Steve Jobs famously said, “Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty because they didn’t really do it, they just saw something. […] Unfortunately, that’s too rare a commodity. A lot of people in our industry haven’t had very diverse experiences. So they don’t have enough dots to connect, and they end up with very linear solutions without a broad perspective on the problem.”

AI takes this concept to a whole new level. Unlike humans, who are limited by personal experience and knowledge, AI has access to vast amounts of data and patterns. It can connect the dots in ways we might not even think of, making ideation faster, richer, and more insightful.

However, AI is not a substitute for human creativity. While AI can generate, analyze, and categorize ideas efficiently, it lacks intuition, experience, and contextual understanding – elements that only humans can provide. The best innovation strategies involve a collaborative approach, where AI supports human ideators rather than replacing them.

In this article, we explore how AI-powered ideation techniques are transforming innovation and how businesses can leverage custom AI assistants for different ideation techniques using the right prompts.

The Shift from Brainstorming to AI Storming

A recent study by Wharton professors Christian Terwiesch and Karl Ulrich, featured in the Wall Street Journal, examined whether MBA students or ChatGPT performed better in idea generation. They evaluated both the number and quality of ideas. In both aspects, ChatGPT significantly outperformed the Wharton MBA students.

Traditional brainstorming relies on human input and discussion, often leading to biases, repetition of known ideas, and slow processing of insights. AI storming takes this process further by:

  • Connecting seemingly unrelated ideas – AI can cross-analyze data from multiple sources.
  • Reducing cognitive bias – AI generates ideas based purely on logic and data.
  • Speeding up the process – AI can produce and categorize hundreds of ideas in seconds.

Yet, AI alone cannot evaluate the emotional, ethical, or strategic relevance of ideas. Human judgment is essential to interpret AI outputs and refine them into meaningful innovation. Terwiesch and Ulrich, the researchers mentioned above, also suggest that leveraging human-AI collaboration is a valuable approach worth exploring.

How to Use AI for Ideation Techniques?

We have already written an article describing and comparing different ideation techniques, you can read it here https://www.crowdworx.com/en/blog/comparing-different-innovation-methods-which-one-is-right-for-your-business/. You can familiarize yourself with that article first and then come back and read how AI can enhance couple of the key ideation methods as an example:

1. AI-Enhanced Brainwriting

What it is: Brainwriting is a structured alternative to brainstorming where participants write down ideas instead of discussing them aloud. This minimizes dominant voices in a group and allows everyone’s ideas to be considered equally.

  • How AI helps: AI is a great brainstorming partner, especially when teams run out of ideas. AI tools can suggest prompts, ask follow-up questions, or bring in fresh perspectives. For example, if a company is developing a new smart home gadget, AI could look at market trends and suggest features inspired by other industries, like healthcare or automotive tech. AI can also improve existing ideas by spotting gaps or combining different concepts into something new.
  • Example AI prompt: “Generate 10 variations of this idea based on market trends and customer needs.”

2. AI-Powered SCAMPER Method

What it is: SCAMPER (Substitute, Combine, Adapt, Modify, Put to Another Use, Eliminate, Reverse) is an ideation method that helps innovators systematically rethink existing products or processes by applying different creative perspectives.

  • How AI helps: AI can apply SCAMPER techniques to multiple ideas at once, making it easier to discover new product improvements. AI-powered tools analyze existing solutions and suggest fresh combinations that might not have been considered before. For example, if a company wants to create eco-friendly packaging, AI can suggest using biodegradable materials or repurposing waste from other industries. AI can also take customer feedback and propose small modifications that make a product more appealing. By testing different SCAMPER scenarios quickly, AI helps teams find the best ideas faster and more efficiently.
  • Example AI prompt: “Apply the SCAMPER framework to improve this concept in a competitive market.”

3. AI-Assisted Trend and Market Analysis

What it is: This technique involves analyzing trends, customer feedback, and industry reports to identify new innovation opportunities.

