AI accelerates ideas: advantages and traps
AI does not lack speed; what it lacks is the discipline of the user to not be led astray by the machine.
AI accelerates most clearly in two areas: quickly sketching multiple directions when stuck, and creating many variations of an existing idea. However, research clearly notes a trap: those suggested by AI early tend to cling tightly to the first option, resulting in fewer and less diverse ideas compared to those not using AI. Acceleration only becomes an advantage when you proactively push AI to explore broadly, self-select, and do not settle for the first acceptable option.
- stuck and need a push to break free from the starting point
- need to quickly see many variations of a single idea
- want to explore more directions instead of making quick decisions
- need a truly distinct direction that sets us apart from competitors
- want to maintain uniqueness to avoid being copied
- need truly diverse ideas, not templates
AI truly accelerates, but not in the way many people think. The speed does not lie in AI generating better ideas than humans, but in its ability to quickly sketch multiple directions in a short time, helping you escape the initial block and see the breadth of the problem. The danger lies in the fact that high speed can lead users to stop earlier, rather than progressing further.
AI performs best where.
There are two tasks that AI can effectively support during the ideation phase.
- Exit from a deadlock: When you do not know where to start, AI provides a nudge to escape the blank page. Not to find a solution, but to have something to react to.
- Creating quick variations: Once a direction is established, AI helps quickly explore multiple variations of that direction, from tone and expression to image layout, without spending time manually creating each one.
These two tasks actually help shorten the initial phase of the creative process. However, both are tools for expansion, not for finalization.
The trap of framing thought
This is the most important part that Sinh Vũ wants you to know before using AI in the creative process.
Design fixation is the phenomenon where designers cling tightly to an initial example, unable to break free even if they want to. Research from arXiv/CHI 2024 notes that groups prompted by AI with images during brainstorming generated fewer ideas, less diversity, and less uniqueness than groups not using AI. This is not due to a lack of creativity, but because the human brain gets anchored to the first solution that seems good enough.
This mechanism operates quietly. You see the AI's suggestions, find them acceptable, and start thinking of ways to improve them instead of considering other directions. By the end of the session, all options revolve around the core set by the AI.
AI can open new ways of thinking and stimulate divergent thinking if used correctly. The outcome depends on how it is used, not on the tool itself.
Frontiers in Psychology, Stimulating or constraining creativity
When to use, when to sketch first
Ask AI first: Suitable when you are completely stuck, need a push to get started, or want a quick overview of the problem without preconceived notions. At this point, AI is a tool to open doors, not a decision-maker.
Sketch first, then ask AI: Suitable when you want to maintain uniqueness and avoid being influenced by machine-generated options. Sketch out a few of your own directions first, then ask AI to see if you've missed any angles or to create variations from your chosen direction. This method protects the original thinking of the creator.
In both cases, the discipline is: do not stop at the first option. Push for at least two to three distinctly different positioning directions before beginning to filter.
Common mistakes when using AI for ideas
- Accepted the first proposal because it seemed good enough: This is the most common mistake. "Good enough" and "the best" are two different things. The first proposal offered by AI is often the safest, not necessarily the most accurate.
- Confusing many variations with many ideas: Ten variations of colors and layouts of the same direction still represent one idea. True diversity should be measured by the number of different strategic directions, not the number of output files.
- Let AI guide the whole team: When using AI in a group session where everyone focuses on the same initial suggestion, the framing effect amplifies. Each person should sketch their ideas separately before converging.
- Measuring success by speed: "We produced thirty options in one hour" does not indicate progress. The right question is: how many of those thirty options are truly different?
The viewpoint of Sinh Vũ
In Sinh Vũ's process, AI is used to broaden the range of options in the initial stage, after which professionals select and refine further. Not stopping at the first option is a mandatory rule, not a recommendation.
Research from Frontiers in Psychology also notes that AI has a human-like bias: most ideas fall into conventional, familiar groups. This means that both machines and humans, without clear discipline, will gravitate towards safe zones. Professionals play a role in pushing ideas out of that zone.
Speed is a tool. The differentiation is the goal. When using AI to draft ideas, you need to ask yourself: am I using this speed to go further, or to stop sooner?
Decision checklist
Topic: How AI accelerates ideas and variations. Sinh Vũ guide, sinhvu.com
Select each item you find appropriate, then print or save as PDF to take with you.
If you have marked most of the signs above, this is the time to discuss in more detail. Sinh Vũ can help you review and propose a direction.
References
arXiv/CHI 2024, The Effects of Generative AI on Design Fixation and Divergent Thinking; Frontiers in Psychology, The paradox of creativity in generative AI; Frontiers in Psychology, Stimulating or constraining creativity. Practical experience from Sinh Vũ Studio.
Frequently asked questions
If you use AI to generate ideas, will it lead to uniformity with competitors?
There is a real risk. Research shows that AI tends to pull ideas from familiar groups because it is trained on existing data sets and leans towards what is popular. If you and your competitors ask AI in similar ways, the results will revolve around the same safe zones. The way to break free is to ask questions with clearly differentiated criteria, then use the judgment of professionals to push ideas beyond what the machine suggests.
Does generating many AI variants mean many ideas?
Not necessarily. Ten variants revolving around the same axis are still one idea, merely changing colors or small shapes. The criterion for evaluation is not the number of sketches, but the number of truly different directions in terms of positioning and emotion. When receiving variants from AI, Sinh Vũ advises you to ask: do these options represent different strategic choices, or are they just the same direction repainted?