11 AI agent examples_ - Infinity Group (UK)

Key takeaways_

AI agents are autonomous tools that can perform tasks, make decisions and integrate with business systems – going beyond simple chatbots.
From customer service and IT support to marketing automation and data analysis, these 11 examples show how AI agents can streamline operations and boost productivity.
Start exploring agent-based solutions to reduce manual work, improve efficiency and unlock new opportunities for innovation.

Feeling busy at work? If so, you’re not alone. Over half of employees and businesses leaders are currently expected to do more work than a single person’s job.

The result is limited capacity, high levels of stress and employee burn-out and potential corner cutting in the bid to save time. It also makes it harder to find time for strategic thinking that drives agility, innovation and performance.

AI and automation are solutions to this issue. Both offer significant time saving benefits, allowing you to free capacity and let employees focus on higher value work. By combining AI and automation in the form of AI agents, the rewards are even greater.

Due to this potential, more organisations are embracing agentic AI. 72% of leaders expect AI agents to be fully integrated across their operations, with 21% anticipating this to be within the next 12 months.

If you want to join the fold before you’re left behind, you need to know how you can best utilise agentic AI to get results across your business functions. We’ve put together 11 AI agent examples to show you exactly how they can work for you.

What are AI agents?

Firstly, let’s dive into what AI agents are.

They are software programs designed to perform tasks autonomously or semi-autonomously, using artificial intelligence. Unlike generative AI, which just serves answers based on prompts, they can actually execute tasks.

A great example of an AI agent is a virtual assistant, like Siri or Alexa. You ask it to do something, and it can autonomously complete tasks, like creating a reminder, sending a text or setting an alarm.

There are three ways to use agents, from simple to more advanced:

Retrieve information, using your data, applying reason and summarising to answer user questions (such as a helpdesk agent)
Complete tasks, using automation to replace repetitive work (such as a bank reconciliation agent)
Operate independently, with the ability to plan responses, orchestrate other agents and escalate issues (such as an agent that researches and qualifies leads)

Each of these can be used in different approaches, depending on the agent you build.

Getting buy-in before you experiment with AI agents_

Before you test AI agents, you need buy-in – or you’re just running experiments that won’t go anywhere. Most pilots stall because there’s no shared clarity on the problem, no ownership of the process and no trust from the people expected to use it. AI agents cut across workflows, data and decision-making, so they quickly expose gaps that already exist; without alignment, you’re automating instability.

The quickest way to build buy-in is to anchor on a problem people already feel, tie it to a measurable outcome (time saved, cost reduced, faster response, lower risk) and set clear guardrails on where the agent operates and when humans step in. Involve the users early and position it as support, not replacement. You don’t need a long strategy phase, just enough alignment to make the test meaningful and scalable.

Our experts explore how to get started smoothly with best practice tips:

The difference between organisations getting value from AI agents and those stuck in pilot mode is simple: they align on the outcome first, then test.

11 AI agents examples_

We’ve put together 11 AI agent examples if you’re looking for a greater understanding of what AI agents are or how you can use them in your business. Remember, these are by no means an exhaustive list – but they should show you how AI agents can work.

1. Chatbots_

Chatbots use natural language processing to understand and respond to user queries. They can follow predefined scripts or use AI-driven reasoning to autonomously answer questions, provide information and support tasks such as booking appointments or troubleshooting common issues.

What it does:

Understands user queries using natural language processing.
Provides instant answers, guidance and information based on rules or AI reasoning.
Handles routine tasks such as booking, form completion and troubleshooting.
Offers 24/7 assistance without the need for human intervention.

Business value: Chatbots reduce wait times, improve user experience and free capacity within customer service teams by taking on high‑volume, repetitive enquiries consistently and at scale.

2. Recommendation systems_

Recommendation systems analyse user behaviour, preferences and historical interactions to suggest relevant products, services or content. With agentic AI, these systems can autonomously refine recommendations based on real‑time inputs.

What it does:

Analyses user behaviour using collaborative, content‑based or hybrid filtering methods.
Suggests relevant content, products or services based on past interactions.
Continuously adapts recommendations as new data becomes available.
Personalises experiences for each individual user without manual tuning.

Business value: You deliver tailored customer experiences that increase engagement, improve retention and drive higher revenue through more relevant recommendations.

3. Fraud detection systems_

AI agents can monitor transactional activity in real time to detect unusual behaviour and block potentially fraudulent actions before they cause harm.

What it does:

Scans transactions continuously for suspicious patterns.
Detects anomalies using machine learning models trained on past fraud indicators.
Automatically blocks or flags high‑risk transactions.
Sends alerts to security teams for further investigation.

Business value: Businesses strengthen security, reduce financial losses and maintain customer trust by responding quickly to fraudulent behaviour.

4. Predictive analytics_

Predictive analytics agents autonomously gather, clean and analyse data to anticipate future trends, events or risks without manual intervention.

What it does:

Collects data from databases, APIs and real‑time streams automatically.
Cleans, normalises and prepares data for analysis.
Generates predictions for demand, performance, risk or customer behaviour.
Triggers downstream actions, such as adjusting marketing campaigns or initiating maintenance alerts.

Business value: You gain earlier visibility into trends and risks, improving decision‑making and enabling proactive responses instead of reactive ones.

5. Inventory management systems_

AI agents help optimise inventory levels by analysing sales patterns, demand forecasts and market conditions.

What it does:

Tracks stock levels and predicts when items will run low.
Automates reordering processes.
Analyses sales data and market trends to balance stock levels.
Alerts teams about potential shortages or overstock risks.

