Alexandria – September 22, 2026 – The AI agents market is primed for hypergrowth and will be a leading enterprise technology category by 2034. The market is projected to reach $251.38 billion by 2034, growing at a CAGR of 46.61% from 2025 to 2034. North America currently holds 38% of market share, driven by adoption in retail, healthcare, finance and technology. An example of this is Belitsoft who built an AI-supported Chrome plugin to help an online retailer train employees and reduce attrition. With adoption and market value skyrocketing, companies need to treat AI agents as a strategic growth area rather than just an experimental tool.
1. The Changing Role of Developers
Developers are shifting from writing code to orchestrating, coordinating and managing autonomous AI agents.
According to IDC’s FutureScape 2026 report, by 2027, 35% of professional developers will be using vibe-coding platforms, and by 2030, 80% of developers will be using autonomous AI agents.
The development lifecycle is being transformed to enable human-AI collaboration. As InformationWeek reports, brittle glue code is being replaced with standardized agentic primitives and well-documented APIs that provide agents with access to tools.
Developers will also need skills in orchestration, API/tool design, evaluation, and agent management, in addition to traditional coding.
2. Voice AI Mainstreaming Gathers Momentum
Voice AI is quickly becoming a ubiquitous interface that allows customers and businesses to interact with AI.
CB Insights says speech AI is the fastest-growing branch of generative AI. Voice agents in customer service, sales, and IT support are getting better at handling complex, multi-turn conversations without human intervention.
In 2025, Meta bought two speech AI companies, Play AI and WaveForms—a sign of rapid consolidation in the space.
The developer’s job is to build voice agents that understand tone, context, and intent—not just words. Voice capability will be a prerequisite for competing in the market.
3. Agentic AI Gets Hit by M&A Wave
As agentic AI is poised for a wave of consolidation, vendor longevity and acquisition focus are key strategic considerations.
AI agent solutions were the most common type of AI exit deal, with over 35 deals to acquire companies in the AI agent and copilot markets in Q1 2025, according to CB Insights.
Enterprise buyers need end-to-end agentic tools to maintain a competitive advantage. Startups today are competing not just for customer attention but also for investor attention. When assessing providers, businesses should ask whether a platform will be able to operate independently within a year.
Startups need to position themselves to eventually stand alone or be acquired. Before they commit, businesses should consider the roadmap, the consolidation risk, and the lifespan of the vendor.
4. The Profit Margin Squeeze Is Upon Us
The economics of AI agents are tightening, and companies must focus on unit economics and capital efficiency.
CB Insights says the “summer of vibe coding” is coming to an end because of high inference costs. Lovable and Cursor are among the companies that have had to raise prices and introduce rate limits, as reasoning models can consume up to 20 times more tokens.
Lovable crossed $100 million in ARR and Cursor crossed $500 million in ARR, but they are still under cost pressure. The most capital-efficient agent companies produce nearly 2.5 times the category average, or $1.4 million per employee.
The winners will be those who have the best cost discipline, not just the best models or the best people. Unit economics can no longer be ignored by executives and developers.
5. Agent Monitoring Becomes Critical
Monitoring, observability, and governance are becoming increasingly important for the deployment of AI agents.
Specifically, strange behavior or hallucinations by agents directly threaten operations. Surveys show that one-third of executives consider security and governance more important than ease of integration when evaluating an agent platform.
In 2025, CB Insights tracked seven early-stage deals worth $30.9 million in AI agent observability and governance. Cekura and Coval have raised seed rounds to test and simulate voice AI agents. Larridin raised $17 million to measure AI productivity and ROI in hybrid human-AI workforces.
Governance is no longer an option, it is a must. You need to have things like audit trails, access controls, testing, simulation, and monitoring in place before you can scale agents.
What Decision-Makers Should Take into Account
To successfully scale agents, AI strategy leaders must prioritize talent transformation, data quality, and governance.
Scaling without controls is a source of operational risk. Even the best algorithms make bad decisions with poor data. Almost one-third of stakeholders cite a lack of skills as a growth barrier.
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.
Media ContactCompany Name: BelitsoftContact Person: Dmitry BaraishukEmail: Send EmailCity: AlexandriaState: VACountry: United StatesWebsite: https://belitsoft.com/
