Artificial intelligence is no longer a promise for the future but the operational engine of many companies. However, when it comes to AI agents – those systems capable of executing tasks autonomously and sequentially – the leap from theory to real production is proving much more complex than the headlines suggested. A recent study with technology managers from more than a hundred organizations reveals that the real bottleneck does not lie in the choice of orchestration platform, but in the gap between strategic ambition and actual implementation capacity.
Modeling platforms – with Anthropic at the forefront – are hogging the business preference, with 40% of respondents citing them as their primary ecosystem for orchestrating agents. The main reason is the severity of the underlying model: companies choose the orchestration system that comes standard with the edge model they've already invested in. However, when asked for an honest assessment of their portfolio, 71% admit that a quarter or less of their so-called "agents" are truly multi-step workflows; Most are still simple chatbot wrappers that respond to a single prompt. It's the chatbot trap: the orchestration architecture is built way ahead of the orchestrated portfolio it is meant to govern.
This gap has direct implications for the control strategy. By the end of 2026, 51% of enterprises expect to have a hybrid control plane – combining vendor-native capabilities with external orchestration layers – and only 6% would delegate all control to a vendor-managed service. Fear of vendor lock-in (35%) is the main reason, followed by security and permitting limitations (28%). The lesson is clear: organizations want to harness the power of the most advanced models without being trapped in a closed ecosystem. The hybrid solution is not a fad, it is an architectural hedge against the risk of dependency.
In parallel, investment follows deployment. Spending is concentrated on agent workflow tools (34%) and security and permit enforcement (25%). However, real-time fiscal control remains a pending issue: more than a quarter of companies (27%) lack a programmatic mechanism to stop a runaway agent before the invoice arrives. This is especially critical in a scenario where agents are moving to production faster than the cost control plane that should accompany them.
In this context, having a technology partner that understands both the AI layer and the underlying infrastructure becomes crucial. At Q2BSTUDIO we work with companies looking to go beyond prototypes, helping them design and implement AI solutions for companies that truly solve business problems. Our expertise ranges from building custom applications that integrate AI agents with multi-step flows, to secure orchestration on AWS and Azure cloud services. In addition, we know that visibility is key, which is why we incorporate business intelligence services with Power BI to monitor the performance and consumption of each agent in real time.
The question every technology management should be asking is not which model platform to choose, but how to ensure that the actual implementation lives up to the ambition. The survey confirms this: most companies have not yet passed the experimental phase. Those that succeed do so not only because of the platform, but because of the way they integrate control, security and costs from day one. That's why more and more organizations are opting for custom software that adapts to their processes, rather than forcing their operations into generic tools. Cybersecurity also plays a central role: a poorly orchestrated agent can become an attack vector if permissions and execution paths are not managed correctly.
All in all, the study reveals an uncomfortable but hopeful reality: the AI agent orchestration ecosystem is maturing, but the pace of deployment is still slower than the market assumes. Companies that close that gap—integrating powerful platforms with hybrid controls and a robust cost strategy—will be the ones that truly harness the potential of autonomous AI. At Q2BSTUDIO we accompany this journey with a practical and results-oriented approach, because we know that technology is not worth for itself, but for what it allows us to do.
