AI can be considered a true partner in innovation, but it is also a tool that enhances human creativity. Here could be some reasons:

AI as a true partner:

• Augmented intelligence: AI can augment human intelligence by providing new insights and perspectives that humans may not have considered.
• Accelerated innovation: AI can speed up the innovation process by automating tasks and generating new ideas.
• Collaborative problem-solving: AI can work alongside humans to solve complex problems that would be difficult or impossible for humans to solve alone.

AI as a tool that enhances human creativity:

• Inspiration: AI can generate new ideas and concepts that can inspire human creativity.
• Experimentation: AI can help humans experiment with new ideas and approaches without the risk of failure.
• Visualization: AI can help humans visualize complex data and concepts, making it easier to understand and interpret.

Ultimately, the role of AI in innovation will depend on how humans choose to use it. If humans use AI as a tool to enhance their own creativity and problem-solving skills, then AI can be a true partner in innovation. However, if humans become overly reliant on AI, then AI may eventually become a hindrance to innovation.

Here are some additional thoughts on the role of AI in innovation:

• The importance of human values: AI should be used to amplify human values, not to replace them. AI should be designed and used in a way that promotes human well-being and sustainability.
• The need for ethical AI: AI should be developed and used in an ethical manner. This means that AI should be transparent, accountable, and fair.
• The importance of human-AI collaboration: AI should be used in collaboration with humans, not in competition with them. Humans and AI should work together to achieve their shared goals.

By keeping these things in mind, we can ensure that AI is used to its full potential as a tool for innovation and creativity.

Thank you.

You haven't only to look at the performances KPI otherwise humans will love... drop in also soft-skills or parameters where AI unfits.

https://github.com/qompassai/Nautilus/tree/main/RedTeam/RedAI/NIST/Qompass_Dioptra

https://github.com/qompassai/Nautilus/blob/main/RedTeam/RedAI/NIST/AI_RMF_Playbook.pdf

NIST Dioptra and their Risk Management Framework (RMF) are what I'd recommend as the first stop for production/enterprise assessment before going after ROIs and KPIs. Organizations that don't appreciate where the regulatory thresholds are for their AI use-cases, particularly if they're incorporating dual-use foundation models in domains that fall within the purview of federal agencies (health, finance, education), are cruising for a bruising.