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AI Agent Usage Breakdown
Comparison of AI agent allocation by operational function.
Primary Sources
Nontechnical Manager Has 37 AI Agents That He Oversees - Business Insider
I built 37 AI agents to help at work. I made one act like a Star Trek character, and another like an FBI negotiator. As told to Ana Altchek You're currently following this author! Want to unfollow? Unsubscribe via the link in your email. Andy Cabasso oversees 37 AI agents. Andy Cabasso 2026-04-29T09:17:01.295Z Andy Cabasso manages growth operations at productivity platform ClickUp. He manages 37 AI agents that handle tasks like scheduling, analytics, and meeting follow-ups. Cabasso personalizes agents with fictional personalities to enhance engagement and task execution. This as-told-to essay is based on a conversation with Andy Cabasso, a growth operations manager at productivity platform ClickUp. He is based in New York. The following has been edited for length and clarity. I used to practice law, and I became very disenchanted with the inefficiency of it, particularly the focus on billable hours. It didn't benefit me to be better with keyboard shortcuts or to be able to work faster than my colleagues.So I started a legal digital agency focused on leveraging automation with projects that were value-priced, rather than priced on inputs. I was acquired by a larger company, and now I focus on growth operations at ClickUp.When I arrived at this company over a year ago, I wasn't working with any agents. Then ClickUp gave us these tools and a tech stack to give us agents that had context on all of our work, and I thought, "How can I best use this?"It snowballed from there. I have 37 agents nowI used to say that I was the most technical non-technical person on my team. I didn't know how to code anything — and I still don't think anyone would pay me to code today.But I understand a lot of the frameworks of how software actually works from working alongside technical cofounders and building marketing automation systems. I understand how databases are structured, how APIs connect, and how data flows between tools.When I first started at ClickUp, we had a mandate to use AI agents more in our day-to-day. There was a culture fostered around sharing our AI workflows. I started small with the tasks that were tedious that I wanted to take off my plate. The first agent I built was a scheduling agent that would look at my calendar and task list, and help me plan out my day.I have 37 AI agents now. I probably use 15 to 20 of them in my day-to-day, and the rest on an as-needed basis.I have one agent that pulls analytics from our outbound platform to give insights ...
Beyond the Hype: What AI Agents Actually Do in an Enterprise
IN THIS ARTICLE The second article of twelve. If Article 1 argued why Caribbean executives must engage with AI now, this article installs the vocabulary needed to engage well — and the discipline to tell a genuinely agentic product from one that has been rebranded as such. Most Caribbean executives have used consumer AI tools. Very few have a precise mental model of what distinguishes a chatbot, a copilot, and an agent — and that gap is the single largest source of confusion in current boardroom conversations about artificial intelligence. This article closes the gap. By the end of this article you will be able to: 1. Distinguish with precision between the five tiers of enterprise AI systems — language model, assistant, copilot, agent, and multi-agent system — and explain the distinction to your board in plain language. 2. Recognise, in any vendor demonstration, whether the product being pitched to you is genuinely agentic or a chatbot marketed as an agent — using a four-question diagnostic you can apply in the meeting itself. 3. Identify at least three concrete agent use cases realistic for a Caribbean enterprise at your organisation’s scale, drawn from the workflows that are already in production elsewhere in the region. A chief executive I have known for a long time — the head of one of the larger Caribbean financial services institutions — telephoned me a few weeks ago after a vendor meeting. He had just been shown what was described to him as ‘an agentic AI solution for relationship banking’. The demonstration, he said, had been impressive. The vendor had sophisticated slides, a well-rehearsed presentation, and what appeared to be a working product. His board was interested. He was about to commit meaningful capital to a pilot programme. But something was nagging at him. He could not say precisely what. He asked me whether I could spare thirty minutes to look at the vendor’s materials before he signed the statement of work. I agreed. The materials arrived that evening. What the vendor was actually selling, I told him when we spoke the next morning, was a chatbot. A capable one, with some useful integrations, but a chatbot nonetheless. It responded to prompts from bank staff; it did not execute multi-step work. Almost none of the so-called ‘agentic’ capabilities in the sales material were present in the product as sold. Some were on a roadmap. Others were frankly aspirational. The productivity claims in the business case rested on the product having ca...
Real-Life Examples of Using AI to Improve Customer Experience in 2025
Here are several examples from our team and CX leaders that you can use for inspiration. Real AI success stories in customer experience Here are some real-life success stories we gathered that you can use as an inspiration to implement AI to improve your customer experience. AI-powered information retrieval for agents
How Personalized AI Agents That Learn Your Workflows Will Multiply Your ...
Personalized AI agents that learn individual thinking patterns produce measurable productivity compounding over time, with less-experienced workers seeing 27-39% productivity gains compared to 5-13% for experienced workers using generic AI.
