Everything You Need to Know About AI Agents in 2025

Maybe you’re dealing with a surge in case volume, but your team is stretched thin. Or you’d love to offer 24/7 support, but tight budgets make it difficult to justify a round-the-clock workforce.

That’s where AI agents like Agentforce come into play. In this article, we will explain what AI agents are, how they work, and what you can do to deploy them successfully.

• What is an AI agent?
• How AI agents work: The four-step cycle
• The eight main types of AI agents and their use cases
• What are the benefits of AI agents?
• Real-world examples of AI agents in action
• 8 tips for successfully implementing AI agents
• Deploying AI agents with Salesforce Service Cloud
• The next generation of business technology

An artificial intelligence agent is an intelligent system that can understand and respond to customer inquiries without human intervention.

They rely on machine learning and natural language processing (NLP) to handle a wide range of tasks, from answering simple questions to resolving complex issues to even multi-tasking.

While often confused, AI agents and chatbots aren’t the same. Chatbots are simpler tools that follow scripts and respond to basic queries.

AI agents can understand social cues and context. They can also continuously improve their own performance through self-learning and use a decision-making mechanism to decide on the best approach based on a nuanced understanding of the situation.

AI agents work in a cycle. They take in information, decide what the next action should be, act on it, and then learn from its results. Here’s how that looks in practice.

1. Perception: They collect data from sources like customer interactions and transaction history to understand context, often in real time.
2. Decision-making: Based on everything it’s picked up, the agent figures out the best way to respond. It does this by spotting patterns and weighing up the context.
3. Action: The agent then steps in to get the task done, which could be answering a question, helping with a request, or getting a person involved if the request requires a human touch.
4. Learning: Each interaction helps refine their models. Over time, they adapt to new behaviours, improving speed, accuracy, and relevance.

This cycle allows agents to deliver consistent, high-quality service, even as customer expectations evolve.

AI agents come in many different forms, depending on the agentic architecture that they use as a foundation. Here are eight different types you should know about.

Adopting AI agents offers numerous benefits, transforming how businesses interact with customers and manage their service operations. Here are four benefits you can expect when using an AI agent.

AI agents are available around the clock, ensuring customer inquiries are addressed promptly, regardless of time zones or business hours. This continuous availability helps businesses meet customer expectations for self-service and improves customer loyalty.

AI agents deliver fast, accurate, and personalised responses, boosting customer satisfaction and improving with every interaction. In fact, 42% of organisations using AI say it’s already had a positive impact on customer experience.

AI agents can easily scale to handle increased volumes of customer interactions, making them ideal for businesses looking to grow without compromising service quality. As case volume increases, AI agents can be easily adjusted to ensure consistent and reliable support.

AI agents generate valuable data on customer interactions, preferences, and behaviours. Businesses can use this data to gain insights into customer needs and trends, enabling them to make informed decisions and improve their service offerings.

Companies in several different industries are seeing the benefits of integrating agentic systems. Let’s dig into some AI agent examples by industry, with specific use cases, that show how versatile this technology can be.

Open Universities Australia (OUA) is focused on making education more accessible for Australians. Reaching a broad audience, however, makes it harder to create personal experiences. OUA saw AI as a way to change that.

OUA partnered with LivePerson to create an agentic tool that can engage with new students, handle inquiries with empathy, and provide warm, humanised conversations. Here’s what they achieved:

• Student engagement: OUA’s AI agent mirrors the tone of student advisors, delivering thoughtful, empathetic responses to support students through the emotions of starting university.
• Personalised support: It gathers insights and shares custom summaries with advisors, helping them tailor conversations to each student.
• Efficiency: The agent handles early-stage queries, giving educators more time for high-quality, one-on-one support.

Despite the benefits, OUA had valid concerns about AI bias, hallucinations, and safety. To mitigate this, they put safeguards in place, including local data handling and rigorous testing, to make sure the system was safe for students.

With those concerns alleviated, OUA integrated a chatbot and freed up educator time to focus on higher-value tasks.

One of New Zealand’s largest telecommunications providers, One NZ, is using Agentforce and Data Cloud to power its transition to an AI-first telco.

With a goal to have 50 AI agents live by September 2025, One NZ has already deployed Agentforce to handle enterprise FAQs, log service cases, and respond to common enquiries like international roaming fees.

The long-term vision is even more ambitious. One plans to implement AI agents that proactively manage plan upgrades, offer device upsells, and book in-store appointments, all while surfacing customer insights to support personalised, end-to-end service.

- Jason Paris, Chief Executive Officer, One NZ

If you’re getting ready to deploy AI agents, here are some best practices to keep in mind.

Start by defining what you want to achieve with AI agents. Whether it's reducing response times, enhancing customer satisfaction, or cutting operational costs, having clear objectives will guide your implementation process and help you measure success.

AI agents rely on high-quality data to function effectively. Ensure that you have robust data collection and management systems in place. This includes customer interaction data, transaction histories, and other relevant information.

Select the type of AI agent that best fits your needs. For instance, a reactive agent might suffice if you need an agent to handle routine customer queries. Consider a goal-oriented or learning agent that can adapt to changing customer needs and provide more sophisticated support for more complex tasks.

Seventy per cent of ecommerce leaders say poor data integration and harmonisation is a major or moderate challenge when adopting AI.

To mitigate this, ensure your AI agents integrate with your existing CRM and customer service tools. This integration will enable a smooth flow of information and enhance the capabilities of your AI agents, allowing them to access relevant data and provide more effective support.

Design your AI agents with the end user in mind. Ensure that interactions are intuitive and responses are timely and accurate, providing a positive customer experience. Test your AI agents thoroughly to identify and address potential issues before deployment, ensuring they meet customer expectations.

Regularly monitor your AI agents' performance elements and gather user feedback. Use this information to continuously improve your AI agents, ensuring they remain effective and relevant. This ongoing optimisation will help you adapt to changing customer needs and improve the overall performance of your AI agents.

While AI agents can handle many tasks autonomously, it is important to plan for human intervention when necessary. Ensure clear guidelines for when and how human agents can assist, providing a safety net for more complex or sensitive interactions.

Implement robust data privacy and security measures to protect customer information handled by your AI agents. This includes compliance with data protection regulations and regular security audits to safeguard sensitive data and maintain customer trust.

If you're looking to integrate AI agents into your customer service strategy, Salesforce Service Cloud can help. Here’s how:

• Intelligent AI agents: With Agentforce, you can automate tasks, offer 24/7 support, and resolve cases faster using real-time, trusted data.
• Data-driven personalisation: Integrated with Data Cloud, agents can access complete customer data to deliver accurate and personalised responses.
• Scalable and secure: Built on the Salesforce Platform, Service Cloud supports high volumes while maintaining performance and reliability.
• Customised to your needs: Use MuleSoft to tailor your workflows and connect them with your existing systems.
• Easy integration: MuleSoft's open architecture makes it simple to plug into your tech stack.

It's an exciting time for business owners. The adoption of AI agents represents a significant turning point. Automating tasks used to rely on predefined input from human users, but now, AI agents can perform tasks and learn with minimal intervention.

As machine learning, large language models (LLMs) and natural language processing (NLP) tools develop, so too will their ability to learn, improve, and make more informed decisions.

We can expect faster decision-making, more productivity and more space for experts to focus on high-value processes.

With all these new AI developments, introducing autonomous agent models at scale can seem like a daunting task. That’s why we created Agentforce, the fastest and easiest way to build AI agents. And you don’t have to be an IT professional to build them. Simply describe what you need it to do, using natural language, and Agentforce does the rest. Try Agentforce today.