Generative AI might be the biggest tech revolution since the Internet itself. But just like when many other technologies are popularised, there are many insecurities, misunderstanding and skepticism when it comes to the use, and potential use of AI. One of them being that you need to be a technologist to innovate with AI. You don’t!

The tech job has already been done for you – that’s the beauty of it! You just need to understand how to make it work for you to create the solution you want. Here’s how:

They bridge the gap between technologists, designers, and other stakeholders, enabling effective communication with generative AI systems. Our experience underscores that 80% of a successful AI project lies in carefully crafting and orchestrating prompts. Meticulous prompt engineering directly influences the quality of the output; invest in understanding the nuances of prompting, and you've already paved the way to exceptional results.

1. Prompts are the language of AI collaboration

Unlock the power of AI – prompt engineering is for everyone!

Prompts are the language of AI collaboration

 are powerful, but your project's success depends on finding the right AI solution for your specific needs. ChatGPT (or GPT-4-turbo) may excel in many areas, but consider alternatives like 

 if Norwegian language output is crucial. For image generation with text, 

 might be a better choice than Dall-E. And, don't overlook the cost-effective benefits of 

 if you don't require the full power of GPT-4-turbo. Remember, the world of AI evolves rapidly. The best models for specific tasks today will be surpassed by new developments. Stay curious, explore new advancements, and don't be afraid to let your project take unexpected but inspiring turns!

2. Explore the power of AI alternatives

AI's rapid evolution demands adaptability. Don't invest heavily in complex, customised solutions early on; they may quickly become outdated or available as off-the-shelf products you can purchase more cheaply. With AI research moving so quickly, tomorrow's solutions might solve today's problems in a flash. Prioritise essential functionality and design for easy updates as language models advance. Avoid reinventing the wheel – solutions from OpenAI, Apple, and others may soon address the specific problems you're trying to tackle. Unless the journey of building it yourself is the reward.

3. Start small, keep it simple 

Including your own text, images, or documents in prompts is a quick way to personalise AI responses. However, remember that AI models have a "context window" – a limit to how much information they can process at once. Avoid overwhelming it with the complete works of Shakespeare! Need more capacity? Try the 

. Create a GPT Assistant in the OpenAI web UI to upload documents and other data. This provides more storage and a wider context window for the AI to draw from, unlocking enhanced personalisation.

4. Harness your data for custom AI experiences 

Hitting the context limit? Explore GPT Assistant or RAG for more robust AI solutions.

Harness your data for custom AI experiences

, be proud that you're using AI in new and innovative ways. Let your users know when they're interacting with AI-generated content. This fosters responsible AI use, promotes open communication, and aligns with fundamental human rights principles like fairness and non-discrimination. AI is a powerful tool, but it shouldn't be used to judge people – human oversight remains crucial.

5. Be transparent

Respect privacy laws and regulations, including GDPR. While sensitive data might not be ideal for cloud-based AI services, explore open datasets or AI-generated synthetic data for experimentation. For maximum security and control over sensitive information, consider open-source language models like LLaMA for on-device processing. Powerful handheld devices with neural engines like the just announced iPad Pro's M4 chip are opening up new possibilities for local AI processing.

6. Be mindful with privacy and data protection

Summing up – to get started using artificial intelligence to create new solutions doesn’t need to be complicated. Think simple, focus on gathering good quality input and be clear with what the purpose is. Let technology solve the rest.

You don’t have to be a technologist to become a generative AI expert