AI Transformation

‍Generative AI is changing the way we work. Not just as individuals. It changes the way entire organizations work. Increases efficiency, enables faster innovation and provides new opportunities. Ignoring these changes means losing competitiveness.

According to scientific studies At Boston Consulting Group consultants, the use of generative AI increased the quality of the outputs by 40%, the speed by 26% and the total amount of work by 15%.

When steam engines were introduced into factories, one such steam engine increased the productivity of the factory by an average of 18 to 22 percent.

This means that generative AI is bringing about a revolution comparable to historical technological breakthroughs.

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Where generative AI helps the most

Each of us has a huge number of individual competencies that we use in our daily work. Take car driving, for example — this consists of approximately 27 different competencies from turning the steering wheel at the right moment and shifting gears to knowing that when red at a traffic light is standing. Each of us has competencies a little differently. For example, people with automatic transmission have trouble shifting gears.

Artificial intelligence has a range of competencies around the 80th percentile. This means that 80% of people are worse or equal to AI in that particular competence.

It's not in all competencies equally. In addition, everyone has microcompetencies a little differently. Therefore, generative AI is most effective in areas where individuals have the least competence.

For example, if you've been writing blogs and newsletters for 20 years, AI may not help you as much as someone who is just starting out with writing. It will not help the doctor to operate better on the patient, the doctor will help with empathy.

AI will help you and your organization the most in those competencies that you have the worst.

Not in the ones you have the best.

Focus on those things you're not good at.

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Three key areas for using AI

Generative AI can be divided into three key areas: models, tools, and scenarios.

1. Models: Models are the basis of modern AI applications and tools. You know them under names like GPT4o, Gemini 1.5 Pro and Claude 3.5 Sonnet. Our recommendation is simple. Always use the latest models. Either directly or through tools.
2. Tools: Apps built above models. There are a huge number of them, and they are increasing exponentially. Do not weigh yourself for a long time ahead on a particular tool. Maybe next week another one will come out, an order of magnitude better. Pay monthly fees, not yearly.
3. Scenarios: Situations where AI tools and models save you time, money, or allow you to do things you couldn't do without them. You need to map scenarios on an ongoing basis at the individual level.

The role of the Chief AI Officer (CAIO) in the organization

The Chief AI Officer is in charge of integrating AI into the organization. Thus, it helps first itself and then the organization to introduce generative AI tools built on the latest models into scenarios.

This includes testing and deploying tools, finding new uses for AI, and crafting strategy.

There are four levels of CAIO maturity in AI deployment:

1. Explorer: Experimenting with AI and looking for possibilities of exploitation.
2. Ambassador: Helps others in the organization see the value of AI.
3. Admin: Systematizes the use of AI, introduces procedures and tools.
4. Transformer: Automates parts of the organization and introduces an AI-first approach.

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The impact of AI on organizations and their future

Generative AI is a powerful tool that transforms organizations. The Chef AI Officer plays a key role in integrating these technologies into daily operations.

If you're Level 1 (Explorer), invest at least 10 hours experimenting with AI tools and models. Sit down and brush it up. If you are at level 2 (Ambassador), force your colleagues to experiment with the AI for 10 hours.

Only then start figuring out what everything is interesting to do within generative AI. And how do you use it to transform your work.

You have to experiment. You don't need to experiment randomly. You need a role, procedures, and relevant stimuli. There are too many tools. It doesn't make sense to try everything. From this there is AI University.

Bring AI into your organisation

No one will tell you in advance if and how the AI will help you. No one knows in advance. You have to experiment. Don't waste time researching AI options and implement the most effective tools right away. That's what AI University is for.

I'm interested

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CAIO Webinar: Chief AI Officer

You can find the full recording of the webinar at It's teachable.

Registration to watch is free.

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