If you scroll through LinkedIn today, you will inevitably see a creator declaring: “I made this TV-quality ad in 60 minutes for $50.”
It is seductive. It is revolutionary. And, according to Marty Hungerford, founding partner at BRX, it is a “magician’s flourish” – a trick that shows the flash but hides the reality.
At Way We Do, we have been watching the polarization of AI understanding with concern. On one end, management teams are burying their heads in the sand, not knowing where to start. On the other, boards are demanding companies go “hell for leather” into adoption, ignoring financial waste and over-promises.
But the “happy middle” – and the only sustainable path forward – lies in a deep understanding of your operational processes and the problems you are trying to solve.
The Illusion of Instant Production
In a recent article for The Australian (December 8, 2025), Hungerford argues that cheap AI demos are warping C-suite expectations. When leaders see a viral video made in an hour, they ask: “If production is this simple, why do we need agencies, producers, and strategists?”
The answer is simple: Generation is not Production.
AI tools can generate stills, music, and voiceovers at lightning speed. But a viable, client-ready asset requires compliance, brand alignment, tone of voice accuracy, and claims substantiation. As Hungerford points out, the viral demos skip the critical steps that keep brands out of court and in consumers’ good graces.
In the rush to celebrate AI’s capability, organizations forget what advertising must still do:
Communicate clearly, truthfully, and distinctively.
And that does not happen without a carefully designed, end-to-end process.
This leads us to a fundamental truth that defines the future of work as stated by Hungerford: “While AI accelerates tasks, it doesn’t replace process. In fact, the quality of your process determines whether the AI output is usable at all.”
This resonates deeply with what we’re building at Way We Do.
AI is transforming production – image generation, voice synthesis, text creation, and even video rendering. But none of these tools decide:
- whether an image fits your brand guidelines
- whether a claim is legally sound
- whether messaging aligns with your strategy
- whether representation is ethical and accurate
- whether the final asset is compliant across channels
That is the domain of structured process, cross-functional role collaboration, and human oversight.
You can’t automate judgement.
But you can automate the steps around it.
Visualizing the Workflow: A Process Approach to AI Creativity
To understand how AI fits into a professional workflow, we need to look at it through the lens of Business Process Management.
Using the creative production examples from Hungerford’s analysis, we can map out a robust “AI-Integrated Creative Production Process.” This demonstrates that while AI handles the heavy lifting of creation, the process relies heavily on structure and human judgment.
Here is what a possible process looks like, broken down by who – or what – is doing the work. You don’t have to be a technical expert to appreciate the level of skill, know-how is needed to produce quality on-brand output.
Phase 1: Strategy & Preparation
Step 1: Strategic Briefing & Risk Assessment
Primary Owner: Creative Lead & Compliance Officer
- [Human] Define Objectives: Outline the audience, tone, and strategic message.
- [Human] Establish Negative Constraints: Create the mandatory “No-Go” list (e.g., “No competitor styles,” “No celebrity likenesses”).
- [Human] Claim Verification: Validate all product claims legal defensibility before scripting begins.
Step 2: Technical Translation (Script-to-Prompt)
Primary Owner: Technical Director
- [Human] Prompt Architecture: Convert the Creative Brief into the modular prompt syntax (Anchor + Action + Environment).
- [AI] Syntax Optimization: Use an LLM (e.g., ChatGPT/Claude) to expand simple descriptors into rich visual vocabulary (e.g., changing “blue light” to “volumetric cyan bioluminescence”).
- [Human] Negative Prompt Standardization: Distribute the “Safe Negative Prompt” code block to the production team.
Phase 2: Technical Setup (The Consistency Engine)
Step 3: Asset Anchoring (Zero-Variance Setup)
Primary Owner: Technical Director
- [Human] Reference Creation: Sketch or design the “Turnaround Sheet” (Front/Side/Back views) of the character.
- [AI] Model Training: The AI engine trains a LoRA or calculates an IP-Adapter embedding based on the reference images.
- [AI] Validation Generation: AI generates the character in 5 distinct test environments.
- [Human] Likeness Clearance: Conduct reverse-image searches on AI outputs to ensure no accidental copyright infringement.
Phase 3: Asset Production (The “Sandwich Method”)
Step 4: Structural Layout (“The Bottom Bun”)
Primary Owner: Concept Artist
- [Human] Greyboxing: Create a crude 3D block-out or 2D collage to lock composition.
- [Human] Camera Locking: Manually define the focal length, camera angle, and subject scale.
- [Human] Control Map Export: Export the layout as a Depth Map or Canny Edge Map.
Step 5: AI Generation (“The Filling”)
Primary Owner: AI Operator
- [AI] Image Synthesis: The AI generates high-fidelity textures and lighting based on the Control Map and Prompts.
- [AI] Iteration: AI generates batch variations (e.g., 20 versions) using random seeds.
- [Human] Curation: The operator reviews the batch and selects the best “Seed” for refinement.
Step 6: Human Compositing (“The Top Bun”)
Primary Owner: VFX Artist
- [Human] Product Overlay: Manually composite high-res photography of the real product over the AI background.
- [Human + AI] In-Painting: Human selects the mask; AI regenerates the specific area (e.g., fixing a hand).
- [Human] Color Grading: Manually match the black levels and white balance of the product to the scene.
Phase 4: Motion & Post-Production
Step 7: Assembly & Hallucination Cleanup
Primary Owner: Editor & VFX Specialist
- [AI] Image-to-Video: AI tools (Runway/Pika) animate the static assets into motion clips.
- [Human] Texture Stabilization: Apply deflicker tools to smooth out AI “boiling” artifacts.
- [Human] Narrative Assembly: Edit the timeline for emotional pacing and story flow.
- [Human] Humanization Pass: Add film grain and handheld camera shake to mask the “artificial perfection” of AI.
Step 8: Final Compliance & Output
Primary Owner: Compliance Officer
- [Human] Constraint Check: Final review against the “Negative Constraints” list.
- [Human] Disclaimer Check: Verify legal text legibility.
- [Human] Audio Verification: Confirm voiceover licensing rights.
- [AI] Data Tagging: AI automatically logs metadata (prompts/seeds) into the project database for future reference.
As you can clearly see in this process, there is more involved with producing a quality video than generating a quick, cheap one with AI in under an hour.
Humans direct.
AI accelerates.
Process integrates.
Humans decide and refine.
Why C-Suites Must Recalibrate Expectations
Efficiency is not the same as effectiveness.
A brand-safe, compliant, strategically aligned advertisement is not created by typing a prompt and pressing “generate.” And if C-suites insist on 60-minute production cycles, teams will be forced to cut exactly the corners that protect the business.
The question isn’t:
“How fast can AI make this?”
but
“How can AI make us more consistent, adaptive, and creative – without compromising standards?”
This mindset shift is critical for sustainable transformation.
The Road Ahead: AI Elevates Production, It Doesn’t Replace It
AI is not the end of creative production.
It’s the evolution of it.
The industry does not need to fear AI – but it must challenge the mythology around it.
The future won’t belong to those chasing shortcuts.
It will belong to those who build clear, repeatable, governed processes that allow AI to shine safely and reliably.
At Way We Do, we are investing deeply in this future – supporting organizations as they document, activate, and continuously improve the operational workflows that make AI useful rather than risky.
Because in the age of AI, process matters more than ever.
AI accelerates tasks.
Process ensures the output is worth accelerating.