  • How AI helps: AI scans huge amounts of data—patents, research papers, social media, and competitor strategies—to spot trends before they become mainstream. It helps companies see small changes in customer behavior, new technologies, and emerging ideas that might go unnoticed. For example, a company developing a fitness product could use AI to check global fitness trends, patents, and online discussions to predict what features will be popular. AI can also connect different industries, like taking wearable tech ideas from healthcare and applying them to sports gear. This helps businesses stay ahead by aligning their innovations with future market demands.
  • Example AI prompt: “Analyze recent patents and industry reports to find gaps in the market for this product idea.”

4. AI-Driven Reverse Brainstorming

What it is: Instead of generating ideas for solutions, reverse brainstorming focuses on finding ways to create problems or challenges—then reversing those insights into potential solutions.

  • How AI helps: AI can help teams think differently by turning problems on their head. Instead of just coming up with solutions, AI can first generate potential challenges or failure points. Once these risks are identified, AI can suggest ways to fix them. For example, if a company wants to launch a new subscription service, AI can highlight common reasons why users cancel and suggest ways to improve retention. Similarly, AI can run different scenarios to see how an idea might fail in the market and propose adjustments before launching. This approach helps teams build stronger, more resilient ideas from the start.
  • Example AI prompt: “List five ways this product could fail in the market and suggest strategies to prevent them.”

5. AI-Powered Mind Mapping

What it is: Mind mapping is a visual ideation technique that helps teams organize thoughts, ideas, and relationships between different concepts. It allows for a structured way of brainstorming, helping teams see connections they might otherwise miss.

  • How AI helps: AI can enhance mind mapping by suggesting connections between seemingly unrelated ideas, organizing concepts into structured categories, and even predicting which ideas have the highest potential. AI-powered mind mapping tools can analyze vast amounts of information and propose new links based on patterns found in research, customer data, or market trends. For example, if a company is exploring sustainable packaging, AI could suggest connections between biodegradable materials, consumer preferences, and cost-effective production methods that teams might not have immediately considered.
  • Example AI prompt: “Create a mind map connecting sustainability trends with emerging packaging technologies and suggest innovative product ideas.”

How to Conduct an AI-Driven Ideation Strategy

A successful ideation strategy integrates structured ideation methods with AI-powered tools to enhance creativity, efficiency, and decision-making. AI-driven ideation strategies allow businesses to explore vast amounts of data, uncover hidden patterns, and generate fresh perspectives faster than traditional methods. However, human expertise remains critical in shaping, refining, and implementing these ideas effectively.

  1. Define your needs – Choose ideation techniques that align with your innovation goals.
  2. Create custom AI assistants – Using Crowdworx AI Toolbox you can build tailored AI assistants for specific techniques and place them anywhere in the system.
  3. Develop strong prompts – Crafting effective AI prompts is key to maximizing AI’s effectiveness in ideation. You should provide specific instructions and context to guide AI responses.
    • Assign AI a role for better outputs
      • Example: “You are an innovation consultant analyzing market trends.”
      • Example: “You are a product designer improving a sustainable packaging solution.”
    • Be specific
      • Instead of “Give me ideas for a new app,” say:
      • “Suggest 5 AI-powered mobile apps for language learning.”
    • Set constraints
      • Define industry, target audience, or use case to ensure relevant results.
    • Encourage multiple perspectives
      • Ask AI to generate ideas from different viewpoints, such as:
      • User needs
      • Competitor strategies
      • Future trends
    • Make prompts detailed and goal-oriented
      • Example: “Generate 10 alternative product concepts using biodegradable materials and analyze their market potential.”
    • Iterate and refine
      • Adjust prompts based on AI’s responses to make them more specific.
      • Add constraints or clarify goals for better results.
  4. Combine AI with human creativity – Let AI provide inspiration but refine and validate ideas with expert input.

Conclusion

AI is not replacing human creativity – it’s amplifying it. While AI can process data, generate ideas, and identify patterns, it lacks intuition, strategic vision, and ethical judgment. Successful innovation requires a hybrid approach, where AI serves as a powerful ideation assistant while human teams bring depth, insight, and context.

By leveraging AI-powered ideation techniques and smart prompt engineering, businesses can generate, refine, and validate breakthrough ideas faster than ever before.