It’s a fact that creativity has always differentiated humans from machines. But AI is changing our beliefs and casting doubts on how wide the gap truly is.

Our creative prowess is one crucial atom that has always differentiated us from machines. It’s the intuition, complex thinking, and intent behind the process that drives the difference between human content and machine content.

But the rise in AI adoption has made business leaders and marketing professionals revisit this argument.

The ability to create was peculiar to a bunch of creatives, such as writers and designers. But today, with a couple of keystrokes and research-driven prompting, anyone can ask ChatGPT to produce a high-quality blog, design an engaging ad, and even pen down a novel.

The only succeeding question has been one of quality. Does the AI-generated blog compare to an expert with a decade of knowledge or the AI-written novel to Shakespeare’s?

However, to what extent does it hold precedence, especially over the speed and efficiency AI can afford? Why are we still stuck at using AI as a tool as an expressway to achieve business outcomes? Maybe because we are asking the wrong questions, and the existing focus needs to shift.

The market is actively investing billions into AI, giving rise to speculations on how modern tech could replace creatives. This vision is short-sighted, giving rise to even more doubts-

What is creativity without the human touch?

Let’s start the AI-creativity debate from here.

The AI-creativity debate

The market is proactively investing in the latent potential of AI, and it’s been constantly exploring the extent to which generative AI can thrive in a creative environment. And actually end up amplifying content. It was ChatGPT that prompted this thinking.

It had the market routinely questioning the disparate differences between human-created and artificially produced creativity. There are prevalent questions that have been answered:

1. How does one nature of creativity differ from the other?
2. How do you decide which one is worth valuing more compared to the other?
3. Does it all boil down to valuing the labor in it?

Basically, the advent of gen AI sparked and even fueled doubts regarding the uniqueness and superiority of human-produced creative assets. So far, the advanced models have been able to create collections of different content formats- from audio to images.

And at the nexus of this wonder movement, there have also been moments of panic- does it compare to what humans are capable of? These are the two broad sentiments regarding using generative AI tools for content creation.

And business leaders and marketing professionals echo the same sentiments.

AI will replace human creativity: Is it a skewed perspective?

To a very significant extent, AI has become a fundamental aspect of marketing storytelling. And the segment that has faced the biggest hit is content writing.

Whether it’s B2C or B2B, artificial intelligence has witnessed a broad popularity. While it hasn’t yet taken over the workforce, it’s working towards it. It has sparked discussion around the fragility of human employees, how easily they’ll be replaced by this modern tech.

And it has led to a widespread belief: AI suppresses creativity. This purview is merely a speculation.

But to dig deeper into this, it’s crucial to grasp what creativity truly is and the space AI occupies amidst all of this.

A straightforward definition of creativity foregrounds the ability to create something new, practical, and surprising. An understanding that is one of the most significant hallmarks of human intelligence. So, when we’re asking whether AI does entail creative prowess, then we are basically probing if it can produce something new and surprising.

The age-old question was whether machines can generate something new. And the same has applied to AI since its introduction. The early-age programmers, Ada Lovelace and Alan Turing, dismissed any nod towards machine-generated value, one that cannot be imagined or delivered by human intelligence.

Even initial AI models, such as ChatGPT, echo this limitation. The tech’s creative output remains substantially derivative, at least for now.

Novelty and usefulness vs the element of surprise.

The truth is, creativity is messy, and its process inarguably cannot be copy-pasted. The intent, context, and judgement that creativity demands- it’s all human-centric traits. These are characteristics that truly aid humans in instilling the kind of creativity in the work they do.

So, the real question is, are large language models truly capable of creating something unique? Or are they adept at sifting through a myriad of possibilities and then creating something that appears novel? Can machines that lack the fundamentals actually be creative?

The long story short is that AI models can fundamentally do what we prompt them to do, and all of it is whatever we’re acquainted with. The thing is that LLMs are trained on massive datasets and outputs derived from probabilistic models. The responses are created from patterns they’ve learned and constantly operate on.

And even though artificial intelligence does create any ‘novel’ ideas, it does so through a specific brute-force approach. Unlike human creativity, which is powered by intent and purpose.

Does AI realize it’s being creative?

It’s a widely known concept that artificial intelligence systems aren’t creative in the traditional way. It exploits human ideas and imagination to drive anything unique, offering a sort of creative illusion.

If you roll two dice enough times, there is a significant probability that you’ll get an unusual combination at least once. This output is incidental, not purpose-driven. And that’s how the current AI models function.

Think about it: human creatives draw on complex thought processes and experiences to execute even the tiniest of ideas. It takes them days and even weeks to convert a single idea into a finished model. There’s a web of emotions, experiences, and cultural contexts that are woven to materialize a creative output.

The missing aspect is intent. And this is what is actually substantial for advertising and marketing to build genuine connections.

Do you think this sort of complexity can be tackled by learning systems that remain within a box?

Their reliance on historical data is where these models falter. Your AI models don’t know any better, at least not yet. And this stumbling block can easily give rise to legal and copyright issues- something that can topple industries such as advertising and marketing.

However, this is merely one side of the coin.

The other side doesn’t entirely cancel out AI’s potential to ideate and bring to reality any creative properties. This is something tech investors, business leaders, and Wall Street broadly believe in. And this is the vision that drives billions of dollars’ worth of investment into AI infrastructure.

