Read time: 3 minutes 

Generative AI tools like Dalle-3, Midjourney, SORA, Firefly and the like are amazing but they can spark concerns that human creativity will become less valuable -  in a world where AI can generate an infinite canvas of ideas and content, in a few seconds

There is no doubt these tools are impressive - we use them every day - but can they replicate human creativity in all it's wild glory? Can AI itself be strategically creative, having the ability to deeply understand consumers, formulate innovative brand platforms, and chart disruption-focused creative strategies.

This is the core of human creativity - a weird blend of data, art and science that can suck air from a room or stop traffic with a graffit-laden roadsign

Rather than killing creativity, AI can augment how we empower human creativity. Strategic roles will involve curating and refining AI outputs to craft differentiated creative strategies. We share examples of AI creativity limitations today, along with an emerging toolkit that balances AI and human strengths.

"I'm scared of losing the human touch in creativity"
- Internal comms director

The Rise of Generative AI

In the last 2 years generative AI exploded into the mainstream. Tools like DALLE-3, Stable Diffusion, Runway ML and Eleven Labs illustrate AI's ability to generate text, audio, visual and video content.

ChatGPT, Claude and open source LLMs such as Mistral and Llama are strong in conversational ability, summarisation and in GPTs case, data analysis.

Understandably this triggers existential questions. If AI can paint pictures and write novels, what room is left for human imagination and ingenuity?

Current Limitations of AI Creativity

While the outputs of generative AI seem creative, the technology still has clear limitations today:

• It lacks Strategic Understanding - Generative AI has no innate comprehension of long-term brand building or how to craft platforms that can drive disruption. Without understanding brands, categories, and consumer needs deeply, its creative options lack strategic grounding. For example, DALL-E might generate novel packaging visuals but cannot formulate an emotional brand purpose.

• No Subject Matter Expertise - AI applications have no specialised skills or training. While programs can synthesise information, they lack human lived experience. As a result the creative possibilities they offer will stay relatively surface level. 

• Mirrors Existing Biases - Because models are trained on existing cultural content, generative AI can amplify stereotypes and stale tropes rather than breaking new ground. For example, DALL-E images of CEOs predominantly feature white men in suits because that matches historical data patterns.

So while tools like DALL-E have incredible technical capabilities, they don’t fully replicate human creativity. Their current imagination limitations means AI cannot drive disruption or category innovation alone. They offer raw materials but lack the spark of human understanding that rewrites the rules.

That said, in narrow domains AI creativity has more potential. Crafting a fictional story, composing a song chorus or designing future furniture objects are easier to automate. However, the breadth needed for practical innovation possibilities eludes AI. Building a brand, designing pioneering customer experiences, writing award winning films - all demand strategic leaps only humans can achieve right now.

AI and Human Creativity Play Together

Rather than AI killing creativity, the future is both human and AI creativity playing together at their best. AI generates options, humans contextualise concepts and make strategic choices. Curating, refining, and realising possibilities will be the differentiating human capability.

The tools to support this balance are already emerging:

Idea Generation - Instead of relying solely on human ideas that risk being myopic, AI offers radically different prompts to reframe thinking. AI visualisations spark entirely new creative directions through images humans would never conceive alone - or at least take a significant amount of time to ponder.

Scenario Exploration - Tools like ChatGPT allow quickly building out and pressure testing strategic scenarios that previously required months of analysis. In hours, a human strategist can assess vastly more possibilities through AI-testing iterations - but it still required human oversight to really make it work.

Mass Personalisation - Humans craft a disruptive brand purpose and experience strategy which AI then translates into endless tailored variants for individual sub-segments. Opening scale opportunities that would be impossible to do manually.

In essence, new tooling allows the multiplying human creativity while keeping strategic choice and oversight. Handled well, it suggests an era of unprecedented innovation rather than one with less creativity.

The New World of Creative Strategy

While parts of production will be automated, human creativity and judgment become even more important in building sustained competitive advantage. When disruptive strategies get copied quickly, standing apart demands unlocking creativity constantly.

• Setting Creative Direction - Guiding leadership teams to make bets based on cultural foresight and category intuition
• Building Capability - Helping brands setup structures, tech stacks, datasets and talent models that foster serial innovation
• Curating Output - Refining and selecting the best AI content to craft it into creative strategies with edge and elevation

The future likely demands more creativity than ever before. Getting this right unlocks the full disruptive potential of human and machine intelligence in harmony. Rather than killing creativity, applied imaginatively there are signs generative AI could spark a renaissance.

AI won't kill creativity, humans are very much in the loop.