This week is all about AI agents. They’re no longer some futuristic fantasy – they’re here, and they’re quietly changing the way businesses operate. You might already be using one without realising it, whether it’s an AI-powered customer support bot, a research assistant, or an automated workflow in your CRM.

But are businesses actually using AI agents effectively? Or are they just experimenting without real impact?

The reality is, AI agents can save teams hundreds of hours by automating tasks like data analysis, customer inquiries, internal approvals, and even creative work. But throwing AI at a problem doesn’t magically fix inefficiencies… it has to be done right.

Firstly, I thought I’d share some great uses of AI agents:

1. Taking Customer Action (before it's too late)

The Problem: Customer facing teams spend too much time collecting, cleaning, and analysing data, instead of making decisions.

The AI Agent: Can extract insights from customer feedback and sales data, to generate clear summaries, dashboards and actionable reports.

Last year, my team and I surveyed hundreds of Customer Success Managers in SaaS who overwhelmingly said they wish they had more time to focus on customer relationships. Using AI agents to pull actionable insights from customer data could be a great way to achieve this.

2. Improving Product Engagement

The Problem: Maintaining personalised interactions at scale proves challenging and takes up time.

The AI Agent: Can monitor user events on your platform, identify behaviour trends, and then automatically send personalised product emails to encourage users to take an action or increase feature adoption.

Of course, depending on how developed your product is, you might already have a dedicated tool that solves this problem. AI agents can be a great intermediary option before investing in an expensive SaaS solution.

3. Automated CRM Updates (to avoid easy mistakes)

The Problem: Manual data entry is a drain of employee time, and things can easily get missed, leading to mistakes down the line.

The AI Agent: Can extract information from client communications and automatically update contacts in your CRM. Anything from a client address change to a note that a stakeholder is leaving the business.

These are just a few day to day examples of AI implementation which can lead to increased efficiency in a business.

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Now, How to Get AI Agents Right?

If you’re thinking about integrating AI agents into your business, here are some things to consider:

💡 Start Small, Think Big Don’t aim to automate everything overnight. Pick one high-friction process or workflow – like customer onboarding or lead qualification – and test an AI agent there first.

📊 Your AI is Only as Good as Your Data If your data is messy, incomplete, or inconsistent, AI agents won’t be able to deliver useful and actionable insights.

🔄 Test, Learn, Iterate The best AI implementations are built incrementally. Start with a pilot, measure the results, and tweak as you go. Solve a genuine problem or blocker your employees are experiencing first to increase internal engagement with the AI agent.

🔐 Security & Compliance Matter AI handling sensitive business data? Make sure it’s built with privacy and security in mind – especially with upcoming AI regulations in 2025.

💻 Meet Your Team Where They Work Have you invested in AI solutions only to find your employees are sticking with their own ChatGPT accounts? AI Agents should seamlessly fit into existing workflows and reduce manual recurring tasks – so first you need to deeply understand your employees’ processes.

AI agents can be game-changers if they’re implemented strategically! But there’s lots to consider.

I’d love to know: Are you already using AI agents in your business? What’s working, and what’s not? Anything you’d like me to cover in future editions?

Thanks for reading!

Caroline