AI as the strategic co-creator or a tool?

If you look closely, the crux of the conversation makes a 180-degree turn here. The conversation doesn’t surround whether ‘AI can be creative,’ but rather, to what extent it will transform creative processes.

In a recent study on Gen AI’s influence on creativity in the advertising domain, the conclusion was simple: the increasing use of Gen AI has undermined creative diversity. There’s a lack of differentiation, and each different style or format of creatives has been standardized.

With ad and marketing agencies leveraging the same prompts and data, and a strict adherence to the policy, ‘whatever worked before, could work now’- the market is facing acute uniformity. As everything becomes better, i.e., as AI helps with speed and scale, everything becomes the same. The same frameworks unify the outputs- the inflection point.

From here on, there’s one road to take- differentiating strategies to stand out.

In the same study, one of the respondents, A Head of Digital-

“I think we went through a similar thing where every Instagram grid looked the same because customers liked…this kind of imagery with this kind of text…We may end up having to go down that path with Gen AI, till you get to that inflection point…where you have to then spread back out and differentiate because everything is going to look the same if you allow it to.”

If you think about it this way, AI-generated content could become stale very rapidly. And avoiding this could demand a lot of maintenance. Someone has to take accountability and survey the end product that’s reaching the market.

AI and content creation: an assistant or a collaborator?

There are two determinants that every creative work is assessed against: novelty and usefulness (value)-

1. Novelty measures the extent to which the output deviates from the norm and expectations.
2. Usefulness assesses the relevance and practicality of the concept executed.

About these two components, Gen AI can work less as a job replacement and more as a collaborative tool. And the result is co-creation, a means to leverage AI in a way that augments human creativity.

One approach where its functionality has grown common is its role as a springboard for human-generated content. You can generate ideas and outlines using the AI tool, i.e., use it to provide prospective starting points that could be used to undertake different creative plotlines down the road. It’s up to the human creator to choose which path to take.

But this perspective also poses a challenge. What if gen AI roots the writer to one specific idea or starting point? The ability to establish multiple perspectives on a single situation stems from human intelligence. Because of their capability to judge. But by focusing on a single perspective, it could restrict the creator’s own thought process. And sometimes, it also conveys confirmation bias.

This way, the output would be less novel and sound similar to other content. This is where its derivative nature poses as a hindrance.

So, basically if you think about it. AI’s space in the business landscape rests on using it right, and not just using it as one pleases.

“Metacognition — thinking about your thinking — is the missing link between simply using AI and using it well.”

Each new AI model and tool brings with it another promise of enhanced storytelling and creative opportunities. This underlying value, in the form of efficiency and scale, that AI can still provide- this is how modern tech is helping human creativity evolve.

AI might not be creating the original and thought-out content that marketers and advertisers want it to. But it’s augmenting humans’ role in the creative process.

Humans are no longer mere content creators. They’re curators and editors of Gen AI content.

What AI’s perfect at is research, planning, and ideation. And at the advanced level, its capabilities of summarizing information quickly and generating multiple ideas to inspire writers and designers are in themselves a motivation. It’s a springboard, facilitating a flow of ideas, concepts, and plans to keep the blank pages filled in.

It is a strategic co-creator, at least given the capabilities of the most advanced models on the market. But only when used right.

Most businesses and teams are integrating AI models such as ChatGPT and Gemini to complete their work. But the question is, is this what AI is supposed to do- to complete your work or rather, improve it? And where is the human perspective instilled in the output? Are we at the stage where outcomes are assumed correct because they’re fabricated by a machine, all because machines can never be wrong?

This assumption is false. Humans must remain at the center of creative endeavors to retain brand authenticity and creative distinctiveness.

“This idea that you can just put something into a machine, and it bangs out an answer, and you go with it is ludicrous. The inputs you add based on your experiences- that’s the secret sauce. That is the authenticity.”

Your content creators, whether designers or writers, and SEO experts, must work in tandem with AI. A stable culture of creativity, experimentation, and inclusion is only possible when the output connects with overall brand goals and positioning.

At the nucleus of the AI-creativity debate is also an inquiry into transparency.

Both disclosure and transparency are of tremendous importance to advertisers and agencies. And principally due to the AdTech black box, there is an ensuing demand to peek behind the advertising processes, from the bidding to asset creation.

Think about the ad agencies that use AI models. The key concern here revolves around being transparent about where the models are deployed across the entire creative development process. If you’re a client paying an agency to come up with ideas using AI, won’t it beat the actual objective? The question here centers on whether outsourcing the ad agency is worth it.

And across advertising and marketing, there are always chances of copyright infringement, sensitive data disclosure, or even desensitized content based on historical data.

Making transparency between agencies and their clients imperative.

The bottom line is that the onus of accountability and responsibility lies with humans, at least in the current scenario. It’s on the brand, the humans, and the agency leveraging it.

The scrutiny and question isn’t whether AI is replacing human creativity. Instead, to truly understand AI’s space in creative strategies and content creation, the weight should be on-

Can AI balance creativity with ethical regulations? And to what extent will it be able to see this through without human interference?

Only an answer to these can truly foreground a response to the persisting question: Is AI creative?