Alexandria - Apr 8, 2026 - Belitsoft, an international AI automation consulting and software development company, today released its AI Agent Development Forecast 2026, analyzing market data, adoption trends, and technical shifts in agentic AI. The forecast finds that agentic AI has become the fastest-growing enterprise technology priority, rising from 13.0% to 17.1% as a top-ranked priority – a 31.5% year-over-year increase.

Market Growth

In 2025, the market for AI agents was worth $8.03 billion. By 2026, it is expected to be worth $11.78 billion, with a compound annual growth rate of 46.61%. Long-term forecasts say that the total will be $251.38 billion by 2034.

Gartner says that spending on agentic AI will reach $201.9 billion in 2026, which is 141% more than in 2025. By 2027, spending on agentic AI will be higher than spending on chatbots and assistants.

In 2026, the world will spend $2.52 trillion on AI, which is 44% more than in 2015. Infrastructure will account for $1.36 trillion (54% of the total), with AI-optimized servers leading the way.

Enterprise Adoption

By the end of 2026, Gartner says that 40% of business applications will have AI agents that can do specific tasks. This is an increase from less than 5% in 2025.

IDC says that by 2027, the number of G2000 agents will grow tenfold, and the number of token and API calls will grow a thousandfold. By 2029, there will be more than 1 billion AI agents in use around the world – 40 times the number in 2025.

More than 40% of organizations now have AI agents in production. By the end of 2026, 71% of businesses will have a lot of AI agents working in production.

However, McKinsey reports that while 62% experiment with AI agents, fewer than 25% have scaled to production. Gartner says that by the end of 2027, more than 40% of agentic AI projects will be put on hold because prices are going up, the business value is unclear, and there aren't enough risk controls.

Multi-Agent Systems

Companies are deploying groups of smaller, specialized agents that coordinate, shifting from task-specific agents to agentic ecosystems. By 2027, 70% of multi-agent systems will have roles that are very specific and narrow. Anthropic says that multi-agent systems are 90.2% better than single-agent systems at hard tasks. Also, 56% of businesses say that multi-agent systems are easier to scale.

Platform Updates in 2026

• Microsoft Copilot Studio has a lot of features, like the ability to automate tasks on both the web and the desktop (public preview in May 2025, general availability in May 2026); the ability to connect to custom MCP servers (public preview in March 2026, GA in April 2026); the ability to create custom metrics for analytics (public preview in March 2026, GA in May 2026); and real-time agent evaluations and activity maps.

• Amazon Bedrock AgentCore: the SDK is still being worked on, and the CDK Construct Library will be released in February and March 2026. This will let agents be deployed with memory and identity capabilities.

• Google Cloud Vertex AI Agent Builder: Python Agent Development Kit (ADK) downloaded over 7 million times. April 2026 adds configurable context layers, new features for observability, and agent identities that are built in.

• Frameworks: Klarna, Uber, and LinkedIn have used LangGraph over 47 million times. Pydantic AI for safe production agents. CrewAI for organizing multiple agents. Microsoft Research's AutoGen is for use in schools.

Industry Adoption

• Cybersecurity: 58.7% planned deployment

• Sales, marketing, service: 51.3%

• Supply chain management: 47.8%

• Software development (developer-facing agents): faster growth than business-facing (IDC)

• Healthcare: slower due to regulation; pilots for clinical documentation, prior authorization, patient triage; production expected 2027–2028

• Financial services: fraud detection, compliance monitoring, customer onboarding; cautious adoption

Security Risks

Forrester says that an agentic AI deployment will lead to a publicly known data breach in 2026, which will result in the firing of employees. Agents are riskier than traditional AI because they can take actions – a compromised agent with CRM access could export customer data; a compromised DevOps agent could delete databases. Google thinks that targeted prompt injection attacks on business AI systems will go up a lot in 2026.

Through 2027, task-driven agent abuse will cost at least four times as much as multi-agent systems. By the end of 2026, businesses will be in charge of a lot more machine, agent, and workload identities than people. Current identity and access management models can't handle autonomous non-human trust on a large scale.

Human Role Changes

By 2030, 80% of developers will work with autonomous AI agents, going from writing code to planning and organizing.

Cisco has switched to spec-driven development, which means that a team of eight people can be cut down to three, with the help of five digital agents, and the output could be tripled. By the end of 2026, Cisco hopes to have six products that are made with AI only.

Anthropic's 2026 Agentic Coding Trends Report says that developers only give AI 0-20% of their work, even though they use it for about 60% of their work.

ROI Results

Average return on investment for generative and agentic AI: 49% ($1.49 per dollar invested), a 20% increase over the previous year. CIOs anticipate up to 179% ROI.

PwC says that 79% of businesses use AI agents, 66% say their productivity has gone up, and 62% expect their return on investment to be more than 100%.

Case studies:

• Rakuten: The AI coding tool added a feature to vLLM (12.5 million lines of code) in seven hours with 99.9% accuracy.

• TELUS built more than 13,000 custom AI solutions, delivered code 30% faster, and saved more than 500,000 hours.

• PGA TOUR: Multi-agent content generation sped up writing by 1,000% and cut costs by 95%.

• Workday's Planning Agent (on Amazon Bedrock) cut down on the time it takes to do routine analysis by 30%, which saved each planning team about 100 hours a month.

Watch List for 2026-2027

• Infrastructure-laying continues through 2028; true agent-native ecosystems are three to five years away.

• First major agent-driven breach expected (prompt injection, excessive permissions, or hallucinated dangerous action), followed by regulatory scrutiny.

• Multi-agent systems become default.

• Platform competition continues among AWS, Microsoft, Google; the framework layer (LangGraph, PydanticAI, CrewAI) may capture more value.

• Getting ready for data is what makes the difference between winners and losers. Businesses that don't have high-quality, AI-ready data will see a drop in productivity by 2027.

• Regulation: The EU AI Act is in effect, and more US states are passing their own laws. By 2027, agentic systems will have to meet certain standards.

• Open-source models like Llama, Mistral, and others fill in the gaps. By the end of 2026, a lot of production deployments will use fine-tuned open-source models instead of costly proprietary APIs.

"We've never seen businesses move from AI pilots to production agents at this speed before," said Dmitry Baraishuk, Partner and Chief Innovation Officer at Belitsoft. "The key to success is to treat agent development like an engineering field and put money into data quality, observability, and multi-agent architectures from the start." Companies that don't follow these steps will have projects that don't work and security problems.

About the Author:

Dmitry Baraishuk is a Partner and Chief Innovation Officer at Belitsoft. Belitsoft is a software engineering company specializing in DevOps, AI integration, and enterprise application modernization. The company serves clients across healthcare, fintech, and enterprise SaaS in the US, UK, and Canada. Belitsoft publishes technology trend analyses to help business and technology leaders make informed decisions about their software investment strategy.

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