AI can now play a role in nearly every stage of creative production, from storyboarding and concept visualization to generating finished images and videos.
For enterprise marketing leaders, these expanding possibilities raise an important question: When should you actually use AI?
Up to this point, much of the conversation about AI in creative workflows has centered on efficiency. But speed is only one consideration. AI tools are also giving creative teams the ability to execute ideas that would have been impractical, or even impossible, just a year ago.
As AI offers value in more places, the challenge is determining what role AI should play in each project and which tools are best suited for the job. That decision should start with the idea, audience and creative objective, not the latest AI model or production tool.
Key Takeaways
- Start with the creative outcome, not the AI tool. Determine what the work should accomplish before deciding if and how AI should contribute.
- Treat AI use as a spectrum. Creative production can range from AI-assisted to AI-integrated to AI-led. No single approach is right for every project.
- Pressure-test AI tools against your audience and idea. Consider whether AI strengthens the message, how audiences may respond, how much creative control you need and what disclosures are required.
- Keep human judgment at the center. As AI expands what teams can produce, creative judgment and oversight become more important.
AI Adoption Is Moving Faster Than Creative Decision-Making
AI is already part of the creative process for most enterprise B2B leaders. What’s lagging behind is how effectively teams decide when and how to use AI tools.
Nearly all marketing leaders (97%) now use AI in their daily creative work, according to Canva’s 2026 State of Marketing and AI report. Adobe similarly found that creative professionals use AI on more than 40% of their projects. But widespread adoption doesn’t guarantee stronger creative outputs.
A year ago, a creative team might have used AI to generate an image or add motion to an existing asset. Today, teams can use a combination of AI models to build increasingly sophisticated images, video and entire production workflows.
Despite that evolution, there are signs of tension between what marketers can produce using AI and what audiences want to see. Canva found that 70% of consumers say they can usually tell when an ad is AI-generated because it feels like it is “missing its soul,” while 87% say the best advertising still needs a human touch.
That creates a new responsibility for creative leaders. When almost anything can involve AI, the question becomes whether it should.
Creative teams need more than a blanket mandate to “use AI.” They need reliable ways to determine how much of a role it should play in their work — and to move forward with confidence.
How to Decide When AI Belongs in Your Creative Process
AI shouldn’t change the fundamental order of the creative process. The idea still comes first. As AI tools become more capable and accessible, it can be tempting to start with the technology.
But that risks putting production decisions ahead of creative ones. The best creative teams aren’t handing an AI platform a brief and asking it to develop the campaign for them. They start by finding the human truths at the heart of the assignment, understanding their audience and developing a creative concept around those insights. Then they determine whether (and how) AI can help bring that idea to life.
Starting with the idea makes it easier to make intentional decisions about where AI belongs in the work, how much of the production it should shape and where human direction remains essential.
Ask five questions before choosing your production approach
There are five questions I recommend marketing and creative leaders answer when deciding how much of a role AI should play in their workflows:
- Will AI strengthen the message or distract from it? Using AI should serve the creative idea, not become the idea simply because the technology is available.
- How will the audience respond to its use? Consider whether people expect authenticity or human connection from the work and whether knowing AI was involved could change how they experience it.
- How much creative control does the project require? Generative production often involves experimentation and iteration. Some concepts, budgets and timelines have room for that variability. Others demand precise control over every detail from day one.
- What will you need to disclose? Platforms and jurisdictions are introducing requirements around AI-generated content and synthetic performers. Those disclosures can become part of the audience experience, so consider their impact during creative development, not after production.
- Does AI enable something we couldn’t achieve otherwise? This is where I see the greatest opportunity. AI can fundamentally expand creative possibilities when it allows us to visualize an idea, build a world or create an experience that would have been prohibitively difficult through traditional production methods.
Find the right place on the AI production spectrum
Your answers can help determine how much of a role AI should play in the work. Think about that role as a spectrum, from AI-assisted to AI-integrated to AI-led production:
- AI-assisted production keeps most of the traditional creative process intact, with AI supporting a specific step of the workflow. A team might use an AI tool to visualize an idea during storyboarding, generate an element within a larger production or add motion to an existing asset.
- AI-integrated production brings AI into multiple stages of the workflow alongside traditional creative and production methods. Teams can move between AI and traditional techniques depending on which approach gives them the control, quality and flexibility the idea requires.
- AI-led production uses generative tools for the majority of the execution, with the creative team directing, evaluating and refining the work. Today’s AI tools can create increasingly sophisticated imagery and motion, making this approach viable for ideas that would have been difficult or cost-prohibitive to produce via traditional creative methods.
No approach is inherently more advanced or creative than the others, and AI-led production isn’t the destination for every project.
The goal is to find the point on the spectrum that best serves each creative idea. Sometimes AI should play a small supporting role. Other times, it can fundamentally expand what the team is able to create.
The more AI leads production, the more important human direction becomes
A mature AI creative practice knows where AI makes the work better and where human judgment still needs to lead. AI can generate and expand creative options, but people still need to set the direction, evaluate the outputs and decide what ultimately serves the idea.
In many ways, moving toward AI-led production makes creative direction even more important. For more AI-led work, our teams use node-based creative production workflows that let us experiment across different models and carry the strongest outputs forward.
One model might produce the right starting image while another handles motion better. AI can also help develop and refine the prompts used elsewhere in your workflow.
That process can involve significant experimentation. For one recent campaign, my team worked through extensive prompting and iteration to get to the final assets. The technology expanded what we could make, but the quality of the final work still depended on human creative judgment.
One way to preserve that human direction is to establish creative guardrails before production begins. Align on the core idea, what the audience should take away and the elements that can’t be compromised. Then use AI to explore different ways of executing within those boundaries.
From there, build human checkpoints throughout production. Creative leads can review early outputs before they’re carried further into the workflow and make deliberate decisions about which directions are worth refining.
At the end, evaluate the work against the original creative intent, brand standards and quality bar rather than simply accepting what the technology produces. AI may generate more possibilities, but people decide which possibilities become the work.
The Best AI-Powered Creative Starts With Knowing Where AI Belongs
Many of the creative possibilities available today would have been difficult to imagine even a year ago. And a year from now, creative teams will almost certainly have a new set of capabilities to consider.
With AI in the mix, the tools will change and improve, but the responsibility of creative leaders won’t. Understand the audience, develop an idea worth executing and make deliberate choices about how to bring it to life.
AI gives creative teams more production possibilities than ever. But having more options also puts a premium on knowing which ones are worth pursuing.
Ready to explore how AI can strengthen your creative work? Contact Walker Sands to learn how our team can help you build and execute ideas that make the most of emerging AI capabilities.
