AI in Customer Support: Why Pre-Built Tools Are Falling Short in 2025

Artificial intelligence (AI) has been improving customer support operations for a while now. Even conservative companies are starting to dip their toes with off-the-shelf AI-powered tools like Zendesk AI. However, they soon find out these pre-built tools are generic and rigid. While they can provide quick wins like lowering support tickets in the short term, they lack flexibility, struggle with complex workflows, and fail to scale as businesses grow.

There’s another group of more adventurous companies that are leveraging advanced engineering technology, which in 2025 is easily accessible basically to anyone, and are jumping in the new trend: building their own in-house AI-powered tools using AI agents.

But what’s an AI agent? Isn’t that level of tech reserved to corporations with an enormous and expensive AI engineering team? The truth is that nowadays, building AI is possible for anyone.

Unlike regular software that just follows fixed instructions, an AI agent is an intelligent and dynamic technology that can observe, understand, and take action based on what’s happening around it. It can process information, adapt over time, and even make predictions.

But basic chatbots ≠ intelligent AI.

Many companies assume they’re getting AI when they buy a chatbot, but basic chatbots are not intelligent AI agents.

The difference? Chatbots follow scripts. Chatbots built on custom AI agents understand, adapt, and act intelligently.

• Chatbots = Rule-based, limited responses
• AI Agents = Context-aware, continuously improving

For example, basic chatbots fail when customers ask anything outside of a predefined script.

Instead of having a chatbot that only spits out pre-written answers, an AI agent can actually understand what customers are asking, pull the right information from your own knowledge base, and even learn from past interactions to improve over time.

In 2025, building an AI agent is within reach to anyone thanks to easy to operate, low-code AI builder platforms like BotDojo (anyone who’s curious enough to try it will understand how to use a platform like BotDojo –but you can request a demo of the tool here).

Building in-house AI agents is also a cheaper alternative to purchasing generic software from corporations with a big name that accounts for half of the price of what you’re getting.

With AI builder platforms, for example, your customer support business can build its own AI agent-powered chatbots, 100% customized to your unique workflows, knowledge bases, and customer interactions. As a result, with the properly customized AI-powered tools doing exactly what you want them to do, you’ll automate intelligently, ensure accuracy, and maintain full control over customer experiences.

What Customer Support Companies Are Already Achieving With Custom AI Tools

Here’s how big, medium, and even small companies are using AI in customer support today, and why custom-built AI agents are a better alternative to generic solutions:

• AI-Powered Chatbots & Virtual Assistants

Many companies deploy AI chatbots to handle common customer inquiries, such as order tracking, password resets, and troubleshooting basic issues. This reduces ticket volume and improves response times.

But while there are many ready-to-deploy pre-built solutions, what you usually get is basic chatbots that rely on predefined scripts and lack true contextual understanding. They can misinterpret user intent, provide generic responses, or fail to handle unexpected inquiries, which can frustrate customers rather than helping them.

With their own custom AI agent, support companies can:

• Build AI that understands business-specific workflows instead of relying on generic scripts.
• Provide source-cited, context-aware responses to ensure accuracy and trust.
• Seamlessly escalate complex inquiries to human agents without breaking the customer experience.
• Continuously train and refine AI models based on real interactions, improving over time.
• Maintain full control over brand voice, response tone, and AI decision-making, rather than being limited by third-party AI logic.

• AI-Powered Knowledge Bases & Self-Service Portals

Support companies are turning hundreds of pages into AI-enhanced knowledge bases that allow customers to find answers without even needing to contact support. AI can suggest the most relevant help articles based on user queries, improving self-service efficiency and deflecting unnecessary tickets.

The problem? Pre-built AI knowledge bases often pull from static, outdated documentation stuck in time. If knowledge isn’t maintained, AI tools may provide irrelevant or misleading answers, reducing customer trust.

Why custom tools built on AI agents are better:

• Instead of pulling from a static library, AI agents continuously analyze customer interactions and identify documentation gaps, keeping knowledge bases accurate.
• Companies can customize how AI retrieves and presents information, ensuring responses are both relevant and aligned with brand tone.

Learn about how BotDojo helped Miva build a reliable AI-powered knowledge base here.

• AI-Driven Email & Ticket Categorization

Manually sorting and prioritizing support tickets in 2025 is inefficient and outdated. Support companies are using AI to analyze incoming support requests, categorize them by urgency and complexity, and route them to the right department.

The downside is that generic AI software typically misclassifies tickets, which can lead to incorrect routing, longer response times, and unnecessary escalations.

Building custom AI agents are better because support companies can:

• Train AI on historical ticket data to improve accuracy in categorization and routing.
• Use sentiment analysis and past interactions to prioritize urgent cases automatically.
• Customize AI workflows to assign tickets based on agent expertise, reducing escalations.
• Ensure AI improves over time by learning from resolution patterns and customer feedback.
• Adapt AI logic to handle company-specific escalation paths, preventing misrouted tickets.

• Customer Sentiment Analysis & Predictive Support

AI-powered sentiment analysis helps businesses understand customer emotions during interactions. Now support companies can use AI to detect frustration, identify recurring pain points, and alert support teams before small issues turn into major complaints or churn risks.

