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Is AI Killing Originality in Design — or Fueling It?
Artificial Intelligence (AI) has emerged as a game-changing force across multiple industries, and digital marketing is no exception. From chatbots and programmatic advertising to predictive analytics and content generation, AI has become deeply entrenched in how marketers operate. But as AI tools increasingly influence design decisions — from website layouts to ad creatives and branding assets — a poignant question looms: is AI eroding originality in design, or could it be the catalyst that unlocks new creative frontiers?
This debate isn’t just theoretical. It lies at the heart of how brands connect with consumers in an ever-saturated digital landscape. Let’s unpack the evidence, arguments, and perspectives on both sides — through the lens of digital marketing.
The Rise of AI in Creative Work
The use of AI in design is not futuristic; it’s here, and it’s growing. Tools like Canva’s Magic Design, Adobe Firefly, and Midjourney are enabling even those without formal design training to produce visually appealing content. These platforms leverage generative AI to automate and enhance everything from logo generation to colour palette selection and image manipulation.
In the UK alone, a 2024 Statista report revealed that 45% of marketing professionals have incorporated AI-based tools into their design workflows — a significant rise from 29% the previous year (source).
For many digital marketers, this acceleration means faster turnaround times, reduced costs, and scalability. Yet it also raises fears that creativity is being replaced by convenience, with algorithms regurgitating design templates based on existing trends.
The Argument: AI is Killing Originality
1. Over-Reliance on Templates and Predictability
One of the most frequently cited concerns is that AI fosters a cookie-cutter approach. Many AI design tools are trained on existing data — portfolios, images, and branding elements that are already in circulation. This leads to derivative outputs that, while polished, lack a distinctive flair.
For instance, brands using AI-generated ad creatives may find themselves using similar layouts, stock-style imagery, and typography. When everyone’s drawing from the same algorithmic pot, how does one brand truly stand out?
2. Commodification of Design
As AI makes design more accessible, it democratises creativity — but at what cost? A brand that once invested in high-end, bespoke design may now opt for an AI-generated visual identity that’s “good enough.” This erosion of value in professional design services is a growing concern for agencies and freelancers alike.
According to the UK’s Design Council, 38% of professional designers reported a noticeable decrease in demand for bespoke branding work over the last year, attributing it in part to the rise of AI-generated alternatives (source).
3. Loss of Human Nuance and Emotion
AI can identify what’s visually appealing, but can it truly understand cultural subtleties or emotional context? While machine learning models can simulate styles or mimic tones, they lack the intuitive understanding that a human designer brings to the table — especially in a culturally rich and diverse market like the UK.
Emotional intelligence and storytelling are core components of impactful design. AI can replicate aesthetics, but originality often lies in personal experiences, sociopolitical awareness, and cultural resonance — areas where AI remains tone-deaf.
The Counterpoint: AI as a Creative Catalyst
1. Supercharging the Ideation Process
Far from stifling originality, AI can serve as a springboard for creative exploration. Generative tools like DALL·E or Adobe Firefly can produce a multitude of variations on a theme, offering designers more options and pathways to pursue. Rather than replacing human creativity, AI augments it — helping creators explore visual territories they might not have considered.
Marketers, too, benefit. With AI tools producing mood boards, social assets, and concept visuals in seconds, teams can experiment more freely, iterating ideas at lightning speed without draining resources.
2. Level Playing Field for Smaller Players
For startups, charities, or small businesses that can’t afford a full-time designer, AI levels the playing field. They can now access tools that allow them to produce professional-quality visuals and branding with limited budgets.
This democratisation of design fuels originality at the grassroots level. A niche vegan bakery in Yorkshire, for example, might use AI to craft a visually compelling brand presence online — something previously out of reach without a hefty investment.
3. Data-Driven Design Decisions
AI excels at crunching data, and when integrated into the creative process, it can lead to more effective design outcomes. A/B testing of visuals, predictive modelling for audience engagement, and heatmaps for UX optimisation all empower marketers to align design with user preferences.
This data-informed creativity doesn’t diminish originality — it refines it. A brilliant visual idea that fails to connect with users isn’t impactful. With AI, marketers can fine-tune original concepts to meet both aesthetic and strategic goals.
Hybrid Creativity: The Middle Ground
Most digital marketers now find themselves embracing a hybrid model — where AI handles the heavy lifting and humans inject personality, cultural awareness, and nuance.
Take, for example, a London-based e-commerce brand launching a campaign for Pride Month. AI can help generate inclusive visuals, but human oversight ensures authenticity, cultural sensitivity, and brand alignment. AI becomes a tool in the creative toolbox — not the architect of the whole structure.
Many agencies are already building these hybrid workflows. Creative teams use AI to generate mock-ups or mood boards, which are then refined, reimagined, or even discarded based on team input. This not only saves time but fosters a more iterative and collaborative design culture.
Case Study: AI in UK Digital Campaigns
Example 1: The NHS “Get Vaccinated” Campaign
During the UK’s COVID-19 vaccine rollout, AI was used in audience targeting and image generation for localised social campaigns. While the core message was government-led, local campaign visuals were adapted using AI-powered localisation tools to reflect community demographics. The final design iterations were, however, reviewed and approved by human strategists, ensuring relevance and impact.
Example 2: Boohoo’s AI-Generated Influencer Campaign
In 2023, fashion retailer Boohoo experimented with AI-generated models to showcase clothing lines in digital ads. The AI-generated influencers sparked a mix of intrigue and criticism — with audiences questioning authenticity. Despite the controversy, it demonstrated how brands are testing AI not just in backend processes but also in public-facing design elements.
Ethical and Legal Implications
As AI takes on a larger role in creative workflows, ethical questions abound. Who owns the design generated by AI? If a logo is created by an algorithm trained on thousands of copyrighted images, does that raise infringement concerns?
Moreover, bias in training data can creep into design. An AI model trained predominantly on Western fashion imagery might overlook cultural diversity or perpetuate stereotypes — an issue of particular relevance in inclusive marketing.
UK-based agencies must stay vigilant. The UK Intellectual Property Office has yet to issue definitive guidelines on AI-generated works, but the legal landscape is evolving rapidly.
Practical Tips for Marketers Embracing AI Design
- Stay Human-Led: Use AI to speed up ideation or execution, but always have human oversight to inject originality, emotional intelligence, and brand voice.
- Customise, Don’t Copy: Avoid using AI-generated templates as-is. Treat them as drafts or idea generators that you can refine and customise.
- Educate Your Team: Equip marketers and designers with AI literacy. Understanding how these tools work (and their limitations) is key to leveraging them effectively.
- Audit for Bias: Review AI-generated visuals for representation, tone, and inclusivity — particularly when targeting diverse audiences in the UK.
- Stay Informed Legally: Monitor updates from regulatory bodies like the UKIPO and the Advertising Standards Authority (ASA) regarding copyright, data use, and ethical guidelines.
Conclusion: A Tool, Not a Threat
AI isn’t killing originality in design — but it is reshaping the creative process. Like any tool, its value depends on how it’s wielded. In the hands of mindful marketers and skilled designers, AI can unlock new realms of creativity, accessibility, and efficiency. But if used indiscriminately, it risks homogenising design and diluting brand identity.
Ultimately, the future of design in digital marketing is not AI or human — it’s both. The magic happens at the intersection of algorithmic efficiency and human ingenuity. That’s where originality thrives.
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