How AI Orchestration Is Reshaping Enterprise Software
The recent wave of tech layoffs has been framed as a signal that AI efficiency has reached a critical mass. But they also signal something deeper about the AI market: Enterprise software has become too complex, too fragmented, and too expensive to sustain in its current form. This leads to AI that doesn’t create value, putting even more pressure on workforce downsizing to determine the ROI of AI investments.
Despite this rhetoric, human agents remain essential in customer service. In fact, most consumers still prefer to speak to a human agent, even when they are assured that AI can resolve their inquiry. When companies recognize that agentic AI can unify fragmented tools and execute tasks across them, it removes the manual coordination burden that slows agents down and undermines customer outcomes. The future is not bloated technology stacks with AI bolted on top—it’s using agentic AI to unify systems and execute tasks so human agents can focus on building trust, loyalty, and relationships, increasing customer lifetime value.
Enterprise AI Software Is Built Around Human Coordination
Modern enterprise workflows evolved under a fundamental constraint: Systems can’t act independently. Siloed, static systems and data show up often in customer service, especially with platforms like ticketing platforms and case management.
Ticketing platforms tried to become the operational center. A customer request would enter a ticket, and the human agent became the connective tissue between the interaction and the underlying software stack, interacting with 4 to 10 systems on average during a single interaction. They pulled data from one system, updated records in another, triggered workflows elsewhere, and manually ensured each step was completed.
The result of human-led orchestration is costly. Contact center agents spend more time navigating tools than resolving issues, increasing cognitive load and slowing resolution. Delays compound, context is lost between systems, and customer experience (CX) suffers as simple requests require multiple manual handoffs. It’s no wonder the contact center industry has an employee burnout and churn problem.
Inevitably, this structure became increasingly complex as software environments expanded. Today, the average company manages 305 SaaS applications. Each system adds capability, but also increases the coordination required to operate them.
The result was an operational model built entirely around human agents being the integration layer. That model is beginning to change in the world of agentic AI.
Humans and Agentic AI Are Teammates
AI systems are moving beyond generating responses and into executing work directly. Once agentic AI handles cross-system orchestration, agents are freed from acting as manual connective tissue between ticketing platforms, CRM systems, and back-end tools. Instead of navigating software, they act on it—focusing on judgment, empathy, and complex decision-making while AI executes workflows in the background.
Gartner predicts that 33 percent of enterprise software applications will include agentic AI by 2028, up from less than 1 percent in 2024. In just four years, AI is moving from virtually non-existent inside enterprise systems to embedded across a third of them.
Most importantly, agentic AI does not make human agents expendable. It makes them more essential by removing the friction that once defined their work. What becomes expendable are the expensive SaaS tools that cost seven figures annually to manage.
CX Becomes a Function of Execution, Not Conversation
This trend is playing out in real time in the CX industry. The AI in CX conversation has focused on front-end automation as the primary solution to operational strain and cost. The assumption was straightforward: If AI could handle more conversations (or in reality, deflect more customers from human agents), it could reduce costs and improve productivity with less agents. Yet AI interaction costs have continued to rise, stacks have grown more complex, and agents remain buried under disconnected tools.
The complexity sits behind the interaction, in the layers of software required for human agents to execute even the simplest request. Outcomes depend on AI execution, not simply automating every interaction. Every customer request ultimately requires systems to retrieve information, update records, or trigger an action. Historically, human agents had to coordinate those steps across multiple tools, which introduced delays and complexity.
Agentic AI flips this assumption on its head. Imagine agentic AI that automates the mundane tasks still on an agent’s desk, easily escalates complex customer issues with full personalization and context, provides next best actions based on the unique customer question, and then can actually execute workflows across siloed SaaS tools with a simple click of a button instead of swivel-chairing across multiple apps and tabs. This is the future and the true value of AI in the contact center, not just using front-end automation to cut out human agents.
CX improves as operational friction is removed and systems handle execution more directly. The complexity that once existed behind the scenes is beginning to fade, and what’s happening in customer service is an early signal of a much broader shift.
The Most Important AI Interactions Will Be Invisible
Many of the most significant AI interactions in the enterprise will never be seen by customers or employees. They will happen behind the scenes, as systems retrieve information, trigger workflows, and execute tasks autonomously. As AI orchestration moves into the software layer, operational complexity collapses, resolution accelerates, and CX efficiency improves across the organization.
This is the real transformation that is under way. The first phase of enterprise AI emphasized conversational interfaces and surface-level automation. The deeper shift is structural. Execution is moving into the system layer itself.
Enterprise AI will be defined by orchestration, by software that can coordinate and act across systems in real time. And by human agents who are elevated by that capability.
Humans remain central to this evolution. In a world fraught with poorly implemented AI self-service experiences, human agents are the new CX differentiator. Their role becomes more important than ever, while the interactions they handle become more challenging and complex, and their objectives expand from manual coordination to strategic oversight, judgment, and decision making. AI becomes the execution engine. Agents become the force multiplier.
Vasili Triant is CEO of UJET, overseeing all company operations and strategic initiatives. Triant brings more than 20 years of experience in telecom, unified communications, and contact center industries. He previously served as VP/GM of contact center at Cisco, where he focused on global alliances and enterprise cloud readiness.