One of the main areas of development of artificial intelligence is the ability to be creative or independently create original content. The possibilities of AI today have advanced so much that it is time to talk about its potential impact on society and the economy.
Author Alexey Sergeev, head of machine learning and artificial intelligence practice at Axenix (ex-Accenture).
The future has arrived.
In January 2023, a part-time Russian State University for the Humanities student defended his thesis. The supervisor approved it, opponents and passed the defense procedure. After receiving a diploma, the lucky man spoke on social networks about how he wrote his scientific work.
They did a great job. But not on the diploma topic but in human cooperation and artificial intelligence. It turned out that the result is the result of the work of ChatGPT, an artificial intelligence-based chatbot from OpenAI. Along the way, it is worth noting the reaction of the university leadership, which did not know how to comment on what happened.
One can argue whether the hero of the scandal is worthy of a diploma of higher education, about the value of a thesis, about the professionalism of teachers and examiners. All this is now to be discussed by officials from teaching and science. Nevertheless, the case at the Russian State Humanitarian University has become a practical example of how generative AI complements a person in solving capacious and complex intellectual problems.
The prominent role of generative AI
Generative artificial intelligence is an AI responsible for creating new original content. It has become a social, not just a technological phenomenon recently. Programs and services were available to users, which began to be used for entertainment and solving practical problems.
The Base10 study, for example, demonstrates that there is already a whole universe of generative AI from more than 300 solutions from various vendors. And this is another argument in favor of the fact that AI will become a new platform for the penetration of IT into our lives. They will play the same role that clouds, social networks, and mobile devices previously performed.
Perhaps the best illustration of generative AI’s potential is its design use. The traditional task of a designer is to create unique images to the specifications required for a large-scale media company.
And, the more such specifications and widely used visual tools in a business, the more designers are required for such work. Generative AI partly solves this problem: artificial intelligence can push designers to generate image variants on a given topic.
However, there remains a need for a designer as an expert, able to choose from options based on taste and an idea of what is good/exciting/witty or mediocre/second-rate.
Changing ideas about creative and intellectual work is only one side of the development of generative AI. It enables companies to transform their business models.
An example is the automation of document requests, which, based on generative AI, was added to the product line by Secureframe. This saves customers the time it takes to complete paperwork when selling complex items such as real estate or company stocks.
The generative AI market on the hype
If we talk about the generative AI market in terms of Gartner, then today, it is at the “hype peak” stage. In the text solutions segment, investments in technology increased by 630%, in imaging solutions by 400%, in data tools by 370%, and in audio-video by 350%.
It can be assumed that the market for generative AI is approaching the “productivity plateau” – the phase of maturity and flourishing of the technology. This is the period when the changes technology brings take on the significance of a revolutionary platform shift across the entire market.
The favorable outlook for generative AI is also based on expectations for startups that develop technologies. Their activity, which is already noticeable today, can make the next five years the heyday of artificial intelligence.
Many companies can use AI in development without investing heavily in software, hardware, and complex model development. We observed the same processes recently when public clouds became the primary development trend.
Initial costs can be minimized through access to private APIs and open-source models, as was the case with the speed of development during the heyday of the cloud.
Future AI landscape
Today, the global market for AI solutions is $135.6 billion. By 2030, it will grow at an average rate of 37.7% annually.
The future of the generative artificial intelligence segment will be primarily determined by how unique technologies will turn into a commodity with understandable and standard characteristics (item). That is, high-quality AI models apply to solving specific practical problems.
Their construction requires the involvement of technical talents, researchers, and data scientists, which will impact the education field. Large datasets themselves are also needed, which will encourage companies and industries to find ways to connect, share, and securely exchange data.
These areas will benefit from pioneering AI adoption companies. They will form a pool of AI tools for businesses and users. By analogy with the public cloud market, their share in the AI solutions market will reach 65-70%.
Today, OpenAI, Stability AI, and Hugging Face have taken advantage of early promotion. However, the story is just beginning, and in the coming years, we will see a struggle between closed-source players and open-source companies.
In the context of the future landscape, it must be said that giant language models like ChatGPT and Midjourney are being created by teams with a clear focus on fundamental research in AI with significant investments.
It is unlikely that an ordinary company in the market can afford an R&D staff of tens and hundreds of first-class Data Science specialists aimed only at experiments whose commercial value is not so straightforward and obvious.
Most likely, shortly, the creation of such models will be the lot of prominent players around whose decisions derivative products and services will be formed.
AI dominance = machine + human
The confused reaction of RSUH scientists to the news about the use of AI in preparing a diploma shows that not only the artificial intelligence industry itself is at the very beginning of technological development, but potential use cases and associated risks are being discussed among the expert community.
In “creative” business areas such as marketing and commercial copywriting, generative AI is currently seen as an area of experimentation.
Trying the technology in action takes time to find cases with high commercial efficiency. However, with the growth of the economy and the accumulation of experience in the use of generative AI, there will be new opportunities for significantly expanding the scope of its application.
And contrary to widespread fear, the development of generative AI will rather lead to the expansion and transformation of the labor market and the formation of new professions and entire professional segments.