Cracking the Code of Generative AI: Separating Hype from the Game-Changing Reality

We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.

We could be mistaken to think that this quote is about Generative AI, but it was coined in the 1960s by Roy Amara who was an American scientist and futurist.

Is Generative AI in a massive hype cycle? Maybe.

But it would probably make more sense to think about Generative AI as a tool for a new type of workforce productivity and business models, rather than just a technology:

1. Economic Value: McKinsey estimates generative AI could add $2.6tn to $4.4tn annually across various industries.

User Growth: Chat GPT, a prime example, reached 1 billion users, showcasing the technology’s mass appeal.

2. Impact on Work: Generative AI differs from previous AI generations, offering unique applications in error elimination, minimizing variance, improving productivity, and achieving breakthroughs.

3. Humans in the loop: Human competencies are required to define and manage Gen AI output including “hallucinations”.

4. Democratizing Knowledge: Generative AI lowers skill premiums, boosting productivity in areas like copywriting and call center operations, even for less experienced talent.

5. Reducing Inequality: By increasing the productivity of lesser-skilled talent, generative AI could reduce inequality, reminiscent of the second industrial revolution’s automation effects.

Generative AI is not just about technology; it’s about thoughtful and nuanced reinvention of business models and workforces.

What are your thoughts about the hype that surrounds Gen AI?

#GenerativeAI #BusinessModel #HypeCycle

Data: Forbes / Reinventing Jobs / Ravin Jesuthasan

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