Several research firms in the artificial intelligence (AI) industry predict that the market will grow at a compound annual growth rate (CAGR) of more than 37% from 2026 to 2031, reaching a size of almost 1.68 trillion dollars by 2030. According to Mordor Intelligence's market research, the market for artificial intelligence will grow from $306.04 billion in 2025 to $434.42 billion in 2026. It is expected to reach USD 2,503.13 billion by 2031 at a 41.95% CAGR. This explosive growth is driven by real business results: as reported in the 2026 AI Adoption & Risk Report from Cyberhaven Labs, 88% of companies now report using AI in at least one business function.
However, despite this widespread adoption, KPMG's Global Tech Report 2026 warns that while 74% of organizations say their AI use cases are delivering business value, only 24% achieve ROI across multiple use cases. According to the same report, only 24% of organizations report being at the highest level of AI maturity today, despite 68% wanting to reach that level by the end of 2026 . This gap between ambition and execution – what KPMG describes as moving from "AI roulette" to disciplined execution – explains why forward-thinking companies are no longer just buying AI tools. They are working with companies that specialize in developing AI agents that can help them go from pilot projects to full-scale autonomous systems.
There are numerous companies around the world that develop AI apps, and it may be difficult to pick the best one from the list of well-known AI platform software brands. Let's take a look at what some of the best AI app development companies have to offer.
Advantages of AI Agents
ROI and lower costs
AI agents can cut labor, training, and operating costs by 15-35% by automating tasks that need to be done repeatedly. They cut down on the need for staff by letting your team focus on more difficult problems. A professional AI agent can start paying off in six to eighteen months.
Getting more done with less work
Different industries' return on investment (ROI) benchmarks show that using AI agents can increase productivity by 20% to 40% and cut down on mistakes in tasks that are done over and over again by 30% to 60%.
Personalized experiences for customers
Generative AI enables agents to give personalized answers. AI agents may look at interaction data to make personalized recommendations and predict potential client behavior.
Better decision-making
AI agents that can make predictions and suggestions can work with both structured and unstructured data. They look through huge databases to find patterns that help businesses make smart choices.
List of Best AI Agent Development Agencies in 2026
Belitsoft
Belitsoft's end-to-end AI agent development services include more than just writing code. Belitsoft is a company that helps you build AI agents. They help you find the best use cases, make simple agents for quick wins, and make agentic platforms for full automation and independence. For example, to help a customer train staff on best practices and reduce high employee turnover, the Belitsoft AI agent development firm created an AI-assisted Chrome plugin for an e-commerce company. Using Microsoft Dynamics 365 Business Central as an example, this product offers in-app help.
They also help you get your data ready, build reliable architectures, train and implement AI agents, test and validate them, add them to your current software systems, and improve performance. Belitsoft's AI agent strategy consultation makes sure that AI automation works with your business goals. Their integration services take care of the technical problems that come up when you try to add agents to your company's infrastructure.
Belitsoft's ongoing development procedures make sure that your AI agents are accurate, safe, and affordable. Because AI agents can change how they interact with you, you can set them up at your own pace. Hire Belitsoft, a skilled AI agent developer, to help your business make more money by increasing sales and lowering costs.
The team is made up of people from different fields, including data scientists, machine learning (ML) and artificial intelligence (AI) experts, and ML engineers. Belitsoft's software developers use AI in their products. They also build the deployment pipeline. UX designers use AI to make experiences that are easy to understand. Full-stack AI engineers do a lot of different things for small businesses and SaaS startups, like writing front-end code and making models.
In the beginning, one or more ML developers quickly build a prototype for them using open APIs and new AI coding methods. This helps companies stay within their budget. Enterprise clients, like Fortune 1000 companies, get bigger cross-functional teams for their AI projects. Belitsoft hires security experts, MLOps engineers to deploy and monitor models, and data engineers to build pipelines and get data ready.
Amazon AI
Amazon SageMaker is one of the AI and ML services that AWS AI, which is based in Seattle, USA, offers. Engineers can create, train, and use machine learning models more quickly and easily utilizing this solution. Clients across a range of industries use AWS AI's AI and ML solutions to automate, enhance, and personalize business processes. By using AI capabilities to craft emails and messages that are specific to the profile and behavior of the prospect, AWS AI users can boost response rates. They are able to develop talking points or sales scripts by examining the service, product, industry, and customer segment.
IBM Watson
With the Watson AI product line, IBM customers can make better choices. IBM offers Watson Studio services to business clients so they can develop and design AI applications. The company's AI apps help with customer service, speed up processes, predict outcomes, and cut costs. Among the case studies IBM presented was the creation of algorithms to predict and prevent sepsis-related mortality based on inpatient clinical data. In time-sensitive situations, such as for urgent medical procedures, these models have shown themselves to be very effective, and prompt assessment of insurance claim data facilitates speedier decision-making.
Deloitte AI
This professional services company helps businesses in many fields, including healthcare, finance, and government, with all aspects of AI strategic planning and development. AI solutions are used by Deloitte AI clients to boost productivity, automate procedures, and make better decisions. Generative AI models simultaneously and continuously detect anomalies, patterns, and discrepancies while conducting a root cause analysis in real-time. This is important for managing risks.
