essential: a curator of AI outputs. Someone who protects brand consistency and ensures quality stays intact. The truth is, sooner or later, that’s going to be all of us.
We’re bingeing on buzzwords like empty calories, and the AI ones are the most overindulgent of the lot. But let’s be honest, it’s nonsense. AI is here to stay, and yes, it will eventually change everything. But over the next few years, it will mostly be a quiet assistant in the background, summarising, suggesting, easing the load on repetitive work, and generating a large amount of content. It may sound mundane, but it’s already changing the way vast numbers of people work.
Currently, AI still doesn’t understand reality the way humans do. It possesses encyclopedic knowledge, but it can’t improvise or make complex decisions based on lived experience. The biggest gaps I see are in reliability, safety and integration with real business processes. Most of the world is still in the “playing around with it” phase, not the “using it every day to run the company” phase.
The advanced features will only become available once we’ve sorted our data, clarified our brand and learned how to use these tools properly. Without that foundation, AI is just a magnifying glass on your existing mess.
AI won’t be taking responsibility anytime soon. It’s not a colleague, it’s a seriously powerful tool. And we’d do well to remember that.
Apologies in advance, but I’ve got more than one good piece of advice.
First: don’t underestimate education. Marketing often appears to be something anyone can easily pick up. It’s not rocket science, right? However, the longer I’ve worked in this field, the more I’ve come to realise how much of an edge people with actual marketing education have. (And yes, serious self-study counts too.)
Where I’m from (the Czech Republic), a large number of marketers entered the field through junior performance roles in e-commerce. They’ve worked their way up, but often without ever learning the basics. Fortunately, we’ve some brilliant people here who have made it their mission to educate the market, and things are improving. But the gap between trained, evidence-based marketers and those who’ve learned everything on the job is still shockingly wide. And the more AI becomes part of our toolkit, the more I wonder: What happens to data-driven marketers when AI is better with data than we are?
That’s why it’s more important than ever to understand the fundamentals. To think in systems and context. Yes, AI has fundamentally changed how we work. But don’t fall for the idea that it can now do everything for you. Two years ago, I was blown away by what LLMs could do. Today, I’m equally blown away by what the human brain can still do better.
AI is powerful. But don’t trust it blindly. Be intentional about when and where you use it. Sometimes, using a “dumber” tool gives you fewer surprises and fewer mistakes.
And above all, no one cares that you used AI.
What I’ve come to realise – and honestly, it’s kind of comforting – is that AI, at least for now, doesn’t create anything on its own. It just amplifies what you give it. If your input is weak – vague prompts, no context, no personal insight – the output will be just as bland. Something that doesn’t offend… but doesn’t land either. Just more noise.
But if you know what you want to say, who you’re saying it to, and why it matters, and you build your prompts on a solid foundation of know-how, tone, argument and style, that’s when the magic starts. AI becomes a tool for amplification. It helps you express things more quickly, clearly and on a broader scale. But it’s still you speaking.
That is the core idea and something every marketer should stick on a Post-it next to their screen: no one cares how you got there, as long as the result works.
That’s not to say that the ends always justify the means. It’s not about shortcuts or cutting corners. It’s about recognising that great results still come from thinking, experience and perspective. Whether you used a pencil, a keyboard, or a large language model to get there doesn’t matter. If the output is strong, relevant and trustworthy, no one’s asking who hit Enter.
AI won’t take our authenticity. But it can help us share it across languages, formats and contexts. If we understand why we’re doing something, AI simply helps us do it better and faster. And that counts.
