We tell you how artificial intelligence will develop in 2025
AI continues to change the familiar landscape of technology and business. We figure out what AI Development Company can do today and what trends in the development of artificial intelligence should be expected in the coming years, together with,Data Scientist at Sparkout.
AI and programming
Artificial intelligence continues to transform programming. According to Stack Overflow, nearly 62% of programmers use AI in their work, and another 13.8% plan to start using it. AI tools like ChatGPT and GitHub Copilot are already helping developers write code faster, find errors, and automatically generate solutions.
Here's what those IT specialists who are already actively implementing it in their work use AI for:
Writing code - 82%; Finding answers - 67.5%; Fixing errors - 56.7%; Documenting code - 40.1%; Synthesizing data - 34.8%; Testing code - 27.1%. Source
AI is actively used in DevOps : it automatically deploys applications, monitors their status, and helps avoid failures. This frees programmers from routine tasks and allows them to focus on more important tasks.
According to G2, AI-powered code generation will be one of the most in-demand technologies in programming by 2025 .
Development of Generative AI
Generative AI is a technology that can create new content based on the analysis of large amounts of data. This could be text, images, music, video, or even complex programs.
Many experts predict that generative AI will be used everywhere: in advertising and marketing, the IT sector and the media market. For now, it will not replace designers, actors, writers or programmers: AI still makes many mistakes due to lack of knowledge. But given how much artificial intelligence makes content production cheaper and faster, investors will be interested in supporting this industry further. This means that in the future, it will be increasingly difficult for us to distinguish generated content from real content.
AI-powered decision making
Last year, 32% of IT professionals surveyed said AI was only good at relatively simple tasks. Developers are trying to solve this problem with agent-based AI.
Agent AI is smart programs that can operate with little or no human intervention. They don’t just answer questions like chatbots, but take on complex tasks. An agent can create a schedule, send the right emails, or analyze data to help make decisions. But for us to trust these systems, it’s important that they work reliably and don’t make mistakes. This is where the AI TRiSM (AI Trust, Risk, and Security Management) approach comes in. It helps track how and why AI makes certain decisions, and also identifies errors and biases in databases.
Deloitte predicts that by the end of 2025, 25% of companies using generative AI will be deploying AI agents, and this figure will grow to 50% by 2027.
AI and new vacancies
Although generative neural networks create some tension in the labor market, they still cannot completely replace humans.
The market is already reacting to this trend: many recruiters include the ability to work with neural networks in their candidate requirements. In addition, in recent years, more and more new vacancies for working with artificial intelligence have appeared. Here are some of the most popular:
A Prompt Engineer is a person who understands how to “talk” to AI in order to get the most accurate and useful answers from it. Their job is to formulate requests so that the AI understands what exactly is wanted from it and gives the desired result. For example, a company needs an image to advertise a new product. The Prompt Engineer creates a request and describes the style, color scheme, and composition of the image, and specifies what impression it should make on the client.
An AI trainer helps train artificial intelligence models. They analyze the interaction of the neural network with users, correct shortcomings, and add missing data. For example, a trainer can teach a chatbot to correctly process rare requests or suggest how to respond to non-standard questions.
An AI Ethics Specialist develops rules and standards for the safe and fair use of neural networks. For example, such a specialist can check that the algorithm for selecting candidates for vacancies is not biased.
An AI Development Services Architect is a person who develops and implements AI systems into a company’s processes. Their job is to configure AI so that it effectively solves business problems and optimizes employee performance.
The Chief AI Officer is a top manager who is responsible for the implementation of AI development company strategies. His task is to determine how the neural network can help the company grow, what technologies should be used, and how to allocate resources.
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