How AI Agents Are Streamlining Coworking Operations

AI agents are already working inside real businesses, responding to customers, scheduling meetings, guiding onboarding, and even preparing leads for sales teams. Unlike earlier automation systems, these agents don’t just follow rules, but instead make decisions based on goals, context, and input from other agents or systems.

For years, automation meant building strict workflows. A customer signed up, and a series of steps followed: send a welcome email, create an account, add the user to a billing system. These processes were useful but rigid. Every outcome was mapped step by step.

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With the rise of tools like ChatGPT and open AI platforms, automation became more flexible. You could drop in some intelligence. An email could adapt its tone or content based on user data. But even then, it was still operating inside a controlled structure.

AI agents work differently. You tell them what result you want, give them access to tools or data, and they figure out how to get there. No manual workflows. No scripts. Just a goal and the freedom to pursue it.

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Think Colleague, Not Tool

Companies like Uniti AI are already deploying these systems to support lead conversion in the flexible workspace industry, according to a report by This Week in Coworking. Their agents act as teammates who are available 24/7, trained to learn from outcomes, and capable of managing entire customer journeys.

Instead of programming steps, users provide parameters. Agents reach out, respond, guide, and even escalate to human staff when needed. The experience for customers feels more personal. For teams, it frees up time for more complex work.

Why AI Agents Are Taking Off

Several developments are fueling this new direction in work technology:

1. Agent Building Kits: Major platforms now offer tools that allow developers to build agents in hours, not weeks. Some can even generate agents using other AI tools.
2. More Investment: Investors are backing AI systems designed for industries with repetitive, time-consuming tasks. These are the same spaces where agents can deliver results quickly.
3. Cross-System Access: New protocols allow agents to connect with CRMs, internal systems, and even platforms that don’t offer public integrations. Think of it like giving your agent a master key.
4. Multi-Agent Collaboration: Instead of one agent doing everything poorly, companies are assigning tasks to multiple agents with specialized roles. One handles onboarding. Another handles payments. A third manages customer follow-up. They communicate and cooperate without human prompts.

Salesforce CEO Marc Benioff recently said today’s executives may be the last to lead all-human workforces. Microsoft’s Satya Nadella has echoed similar ideas, noting that software architecture is being rebuilt to support agent-based systems.

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That means companies will assign work to AI agents the way they would to team members. Some will supervise them. Others will train them. All will need to understand how to work alongside them.

Early Adopters Are Already Seeing Results

Orega, a workspace operator, took a cautious approach. They explored AI systems for nearly a year before choosing to “hire” an AI sales agent. That decision followed early wins in marketing, where AI tools helped create content and automate communications.

Now, the agent helps qualify leads, respond faster, and ensure no potential customer gets missed during off-hours. 

What Comes Next

AI agents won’t replace every role, but they will take over repeatable, decision-driven tasks — the ones that don’t require human judgment but do require time and attention. In many cases, these agents will hand off work to human teammates or gather data to make their jobs easier.

Instead of replacing people, AI agents are likely to change what people spend their time on. That brings new challenges around training, management, and collaboration, but also new possibilities for productivity and growth.

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