Artificial intelligence is often called the technology of the decade, and rightly so. 77% of businesses worldwide are already using, actively exploring, or even investing in AI tools. 

The results of the AI boom are tremendous. On average, a company saves 22% on process costs and receives an 80% productivity boost after implementing AI into workflow. However, the future capabilities of artificial intelligence are even more overwhelming. 

The market size of AI-powered tools is expected to show an annual growth rate of 27.67%. This is an insane number, because the average market growth rate is about 4%. It means that artificial intelligence is developing so fast that its global volume may triple and reach about $826.70 billion in the next five years.

I’ve analyzed the market and am ready to share the most promising and ambitious trends in AI development and how they will impact the global market and business processes in small, mid-sized, and large enterprises.

Brief History of Generative AI

But first, we turn to the history of generative AI in the modern world. While most of the technologies used to develop and teach neural networks have been known for decades, AI assistants and chatbots have been common since Siri's creation. Why have they become so popular now?

The first functional multilayered artificial neural network was developed in 1975—yeah, fifty years ago. This neural network was able to recognize visual shapes, such as handwritten characters or geometrical figures. Moreover, it could be trained by specific databases to track certain conditions and patterns. 

You may wonder why AI-powered started snowballing just recently, when we had all the necessary algorithms fifty years ago. The answer is trivial: The previous generations of AI technologies were vastly ahead of their time. 

In the 80’s, computer scientists didn’t have enough computing power to operate and teach neural networks. 

For comparison, the supercomputer Cray-1, created in 1975, was one of the top computing machines of its time with a stunning 160 MFLOPS processing performance. Contemporary computers could boast no more than 0.3 MFLOPS. 

Now, a single processor in an average iPhone 15 has 1789.4 GFLOPS of computing power, which is about 11,000 times more than the exclusive supercomputer of fifty years ago. 

The 1990s and 2000s are considered the great winter for AI development because data scientists had everything except computing power to develop the technology. That’s why most of them switched to more achievable goals and projects. 

The renaissance of AI began in 2011. Apple developed Siri, the first digital virtual assistant, and implemented the technology into the iPhone 4S. The world went mad. Ordinary people realized AI was not the fairy tale of science fiction, but the real thing. 

Three years later, the first generative adversarial network was developed. It was able to create near-realistic images, videos, and audio. Businesses noticed it, but very few tried to adopt and implement generative neural networks into their workflows. 

Everything changed after OpenAI’s ChatGPT 3 was announced in 2022. Frankly speaking, it was almost the same generative neural network, but it was carefully trained using a massive amount of data. The true age of AI had begun. 

Open API can be integrated almost everywhere: CRM systems, operating platforms, document management systems, project management tools, risk management applications, learning and development platforms, and many other business projects. 

Techstack’s expertise in OpenAI API integration is matched only by our breadth of industry knowledge. Our team of AI specialists brings a wealth of cross-domain experience, ensuring your integration leverages best practices from multiple sectors.

To solve the most critical business needs and tasks, we harness the full spectrum of OpenAI's powerful models to deliver unparalleled AI solutions for your company. 

The artificial intelligence market is growing like crazy, and the latest technologies in AI development are being created every week, so it’s a bit hard to keep an eye on them. We’ve done it for you. 

Techstack’s experts have analyzed dozens of current trends in AI development and picked the most promising ones that will likely shape the next five years of neural network evolution. 

Autonomous AI agents will become much more common

In 2020, about 24% of businesses worldwide have tried using neural networks to improve product and service development processes. Still, the adoption of AI in other branches was relatively low: 15% for manufacturing goods, 10% for human resources operations, 9% for logistics, and 8% for strategic management and finances. 

Now, the latest trends in AI development are being hyped. Businesses try to implement innovative AI-powered tools because they’re cool and cheap. Moreover, companies can delegate routine, repetitive, or simple tasks to neural networks. 

For example, autonomous AI agents have already achieved 90% accuracy in identifying early-stage diseases, including various cancers, fractures, and neurological disorders. The automatic analysis process takes only 0.24 seconds for a single MRI scan. 

AI autonomous tools are actively tested in US, UK, and EU healthcare. For example, Techstack’s team helped to improve an AI-powered virtual assistant for a US healthcare provider, focusing on cancer risk assessment. This innovative solution combines a relatively new technology in AI development (Open AI API) and advanced language models with specialized medical knowledge to provide personalized risk evaluations for patients. 

Our team was responsible for integrating OpenAI's cutting-edge technology, specifically their ChatGPT model, known for its advanced natural language processing capabilities, and improving the virtual assistant developed by our client's in-house development team. 

41% of businesses predict that up to half of their core business processes will run on AI agents by 2025, and over half of companies will deploy AI agents into their workflows by 2027. 

However, businesses must prepare more for agentic AI integration in the global market because effective implementation requires significant changes in foundational infrastructure and data management practices.

In the next five years, we’ll see a smooth transition from using AI in every possible business process to carefully implementing autonomous AI agents into the fundamental infrastructure of large businesses. In 12 years, the entire industry is predicted to grow a hundred times, from $7.84 billion in 2024 to $783.27 billion in 2037.

Generative AI will be everywhere

By 2026, 75% of businesses will use generative AI to create synthetic customer data, up from less than 5% in 2023. Moreover, over 40% of generative AI solutions will become multimodal, capable of creating text, images, audio, and video. 

Human-like communication is highly demanded in AI development. According to Statista, over 60% of customers in the 25-34 age group are more likely to use chatbots when visiting brand websites than wait for a real sales manager to respond.

