AI for Creativity: Enhancing Idea Generation with Creative Methodologies

Every idea, regardless of its origin, typically moves through four distinct stages. The first stage is **Research**, where extensive information is gathered about the problem, competitors, audience, and trends to saturate the subconscious. This is followed by **Focus**, where the collected data is used to hone in on one or two key hypotheses that serve as a foundation for idea generation. The third stage is **Generation**, a phase of brainstorming where a multitude of ideas, even seemingly unrealistic ones, are formulated without immediate judgment. Finally, **Filtering** involves evaluating these ideas against specific criteria such as feasibility and budget, ultimately selecting one or two viable concepts for testing. AI can significantly support the research, focus, and filtering stages by rapidly processing information and identifying patterns. While it can assist in idea generation, its role here is more as a stimulator than an independent creator, as it operates within predefined patterns and lacks the human capacity for truly out-of-the-box thinking.

The quality of AI output is directly proportional to the quality of the input prompt. While AI can respond to simple requests, vague prompts can lead to guesswork, inaccuracies, or even fabricated information ('hallucinations'). To improve AI responses, structured prompts are essential. A **minimal structure** includes the goal or task with context, the desired format of the response, and any limitations or additional instructions. For example, instead of 'Write a post about choosing a bouquet for September 1st,' a better prompt would specify the target audience, the persona of the writer, the desired number of tips, and specific exclusions. A more **advanced structure** can be built using the PARTS framework: Persona (who the AI should be), Aim (the objective of the response), Recipients (the target audience), Theme (the specific topic), and Structure (the desired format). By providing detailed 'building blocks' within these structures, users can guide the AI more effectively, leading to more precise and useful outputs. Experimenting with different prompt structures is key to finding what works best for specific tasks.

For those looking to leverage AI in their creative endeavors, several tools stand out. For **idea generation**, Anton Lebedev-Romanov recommends **ChatGPT** and **DeepSeek**. When it comes to **image creation**, **Midjourney** and **Gemini 2.5 Flash Image (NanoBanana)** are powerful options. For **video production**, **HeyGen** is a notable tool. For **marketing-specific tasks**, such as defining target audience segments, the online platform **Board of Innovation** offers integrated AI capabilities. These tools, when used strategically and in conjunction with human expertise, can significantly streamline the creative workflow and enhance the quality of generated ideas and content.

In summary, artificial intelligence serves as a powerful amplifier for human thought, not an independent creative entity. The human role remains paramount in setting tasks, critically evaluating AI-generated content, and providing the strategic direction. AI can be effectively combined with creative methodologies like CRAFT to unlock novel solutions. There is no one-size-fits-all approach to using AI for creativity; continuous experimentation and adaptation are necessary to find the most effective combinations for specific company needs. For those seeking to harness AI as a creative partner, further learning through specialized courses can provide valuable insights and practical skills.