Is the gold-rush mood in AI over?

Are you also excited to see what happens with AI? AI technologies took off last year. With the opening of ChatGPT, we all suddenly saw what generative language models can do. Abstract artificial intelligence suddenly got a face and became approachable. AI is now omnipresent. In writing, in images, in programming. But also in music, videos and web design. There is no service or product that doesn’t have a little AI in it.

Many people are already feeling oversaturated and want a simpler world back. For many, AI is also a cost factor. Every tool costs money, and familiar tools suddenly become more expensive with AI. We also tend to neglect the fact that AI, like cryptocurrencies, is driving our global energy consumption to unimagined heights. This enormous computing power that is needed competes with our efforts to limit CO2 production and save energy.

So what should and will happen next with AI?

A simple model: the product life cycle

Let’s first try to place AI technologies in their life cycle. In order to understand the various phases that a product goes through from its introduction to its decline, the product life cycle model has proven its worth. The model distinguishes between 4 or 5 phases. The maturity phase is sometimes combined with the saturation phase.

1. Introduction phase: In this phase, the product is launched on the market. It can take a while to establish itself on the public market and sales are often low.
2. Growth phase: As soon as the product is accepted, it experiences rapid growth. Sales figures rise sharply and the product begins to make a profit.
3. Maturity phase: In this phase, sales reach their peak. The product has established itself on the market and competition is increasing.
4. Saturation phase: Here the product encounters a lot of competition and price pressure. Demand for the product may decrease and it may become part of people’s everyday lives.
5. Decline / degeneration phase: In this phase, sales decline and the product could be withdrawn from the market, often due to outdated functions or better competition.

So how can we locate AI technologies in this product cycle?

Still growing?

It took quite a long time for AI applications to reach the wider market. But then it took off like a rocket. In the past year, the topic of AI has occupied us like no other technology topic has for a long time. There is hardly an area of life in which AI is not present.

Today – a year after its brilliant launch – it is difficult to determine the exact stage of AI technology in the product lifecycle, as AI may be at different stages in different areas. Some aspects of AI, such as machine learning and data analytics, are widely adopted and may be at the maturity or even saturation stage. Other aspects, such as advanced autonomous systems, could still be in the introduction or growth phase. Overall, however, AI technology remains a rapidly evolving field with significant potential for future growth and innovation.

… or is the market already saturated?

However, there are also some aspects that suggest to me that the peak of AI technologies has perhaps already been reached or even passed:

• Increased competition: There are too many companies and start-ups developing and implementing AI technologies. The market is saturated. There will be consolidation and displacement.
• Price pressure: Increasing competition could lead to price pressure as companies try to offer their products at competitive prices. Only offerings with a solid business model will survive.
• Shift from freemium to premium: Products that were previously free of charge are now subject to a charge. Although this is a solid business model, it may not be appreciated by customers. And it won’t work without customers.
• Integration into our everyday lives: AI technologies are increasingly becoming part of our daily lives, from voice assistants to recommendation systems in online stores. Small, innovative solutions will disappear. The large providers have it easier here due to their market power. But they also have to deliver quality. Customers are now used to innovative concepts and expect the same in their everyday products.

And what about the continuing education market? I sensed a gold-rush atmosphere last year. The need for further training was great, and technological progress was too fast for many. To exaggerate a little: anyone who had ever successfully prompted could immediately sell their knowledge as a coach.

I think those days are over. For me at least, the prompting templates and AI course offerings on LinkedIn are quite annoying. I am also skeptical about the development that someone who has once successfully prompted an image generation in Midjourney becomes a coach. Analogy: Just because I’m good at cooking doesn’t make me a coach for trainee chefs. Gone are the many training courses that only focus on learning about different AI technologies. What is needed today is specific application knowledge in the context of everyday life.

Maturity is good

A constant evolution begins with maturity. No more hype tools, super bargains and unrealistic market promises. We are now in the phase in which the wheat is separated from the chaff. Many offerings and tools that have sprung up quickly will disappear as users now have more skills. They can prompt themselves, have had their own experience with AI models and can set up more complex workflows. They no longer need the “entry-level offers” that were often promised at unrealistic prices during the growth phase in order to keep the hurdle to the new technology low.

What’s more, many AI applications are now integrated into the tools we already use on a daily basis. Users are therefore happy to fall back on their usual tools and no longer need the “promising” special tools.

Now comes the important and good ideas that are driving the AI world forward.

How do you see the development of AI technologies? Are we still in the growth phase or have we already reached a saturation phase? Please leave us a comment!