However, generic tools not built for this purpose can misinterpret human emotion, especially when dealing with sarcasm, industry-specific language, or regional nuances.

With your own custom AI agent, support companies can:

• Train AI to understand industry-specific sentiment trends, reducing false positives.
• Analyze real-time customer interactions and flag at-risk customers proactively.
• Provide actionable insights to support teams, allowing them to intervene before issues escalate.
• Use AI-generated reports to track customer satisfaction trends over time.
• Incorporate business logic and historical data to improve predictive accuracy and reduce churn.

• To Assist Live Agents Without Replacing Them

AI isn’t just for customer-facing chatbots. It can also assist your human support reps in real-time by suggesting responses, retrieving relevant data, and automating repetitive backend tasks.

However, many off-the-shelf AI assistants provide generic recommendations that don’t align with the company’s processes, forcing agents to manually verify AI suggestions.

With your own custom AI agent, support companies can:

• Build AI copilots that analyze customer history and past interactions to suggest better responses.
• Automate note-taking and case summarization, saving agents time on documentation.
• Provide real-time resolution suggestions based on similar past cases.
• Integrate AI directly into CRM and helpdesk systems for seamless data retrieval.
• Ensure AI-generated recommendations align with company policies and service guidelines.

AI is a powerful tool, but its true potential lies in customization. Off-the-shelf AI tools often fall short because they aren’t built for the specific set of needs of your company.

If you’re curious about building AI support agents tailored to your own workflows, internal data sources, and unique business objectives, BotDojo is here to support your in-house team with pre-built workflows and templates readily available for your customization. You can start building AI agents in a matter of hours!

Write down your questions for one of our experts and book a demo here.

The Cons of Using AI in Customer Support (And How to Overcome Them)

As you can see, AI has the potential to transform customer support, but when implemented incorrectly, it can cause more problems than it solves.

When your AI tools aren’t properly implemented or you’re using solutions that promise to deliver for everybody, you can create frustrating customer experiences, security risks, and unreliable automation.

Here are some of the biggest downsides of AI in customer support, and how the right AI strategy overcomes them:

1. AI Can Get Answers Wrong (If It’s Not Built Properly)

AI tools sometimes hallucinate answers. They may pull in irrelevant, outdated, or even completely incorrect information. Off-the-shelve generic AI tools are especially unreliable because they don’t understand YOUR business rules, documentation, or tone of voice.

Here’s how to fix it:

• Build your own AI agents and train them on company-specific data rather than relying on generic language models.
• Implement source-cited AI responses to ensure customers always get accurate, verifiable answers.
• Continuously evaluate AI performance with built-in monitoring tools that detect and correct misinformation.

When you build AI agents with BotDojo, you don’t have to worry about inaccurate or misleading AI responses. BotDojo’s built-in evaluation framework automatically verifies responses, flags hallucinations, and improves AI accuracy over time.

Unlike generic AI chatbots that simply generate responses, with BotDojo, you can build AI agents that automatically evaluate AI outputs, flag inaccuracies, and refine responses over time. This means your AI agents will continuously improve with every interaction, and ensure customers receive reliable, fact-checked answers, not random AI-generated guesses.

By choosing BotDojo as your AI agent builder platform, you’ll be building AI you can trust. We want to show you how. Book a free demo of BotDojo here.

2. AI Can Sound Robotic and Frustrate Customers

Customers don’t want to talk to a cold, scripted chatbot. When AI tools fail to understand intent or handle complex requests, customers end up escalating more tickets, driving up support costs.

Here’s what you can do:

• Build AI agents that understand context and can engage in natural conversations.
• Train AI to detect frustration and escalate seamlessly to a human when needed.
• Regularly update AI models based on real customer interactions to improve accuracy over time.

3. AI Tools Are Hard to Integrate

Many AI platforms require complex engineering work just to connect with existing CRM and support systems. Businesses that rely on pre-built AI tools often find themselves stuck in a rigid system that doesn’t work with their existing workflows.

This is the solution:

• Take matters into your own hands. Use low-code AI builders and build and integrate your own custom-built AI apps to your favorite tools.

By building your in-house AI-powered tools, you’ll ensure they are compatible with your own CRM, helpdesk, and ticketing platforms for smoother adoption.

Building In-House Custom AI Is Easier & More Affordable Than You Think

Many businesses assume that building custom AI agents is expensive and complicated. That may have been true a few years ago, but in 2025, low-code AI agent builder platforms like BotDojo make AI customization accessible to any support team.

Here’s why building your own AI tools is more cost-effective than buying pre-built solutions:

• You’re not paying for a brand name. Many off-the-shelf AI tools come with huge price tags just because of the company selling them. When you build in-house, you pay for functionality, not branding.
• You only build what you need. Off-the-shelf AI tools bundle features you may never use, but when you build your in-house tools, you choose exactly what your AI does, keeping costs low.
• Faster ROI with AI that actually works for your business. AI agents that align with your workflows deliver value faster, leading to higher efficiency, better CSAT scores, and lower operational costs.

If you’ve been relying on pre-built AI tools that don’t quite fit your needs, now is the time to consider building your own AI-powered support solutions. With platforms like BotDojo, creating AI agents is easier, faster, and more affordable than ever.

Ready to start? Request a demo here and see how easy it is to build AI support agents that actually work for your business.