AI-Augmented Creativity: Rethinking the Role of Human Imagination in Digital Experience Platforms

By Anubhav Tiwari, Senior Product Manager at Material

It’s a familiar story. In many organizations, marketing and brand teams are swamped and the creative pipeline is a mess. In the bustling world of digital experience platforms (DXPs), the problem is usually assumed to be a “capacity issue” or a “talent gap.” The default fix? Hire more people or double-down on faster tools. But most bottlenecks have little to do with skill or imagination. Instead, they’re symptoms of broken systems.

When AI is introduced into such environments, it rarely fixes the root causes. Even the most sophisticated generative tools will only amplify existing inefficiencies and produce a higher volume of generic, off-brand content. In other words, AI doesn’t fix a broken creative pipeline; it just moves garbage faster. So, it’s time to stop treating creative bottlenecks as a people problem and start addressing it as a systemic architecture problem.

The Infrastructure Gap

This shift in perspective – from blaming teams to examining infrastructure – is critical. Even with mature platforms like Drupal, most organizations still lack the foundation to support an agile, AI-augmented creative process.

Without this foundation, teams can’t:

• Bring diverse creative inputs together from ideation to execution.

• Iterate with structured, integrated feedback loops.

• Support human judgment at scale.

AI can generate endless variations of headlines or campaign concepts, but without the right data and infrastructure, it struggles with tonal nuance, brand context and audience insight. The danger isn’t in AI itself, but in assuming that dropping a tool into the process solves the deeper creative challenge. This is fueling two dangerous myths:

1. Adopting AI is enough.

2. Speed equals creativity.

Neither is true. Flooding the pipeline doesn’t create value, it dilutes it. This gap is already showing up in three big ways:

• Content fatigue. Without audience data to shape what gets produced, marketing teams push out more content than ever — overwhelming audiences and diminishing impact.

• Unmanaged AI adoption. Many teams are implementing generative AI tools without a clear structure, governance or feedback loop. This ad hoc approach creates outputs that look efficient but are inconsistent and disconnected from the brand narrative.

• Shallow platform maturity. Most CMS and DXP stacks are built to scale output, not quality. These platforms don’t enable real-time creative feedback or enforce brand guidelines.

These cracks explain why high-potential teams repeatedly hit the same walls: endless review cycles, diluted brand voice and disconnected campaigns. The issue isn’t that AI produces “bad” content; but that it produces more of the same bland content, flooding your channels with noise in perfect grammar.

AI’s Role Isn’t to Create – It’s to Expand Possibilities

If the real issue is broken systems, then AI’s value must be reframed not as a substitute for creative authority, but as a force multiplier within a redesigned process. Its true strength lies in its ability to expand the system by generating a vast range of options, unlocking creative variance and removing friction from the idea-to-execution pipeline.

Leading organizations don’t ask AI to be the artist. They use it as a multiplier, enabling faster production with structured human oversight. In this reframed narrative, the role of a creative professional shifts from a content generator to a strategic editor who curates, refines and provides the final, nuanced touch that ensures brand integrity and emotional resonance.

Make Your Creative Stack Learn

Even with AI generating endless variations, the real edge comes only when the system itself can learn from what works and what fails. Yet most AI-augmented stacks are stuck in “generate and ship” mode, with no feedback loop to carry lessons forward. All the rich campaign data including performance, audience behavior and brand response evaporates and doesn’t help in refining content creation, which is a continuous process.

To truly leverage AI, creative platforms must be designed to learn by treating performance metrics as training signals, where every campaign becomes a valuable dataset and every dataset sharpens the next campaign. The loop compounds into a system that gets more precise, on-brand and effective with every cycle.

Treat Brand Identity as Live Data Asset

Feedback loops make the system smarter but encoding brand identity as data is what makes it distinctive.

Every brand has a unique tone, set of values and cultural nuance. But too often, this identity lives in static documents, not in the systems that create content. To scale creativity with AI, it is important to treat brand identity as a strategic, operational data layer which is trainable, measurable and governable.

Organizations are already encoding brand elements into prompt libraries, tone scoring systems and feedback models. When brand taste becomes trainable data, the creativity it enables becomes scalable. You can deploy AI to generate options that are not just fast, but also fundamentally aligned with your brand’s identity, allowing your team to focus on the truly strategic and imaginative work.

Four Strategic Shifts to Enable AI-Augmented Creativity

The transition from static guidelines to living data and manual workflows to a truly scalable, AI-augmented creative system is defined by four core changes:

1. From team-owned ingenuity to platform-built inspiration
   The shift is from creativity locked inside departments to creativity embedded in the system. When imagination is built into the platform, it scales across teams and touchpoints instead of bottlenecking in a single function.

2. From faster outputs to variance and iterations
   When AI generates variations, experiments and refinements at scale, human teams are free to focus on curation and strategy rather than first drafts.

3. From manual editorial review to systemic feedback and refinement loops
   The win comes from moving past subjective, one-off reviews. Performance data, audience signals and brand guidelines flow back into the system, ensuring each new output is sharper and more effective than the last.

4. From static guidelines to living, programmable brands
   The advantage lies in making brand rules active. Instead of sitting in PDFs, they’re encoded into prompts and models, guiding outputs in real time and keeping everything on-voice and on-strategy.

Together, these shifts redefine creativity as an organizational capability embedded into the digital experience platform rather than siloed inside teams.

From Content Stack to Experience Engine: How Drupal Powers AI-Human Co-Creation

Drupal’s architecture shows how these shifts come together in practice, with AI and humans working in tandem.

• AI generates structured, multilingual content at scale, handling the heavy lift of repetition and translation.

• Editors refine intent, emotion and narrative arc, giving the work resonance and brand authenticity.

• The platform enforces tone and consistency across templates, ensuring every iteration strengthens the brand instead of diluting it.

This is Drupal not just as a CMS/DXP, but as an AI-human system where scale meets nuance.

Creativity at Scale: An Edge Only System Thinkers Will Have

The next wave of creative advantage won’t come from AI hype or human brilliance working in isolation. It will come from those who design creativity as a system-level capability, where infrastructure enables human curiosity and imagination.

• A human-only model can’t scale.

• An AI-only model can’t matter.

• The win is a learning creative system where AI expands options and humans decide what’s right.

Drupal hints at this future, where platforms don’t just publish but learn – embedding brand guidelines, performance signals and co-creative loops directly into the stack. That’s the shift from generating content to compounding creativity.

Organizations considering this shift should ask themselves:

• Are you designing systems that learn, or just ones that ship content?

• Is your brand identity encoded in your tools, or trapped in a static PDF?

• Do your teams act as draft machines – or strategic editors of what truly resonates?

If you’re still framing the debate as AI vs. humans, you’re asking the wrong question. Reach out to Material’s experts to learn more about building systems where imagination scales.