What blockchain developers can learn from AI

When it comes to usability, there is a gap between AI and blockchain technologies. Eduard Muzhevskyi—Science Photo Library via Getty Images

As soon as the word “blockchain” is uttered, speculation about cryptocurrency prices appears. In contrast, the first thoughts about artificial intelligence revolve around what users are already doing with it.

The stark difference alone is enough to make many blockchain enthusiasts, like myself, incredibly jealous.

Given that the use of AI is off to such an impressive start, what can blockchain learn from AI?

To answer that question, let’s look at the similarities and differences between the two sectors.

First, a quick summary of the parallels between their developments.

Both AI and the blockchain have brought transformative advances in technology and gained significant market attention.

With the blockchain, the fundamental innovation was seamless peer-to-peer transfer of digital assets, independent of intermediaries. With AI, machine learning and its language are central elements revolutionizing the use of knowledge everywhere.

With so many conceivable use cases, these two technologies have piqued the interest of millions. Both industries are rapidly growing, with the potential to create millions of jobs as thousands of new businesses have already attracted billions of dollars in investment.

Over the past decade, both technologies have significantly matured and evolved, offering equal potential to reach billions of people. But the similarities end there.

AI has done much better in terms of market introduction and user adoption.

AI’s consumer experience is more elegant, but also simpler. For example, OpenAI’s ChatGPT has spawned the creation of dozens of applications for all possible sectors. A user does not need to download anything or have specialized knowledge of machine learning or natural language processing. Often, users can try a new product without even formally registering.

AI technology has done an excellent job of appealing to developers who want to inject their applications with the power. The APIs offered are generally easy to understand and functional, from start to finish. Notables from OpenAI, Google, Microsoft’s Azure Cognitive Services and AWS are just a few examples. In contrast, blockchain developers are confronted with a patchwork of technical resources.

Under the hood, AI is quite complex, but as developers sifted through technical jargon – Deep Learning (DL), Large Language Models (LLM), Natural Language Processing (NLP), Machine Learning Languages ​​(MLL) – end users were asked to do it. The blockchain sector, on the other hand, remains dominated by technical discussions that leave many potential participants grasping for clarification rather than simply experiencing the technology.

AI refrained from overhyping itself too soon, allowing plenty of time for development and refinement over the last decade, before it was ready for prime time. During that gestation period, developers dedicated themselves to fine-tuning the technology, tackling intricate challenges, and only now are we witnessing the true impact of AI on the average consumer.

In contrast, the blockchain industry continues to reveal its fixation to the public, resulting in a huge gap between hype and reality. Several participants in this industry continue to promote unproven products or exaggerated business models, exposing their experimental ventures to public scrutiny and inviting criticism or skepticism. Some examples include the increased expectations around DAOs or GameFi that were supposed to revolutionize gaming.

With a combination of practical, realistic and compelling use cases, AI has now entered various sectors and segments one by one. Artificial intelligence is already becoming verticalized and specialized, while blockchain’s ambitions to permeate industry remain a work in progress. Although blockchain’s impact has primarily been felt in finance, most other attacks in various sectors have been weak or hopeful at best.

There is much that the blockchain community can gain from the success of AI. I hope the upcoming generation of blockchain entrepreneurs will not only take inspiration from their predecessors, but also look to their peers in the AI ​​field for valuable insight and guidance. The lessons are there for the taking.

William Mougayar has four decades of technical industry experience and is the author of Business Blockchain. The opinions expressed in Fortune.com comments are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.