Generative AI has quietly shifted from being a futuristic concept to a daily companion. Over the past year, I’ve used tools like ChatGPT for writing, Midjourney for visuals, and Runway for short video concepts. At first, these tools felt like “assistants.” Now, they often feel more like co-creators.
I first realized their potential while creating marketing content for my previous job. That is where I was taught – and learned firsthand – how to use AI daily to optimize my workflow. What used to take hours -writing ad copy, structuring blog posts and captions, and experimenting with brand messaging – could suddenly be done in minutes. Since the company also covered the premium subscription, I could make full use of ChatGPT’s advanced features. I wasn’t just speeding up my work; I was expanding my creative and critical thinking. It offered multiple directions at once, forcing me to reflect on why I preferred one version over another. Instead of replacing creativity, it amplified it by giving me a creative mirror to think through ideas faster.
Yet every marketer who uses chat agents like ChatGPT has likely noticed the same limitation: a narrowness of perspective. The model reflects what is statistically common, not what is contextually insightful. When generating campaign ideas or headlines, it tends to default to safe, universal tropes rather than niche or counterintuitive angles that truly capture attention. In other words, AI can reproduce creativity, but it struggles to originate it. This limitation becomes especially visible when working in branding, where differentiation and emotional subtlety are key. ChatGPT might suggest a clever slogan, but it rarely surprises – it gives you what the internet already thinks is good. True creative insight still requires human judgment, intuition, and cultural sensitivity – elements that can’t be reduced to patterns of probability.
Then came visual tools. While I haven’t employed AI image generators for my professional work, I used AI to inspire me on certain elements of the visuals and the layout of the final project. As an example, for my previous blog post – I described an idea – a split world between traditional aviation and virtual travel – and within seconds, I had a hyperrealistic visual that perfectly matched the concept. That moment captured what makes generative AI so transformative: it compresses imagination-to-reality time from hours to seconds.
Again, it’s not without flaws. AI often delivers polished but “safe” answers. Creativity, by nature, thrives on unpredictability and imperfection – two things AI still struggles with. I sometimes notice how text outputs can sound formulaic or visuals too idealized, repetitive and almost too perfect, lacking the human quirks that make content memorable. There’s also a growing concern about over-dependence: when the tool becomes too good, do we stop exploring ideas ourselves?
One improvement stands out to me – especially after writing the text for this blog: It would be a “co-creation mode” – an interface where AI explains why it made certain creative choices and lets users steer tone, emotion, or intent interactively, almost like a conversation with a creative partner rather than a tool.
Generative AI has taught me that creativity isn’t dying – it’s evolving. The next leap won’t be about machines creating for us, but about humans learning to create with them.
So I’ll end with a question for you: When your next big idea comes along, will you brainstorm it alone-or with an AI sitting right beside you? ( I suppose it is the latter )