Business value: You prevent stockouts, avoid excess inventory and ensure consistent product availability while reducing operational inefficiencies.

6. HR recruitment tools_

AI recruitment agents streamline candidate screening and reduce the manual workload on hiring teams.

What it does:

Screens CVs and analyses candidate qualifications.
Matches applicants to roles using predefined criteria.
Prioritises top candidates for human review.
Supports interview scheduling workflows.

Business value: Recruitment becomes faster, more consistent and less biased, allowing HR teams to focus on engaging and interviewing strong candidates.

7. Voice recognition systems_

Voice-enabled agents understand and transcribe spoken language to support customer service, documentation and accessibility.

What it does:

Converts speech into accurate text.
Extracts key information from recorded conversations.
Assists users who prefer speaking rather than typing.
Generates documentation from calls or meetings automatically.

Business value: Teams save time on transcription and data entry, while accessibility improves for users who benefit from voice‑based interactions.

8. Dynamic pricing tools_

Dynamic pricing agents adapt prices in real time based on demand, competition and market conditions.

What it does:

Monitors market signals and competitor pricing.
Calculates optimal price points.
Updates pricing across websites and ecommerce platforms automatically.
Tests different price strategies to maximise results.

Business value: You stay competitive, increase sales opportunities and maximise revenue through intelligent, real‑time price adjustments.

9. Supply chain optimisation_

Agentic AI can analyse and act on operational data to improve logistics, stock management and supplier performance.

What it does:

Forecasts demand to optimise inventory.
Plans and adjusts delivery routes based on real‑time conditions.
Evaluates supplier performance using historical data.
Responds to disruptions by automatically rerouting shipments.

Business value: Operational costs decrease, delivery times improve and the overall supply chain becomes more resilient and reliable.

10. Sentiment analysis tools_

Sentiment agents interpret text from reviews, social media and other sources to understand public opinion.

What it does:

Uses NLP to classify sentiment as positive, neutral or negative.
Monitors online mentions for emotional tone.
Alerts teams when negative sentiment spikes.
Highlights themes or areas for improvement.

Business value: You gain a clear picture of customer perception, enabling proactive brand management and more effective marketing strategies.

11. Personalised marketing_

AI agents create and deliver tailored marketing campaigns by analysing customer behaviour and preferences.

What it does:

Examines customer data to segment audiences automatically.
Builds personalised email, ad and content journeys.
Schedules campaigns based on the best time for engagement.
Adjusts messaging based on user responses.

Business value: Marketing becomes more targeted and effective, boosting conversion rates and strengthening customer relationships.

Copilot Agents: making AI agents accessible_

Now you know some AI agent examples, you might be wondering how to create them for your business. Luckily, Microsoft are making it easy with Copilot Agents.

Copilot Agents are Microsoft’s take on agentic AI, tailored to specific business use cases. The agents act as automatic bots with AI capabilities, enabling you to alleviate manual work and minimise intervention.

You can easily build and configure them within Copilot Studio, without the need for highly technical skill. Plus, they’re already grounded in your data for smoother processes.

Plus, if you needed even more inspiration to get started, Microsoft have created pre-built Copilot Agents that you can embed in your business and across tools you already use. You can find out more about what’s available here.

And if none of these pre-built agents work for you, you can create your own from scratch, thanks to Copilot Studio’s easy-to-use interface.

Copilot Agents in real life_

Still not sure whether Copilot Agents can drive results in your business? Luckily, organisations have already deployed Copilot Agents – and seen the results. Here are just a few stories, courtesy of Microsoft.

Pets at Home_

Pets at Home, the UK’s largest pet care company, has integrated Microsoft Copilot Agents to enhance various aspects of their operations. They developed AI agents to support different business areas, including a notable application for the retail fraud detection team. This AI agent helps investigate suspicious transactions more efficiently, improving the team’s effectiveness.

As a result, they have experienced a cost avoidance of £1 million+, with seven figure annual savings predicted.

Microsoft_

Microsoft has tasted their own champagne and implemented Copilot Agents. This has included a technical support agent that supports engineers by empowering businesses and customers to self-serve as much as possible.

Since implementing the agent, they’ve already experienced a 32% increase in self-service and a 20% reduction in missed routing for calls.

Infinity Group_

Yep that’s right – we use AI agents to automate the work that slows teams down and to amplify the work that moves projects forward. Internally, our agents take on everything from answering repetitive product or process questions – by retrieving and reasoning over our documentation – to automating routine tasks like bank reconciliation, meeting prep or data gathering. They also act as more advanced collaborators: researching and qualifying leads, spotting gaps or inconsistencies in project requirements, highlighting risks early and orchestrating next steps without manual intervention.

In delivery, our agents analyse ambiguous inputs, flag unclear scope items and remove the admin that traditionally drags projects off‑track, freeing consultants to focus on design, decision‑making and client outcomes. Customer‑facing teams benefit from autonomous chatbots that resolve everyday enquiries, while personalised‑recommendation and predictive‑analytics agents quietly optimise user journeys, inventory and operational planning in the background. Together, these agents strengthen project delivery, reduce risk, improve decision quality and reclaim time across the business – creating smoother processes, more consistent outcomes and more space for our specialists to focus on genuinely high‑value work.

Find out how we’re using Copilot Agents.

Start with Copilot Agents_

If you’re ready to experiment with AI agents, Copilot Studio makes it easy. With a user-friendly platform and endless possibilities, you can easily create agents that align to your business needs and boost automation.

Find out more about Copilot Agents and how to get started in our guide.

Key takeaways_

What are AI agents?

Getting buy-in before you experiment with AI agents_