A successful creative project depends on a smooth flow of feedback. When all stakeholders offer constructive suggestions on time, creative teams are more likely to deliver great creative.
Unfortunately, it doesn’t always work this way. The creative review process is frequently hampered by vague, late, or scattered feedback that’s difficult to track and organize.
As artificial intelligence evolves, AI tools are emerging to support creative review and approval.
In this blog post, we’ll explore how creative teams can integrate AI to streamline creative feedback issues, as well as suggest improvements to the creative assets themselves.
What we'll cover
Table of contents
The negative impact of conflicting creative feedback
Every designer knows that sinking feeling: As the clock ticks, feedback trickles in. But not only is the feedback vague (“This looks weird”, “The colors aren’t sexy”), it’s delivered haphazardly across email, Slack, and other tools that were not built to review and approve creative elements. On top of that, the feedback arrives late on a Friday and the final deadline was the prior Wednesday.
Sometimes the feedback doesn’t come at all, leaving creative teams waiting in limbo. The consequences of conflicting feedback can negatively impact team dynamics and overall creative quality in the following ways:
- Delays: When stakeholders provide conflicting feedback, designers may become unable to act, delaying project timelines.
- Creative inconsistency: Conflicting feedback may result in creative work that tries to please too many points of view, resulting in a disjointed final product.
- Quality compromises: Designers may make hasty changes to satisfy conflicting feedback, watering down the original vision.
- Designer disengagement: Designers with no clear guidance may deliver the bare minimum just to finish the project.
- Communication breakdown and team tension: Team members stop sharing opinions because they’re worn down by frustrating feedback. This lack of resolution can erode trust and teamwork.
- Revisions and costs: Mounting revisions can inflate project costs, especially if changes are made late in the process.
It shouldn’t be this hard to achieve a harmonious review process. Creative directors should be vocal within the company about the importance of timely and constructive creative feedback. But they may also consider implementing AI tools to fill in the very real gaps left by conflicting creative feedback.
How AI helps facilitate creative collaboration
There are two main ways creative teams can use AI to improve communication and efficiency within their creative review process.
AI collects feedback from different channels
AI can automate the time-consuming task of gathering and organizing the actual feedback. Ideally, all your creative feedback is organized on the same platform. But it’s more likely feedback is arriving piecemeal via email, Slack, Asana, and other communication and project management tools.
AI-powered collaboration platforms such as Ziflow, Miro, Notion, and several others can streamline the creative review and approval process by consolidating feedback from multiple stakeholders, prioritizing suggestions, and facilitating discussions within the team.
While AI can’t fix the very human tendency toward vague, late, or non-existent feedback, AI-powered tools can analyze the feedback that exists and summarize common themes using NLP (natural language processing). This helps designers address frequent feedback and concerns. AI can also analyze the sentiment of feedback to gauge emotional tone, which helps designers understand not just what needs improvement, but also how it's being communicated.
AI analyzes design elements and offers suggestions
AI-powered tools such as ZiflowAI, Adobe Sensei, and Canva can examine layout, color schemes, and typography, and provide instant feedback based on established design and user experience (UX) principles. Such AI suggestions can be a great uniter when designers and stakeholders have reached a stalemate, or if stakeholders are having trouble articulating what changes they want.
For example, teams could ask the ZiflowAI chatbot: “What imagery should I use to suggest I’m a luxury brand without appearing elitist?” The chatbot will respond in seconds with ideas for visual elements that could solve your problem.
Additionally, AI can also spot design errors such as color contrast or inconsistent spacing, helping designers ensure that their work meets technical requirements.
Integrating AI into your creative review
Designers should resist over-relying on AI and automation, as human judgment is the cornerstone of exceptional creative.
But when AI is used to support designers, it can serve as an antidote for conflicting feedback loops that delay the creative process.
Here are four tips for teams looking to implement AI for creative review.
- Have clear goals: Identify upfront what aspects of the creative review could be improved by AI. Do you want suggestions for your actual creative assets? Do you want to automate feedback collection? Improve team collaboration?
- Choose the best AI tools for you: Seek out tools that specialize in the creative review areas where you’re lacking. Compare different tools to find the right fit.
- Use AI to complement human creativity: All team members should use AI-generated insights as a companion to their intuition. Let AI make suggestions, but final decisions should always be human.
- Assess AI impact regularly: Is the team benefiting from AI insights? Get consistent feedback about the pros and cons of AI integration and make adjustments as needed.
At Ziflow, we’re excited about how AI merges human artistry and analytic prowess to smooth over conflicting creative feedback. With AI as a collaboration guide, it’s easy to envision a future where creative feedback is no longer muddled and plodding but is the clear stepping stone to creative excellence.
