AI customer experience platforms help teams remain efficient as operations scale. Compare leading options for B2B teams with complex needs.
A logistics customer wants a delivery update, but the customer support team is slammed and the email sits in the queue. By the time the reply goes out, the delivery deadline has passed.
An AI customer experience platform reduces these delays. These platforms combine AI assistants, automated workflows, and analytics so teams move faster. In this scenario, a chatbot could have given the customer a real-time delivery update while flagging the approaching deadline to the support team.
Automation isn’t a magic bullet, though. In Front’s State of Service Expectations report, 58% of professionals said they believe AI can improve customer service, yet 80% think AI struggles to solve problems on the first try.
And some AI tools automate the interaction without preserving context, ownership, and follow-up, creating extra work for B2B teams. Front’s Coordination Tax report found that the typical B2B company spends nearly three hours coordinating for every hour spent solving customer problems.
That’s why it pays to choose an AI customer experience platform that fosters coordination rather than over-relying on automation. Compare leading customer experience platforms and find out what to evaluate beyond an AI feature list.
5 leading AI customer experience platforms
When comparing examples of customer experience platforms, it’s clear each one has a different way of using AI to improve the customer experience. The right one depends on your operating model, your customers’ needs, and the systems you already run.
1. Front
Front offers an open customer operations platform where your team and AI agents do customer work together. Instead of betting on one vendor’s agent, you run the mix that fits your operation.
Front’s custom Autopilot agents are built for cross-team customer work — configure them by team, brand, or process. Prefer to bring your own AI? Front also connects external agents like Claude, Codex, or Decagon and treats them like teammates, giving them the customer context, clear ownership, and performance data they need to work alongside your people. Smart QA and Smart CSAT run quality and satisfaction analysis on conversations automatically, so you can see how well both humans and agents are performing.
Front is built for B2B companies that manage high volumes of conversations, often with multiple stakeholders.
2. Zendesk
Zendesk’s AI customer experience technology sits inside an omnichannel ticketing system built to handle high volumes of support tickets.
Its AI copilot predicts customer needs and drafts recommended responses to help support teams work faster. You can also use Zendesk AI agents that resolve issues autonomously and learn from every interaction.
Zendesk is a strong fit for large B2B or B2C companies that want to gradually automate parts of their customer service within conventional ticketing workflows.
3. Freshdesk
Freshdesk’s traditional help desk software features the company’s AI tool, Freddy AI.
Freddy AI can autonomously resolve many queries across support channels, email, Slack, and Microsoft Teams. For issues that human service representatives are handling, Freddy AI Copilot can assist with conversation summaries, translations, and suggested replies. Freddy AI Insights alerts team leaders about evolving issues like volume spikes or potential service-level agreement breaches.
Freshdesk works well for companies that need a straightforward help desk with extensive AI features.
4. Fin
Fin (formerly known as Intercom) is a single AI agent that works across the entire customer journey, from sales and onboarding through ongoing customer service.
It’s designed to be highly autonomous even for complex workflows, while still giving teams direct control of the tool’s behavior. Fin can take actions like updating accounts, processing payments and refunds, and answering questions. It also integrates with more than 50 systems, including apps like Shopify, Salesforce, and Jira.
Consider Fin if you want a highly automated, AI-first platform in which the AI agent is designed to resolve most customer issues.
5. Salesforce Agentforce
Salesforce Agentforce is an AI extension for the Salesforce ecosystem, which includes sales, customer service, customer relationship management (CRM), and other software systems. Agentforce gives customers instant answers and generates personalized responses by drawing on CRM data.
Salesforce Agentforce is a good choice for large enterprises that already use Salesforce for sales, marketing, and customer service, and want to add an AI agent that works with all those systems.
What to look for beyond the AI feature list
Many examples of AI customer experience boast a long list of features, but the best choice isn’t necessarily the option with the most capabilities. The right tool depends on the level of automation and context you need based on your team’s operations. Here’s what to weigh.
The right level of AI autonomy
Kevin Yang, Front’s head of AI, believes that customer trust in AI-powered self-service will grow, but human service representatives will remain essential for more complex issues. To ensure your team still controls those trickier issues, make sure your chosen platform supports an appropriate level of automation.
Maximum automation can boost efficiency, but teams still need to define when an AI agent hands off to a person. A logistics firm might automate simple status updates and delivery queries while requiring a handoff for complex, multi-team issues. Without thoughtful handoff logic, automation hurts the customer experience instead of helping it.
Connected systems and channels
AI tools need customer context to solve problems. Front’s Coordination Tax report found that 48% of operations leaders want AI tools to understand context across teams and systems.
Before joining Front, Kevin Yang ran a food delivery company, EAT Club, that got a flood of order-status questions around lunchtime. Answering even a simple one meant checking the order system, the restaurant, and the driver — exactly the kind of connected, cross-system context an AI platform needs to actually save time.
Reliable ownership and context
Handoffs are where AI-driven workflows most often break down. The Coordination Tax report found that 71% of AI-using B2B companies have experienced a significant AI issue, including additional coordination work (24%), lost handoff context (22%), and incorrect routing (20%). Look for a platform that keeps handoff ownership clear and preserves context all the way through.
Quality and resolution visibility, beyond speed or deflection
An AI chatbot answering a question doesn’t mean the customer had a good experience. Some platforms make it easier to monitor the quality of each interaction and keep the experience consistent.
One way to measure quality is with Front’s AI Experience Impact Score, a metric that incorporates accuracy, customer effort, and the smoothness of a handoff. This is just one example of AI customer experience metrics, but the general goal is to measure customer experience regularly and adjust workflows depending on what the data shows.
Integration abilities
When it comes to integrations, more isn’t necessarily better. When evaluating different platforms, look for relevant integrations you can use to bring external context into the platform. That might mean shipment tracking info, order status, contract information, invoice details, project updates, or inventory levels. With the right integrations, your agentic AI platform can access all the data required to answer customer questions accurately.
How Front keeps AI in sync with the work around it
The best AI customer experience platforms keep conversations connected to customer context, with clearly labeled ownership at every step. No matter which platform you choose, its success will depend on whether you strike the right balance between automation and human decisions.
Front’s agentic platform automates routine requests, assists with finding information during involved conversation, and provides automatic reporting. Uber Freight uses Front to expedite routing and escalation, and its team members rely on AI Summarize to understand long threads quickly. The company’s support operation now works more efficiently, with email response times improving by 50% compared to before using Front.
Watch this video to see how Front AI works in practice:
Book a demo to see how Front improves your support workflows.
FAQ
How do you measure the success of an AI customer experience platform?
Track customer experience metrics like response time, resolution time, customer effort score, and CSAT.
How do you implement an AI customer experience platform?
Gradually automate workflows using AI features, test the results as you go, and make sure that you have the coordination and context you need to provide a positive customer experience.
What customer work should teams automate first?
Start by automating repetitive tasks like status updates and frequently asked questions. Make sure complex or sensitive questions are routed to human teams.