Chatting with a bot is already perceived as typical for customers. Chatbots can quickly gather data from potential clients, answer typical and dumb questions, help select goods and services, etc. 

Businesses are actively testing generative AI solutions based on natural language processing neural networks. It reveals a broader AI development trends: creating separate software for communication with the target audience, not just an add-on for a website. 

It will open a new era of customer communication, not only with text but also with images, audio, and video. Moreover, in a few years, we can see a real boom in various robotic systems using generative AI for communication, even for offline applications. 

Moreover, generative AI solutions can be responsible not only for communication, but also for simulating environments and identifying new opportunities to develop the product and better meet consumers' requirements. That’s why many businesses are going to focus on using synthetic data in areas close to the customer journey to create a unique experience for each client on both the product and service sides. 

AI models will become commodities 

The artificial intelligence market is highly competitive. As of 2024, over 70,000 companies are developing AI-powered tools and solutions for businesses and ordinary users, and there will be more. 

That’s why the most promising AI-powered tools should be utterly customizable to meet business goals and expectations. It’s easier to perform when a product is created not as a platform, but as a full-fledged solution. 

Benedict Evans, an independent analyst and author of an independent newsletter with 175,000 subscribers, compared the current development of AI tools with the global rise of computer technologies in the 1980s and 1990s. Modern developers are focused on incremental improvements in AI specs—just like they were with CPU memory and speed. That’s why we expect AI models to become more interchangeable and multipurpose. 

Now, companies developing AI tools are competing for better performance because a cap of neural network possibilities has yet to be reached. But when it’s close, the primary benchmark will be the products’ usability, customizability, and security. AI companies will develop separate artificial intelligence products into full-fledged ecosystems that can simultaneously fulfill all business needs.

The rise of artificial emotional intelligence

Modern AI systems can analyze users’ facial expressions, gestures, tone of voice, and other factors through computer vision, sensors, cameras, tons of real-world data, speech science, and deep learning algorithms. This helps neural networks identify human emotions and decide how to react to them accurately. It’s similar to how the human brain determines other people's feelings.

Emotional AI is widely deployed in customer services. 84% of call centers in the US use AI tools to analyze customers’ tone of voice and emotional components when speaking with hotline managers. 

Half of consumers believe AI has already improved customer service, but most (79%) still believe human managers are essential.

However, the actual scope of artificial emotional intelligence solutions is much broader than customer services. AEI can be helpful in healthcare, education, banking, media, government, insurance, automotive, and other areas. 

For example, artificial emotional intelligence programs in schools can reduce disciplinary incidents by 30% and improve academic performance by 20%. Moreover, AEI tools can help prevent bullying and even suicide attempts by carefully measuring and analyzing each student's mood dynamic. 

However, AEI tools are still underdeveloped. The main issue is people's privacy. A neural network needs to analyze the facial expressions of real humans, which is almost impossible—GDPR and other laws protecting personal data forbid such image usage. But when this issue is solved, we’ll witness the great rise of emotional artificial intelligence solutions. 

The regulatory environment will become stricter and more comprehensive

Legislation governing artificial intelligence is still fragmented and incomplete. The first legal framework regulating AI development and utilization was created just recently, in 2023. The “EU AI Act” is the fundamental statutory instrument to provide safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems in the European Union. 

Other countries are also actively working to regulate and control the rapid development of AI. In September 2024, Australia adopted a Voluntary AI Safety Standard comprising rules and guidances for AI system creation and usage. The Australian parliament also considers mandatory policies regarding AI in high-risk projects. 

In some cases, legislative control is primarily focused on generative AI systems. For example, China’s government passed the Interim Administrative Measures for Generative Artificial Intelligence Services. This law limits the development of generative AI but doesn’t affect neural network usage in data analysis.

Some international organizations also increased their interest in regulating AI development and usage. Initiatives from the United Nations Educational, Scientific and Cultural Organization (UNESCO), the International Organization for Standardization (ISO), the Group of Seven (G7), and others exist. However, these initiatives are just consultations and discussions. 

Surprisingly, in the US, one of the global leaders in AI development, neural network creation, teaching, and usage are not controlled or limited by law. Moreover, American lawmakers don’t even discuss them. There are serious risks that the lack of control and accountability will lead to significant safety issues even at the governmental level. Creating controversial fake videos with public statements from governors, ministers, and even presidents is as easy as pie. 

What’s more disgusting, AI can be used to create non-consensual porn with a victim’s face. In January 2025, there was a loud scandal about making fake AI sexual images with underage high schoolers. Scammers blackmailed young girls and even printed fake photos to distribute. 

Such situations pressure the authorities to create a safe environment, preventing the undignified utilization of AI tools. However, a critical point is still far away—prioritizing the topic on the international level will take a few years. The main question is when the required legislation will be created: before or after some scandalous disaster. 

The regulation may be flexible. For example, AI applications can be tiered by the risks of illegal usage. Low-risk applications can go to market faster, but high-risk ones need proper protection and control. 

Creating a cohesive global standard for AI applications is essential. Experts reckon we will witness the first steps to this in the next five years. 

Riding the Crests of AI Development 

AI is no longer a hyped trend; trending technologies in AI development will shape the future of many industries and infrastructures. Frankly speaking, it’s a game changer for global business. That’s why AI-driven tools are skyrocketing now. 

Making precise predictions is hard because AI's peak point is not yet reached. But it’s close. The development of AI applications in the next five years will form the global business for decades. And then we’ll see how promising or terrifying they will turn out to be. 

So, don’t wait for someone else to make an AI impact, let’s make it together.