Intel AI
It is the world's top company in AI hardware. It offers a wide range of services and solutions, from cutting-edge AI chips and processors to AI software that helps businesses in healthcare, cybersecurity, financial services, and the automotive industry create and grow AI applications. AI services and products enable the creation of complex AI models and improve machine learning. They also help speed up the processing and automation of real-time data.
Google AI
This part of Google is working on improvements in machine learning, computer vision, and natural language processing. Google Cloud AI, Google Translate, and Google Assistant were all made possible by Google's work on AI research and development. Google Cloud's LLMs and GenAI features are changing the way people order food at fast-food restaurants through drive-thrus. A voice-activated AI assistant takes the place of an employee. It answers common questions and takes voice orders from customers. The AI assistant can quickly place an order and send it to the kitchen because it works with the POS system.
Microsoft
The long-standing collaboration between Microsoft and OpenAI has seen billions of dollars invested. Because of this, Microsoft Azure was the only company that offered OpenAI cloud solutions in 2019. The business uses AI-powered solutions and machine learning models to boost output and productivity in many different fields. Microsoft's Prometheus model includes OpenAI. The company also wants to redesign its Bing search engine, which is also called Copilot, so that it can compete with Google in the search market. Microsoft Bing offers real-time automation solutions and advanced AI assistants to help businesses get the most out of their workflows.
OpenAI
This company made ChatGPT, an AI app that uses large language models (LLMs). OpenAI makes AI tools that make interactions in real time better and make business operations run more smoothly. The company works with Microsoft, which provides secure genAI solutions for a variety of industries, including virtual assistants and advanced automation systems.
Salesforce Einstein
AI-powered customer relationship management (CRM) tools can help businesses give each customer a unique experience. They make use of predictive analytics, automation, and machine learning. Einstein AI's features enable you to do things like predict sales, score leads, and automate processes. Salesforce Einstein AI solutions allow sellers to automatically make sales pitches for each and every lead. The AI algorithms use CRM data to write and send out introductory emails and make phone calls. The assistant bot reviews the customer's most recent CRM data to make or change an email that meets the lead's needs in terms of tone and context.
How Much It Costs to Make a Custom AI Agent
Making a new software product is like making an AI agent. The cost will be determined by your desired level of spending. For a few thousand dollars, a small business can purchase a basic AI agent. Most of the time, big companies spend tens of thousands of dollars to make autonomous multi-agent systems, which are systems in which multiple AI components work together to complete tasks.
What affects the AI agent development cost
The final cost of the agentic AI system depends on how complex it is, how many other software programs it works with, how much data preparation is needed, what compliance standards apply, how much experience the specialists need, and whether or not ongoing support is included.
It takes more work to make things work correctly when you add more separate parts. You need professionals who can handle your company's data, understand coding and math, and ensure that AI agents do what they're supposed to do. It is also crucial to do professional testing with a variety of situations. Formatting and cleaning data often need more money. Building retrieval pipelines with RAG also raises infrastructure costs.
To connect an agent to multiple APIs, CRMs, ERPs, or payment systems, custom connections are needed, and each integration can incur an additional cost. Focusing on business outcomes rather than the guesses of a few consultants makes it easier to start small.
It costs more to hire data scientists, AI engineers, prompt engineers, DevOps experts, and QA experts. More specialists and longer schedules result in higher budgets. Hourly wages differ significantly. In Eastern Europe, the lowest wages are around $40 per hour. In North America, engineers usually charge between $120 and $200 per hour.
If you work in a regulated industry, you need compliance experts to prevent you from having to redo things at the last minute, which can cost a lot of time and money. After the launch, it is advisable to set aside money each month for using the LLM API and cloud hosting.
The type of AI agent determines the cost of creation
Custom AI agents for businesses, both simple and more advanced
The average cost to build a chat assistant or workflow assistant that uses existing LLMs and a few integrations is about $10,000 USD, depending on the size of the project. The project may require user interfaces, ongoing maintenance, and specialized backend development. If you require a bespoke interface or more connections, the cost increases.
AI agents made for certain industries
Agents who use trained models to do certain tasks for your industry may start out making about $20,000 a year. They need more work to integrate, train, and prepare the data. Enterprise AI agent systems with numerous integrations and complicated decision flows cost more. Fully autonomous thinking, planning, and acting agents could cost up to $30,000.
AI systems that have more than one agent
It could cost up to $50,000 USD for solutions that have more than one AI agent working together. The additional coordination logic and infrastructure that supports the project contribute to the budget.
Assessing Engagement Models for AI Agent Developement
If the engagement structure does not fit your needs, the right skills do not matter much. By 2026, three main models will dominate the world of outsourcing.
Dedicated team
For companies that wish to maintain their staff, modify their collaborative style, and gradually develop a data platform, this is the perfect choice. You learn about your data landscape from the inside out. It is common to have to commit to at least six to twelve months.
Project-based (fixed scope)
This is the best option for integration projects that are well-understood, have clear requirements, and have stable specifications. For example, going from ETL on-premises to ELT in the cloud. You receive a set budget and clear deliverables. It requires a significant amount of paperwork upfront; changes to the scope cost a lot.
Fractional support / Staff augmentation
This is best for adding specific skills to existing internal teams, like adding streaming capability to a team that focuses on batch work. You still have full control over management. According to much market research, security and access steps must be cleared, which is necessary for fractional support to work well, so that outside experts can be productive within a week.
