AI Integration Made Easy: How to Seamlessly Incorporate AI Into Your Existing Systems

While looking for the ways to transform client interactions and boost operational efficiency, managers more often come to the solutions of AI tools implementation. The process of tools’ integration with such Customer Relationship Management (CRM) systems as Zendesk and Freshdesk can seem complicated.

Often, managers feel unprepared, inadvertently capping their potential and leading to underperformance. The following article addresses common concerns around AI integration and shares successful case studies to illustrate its impact.

Addressing Common Business Objections

Despite understanding the importance and benefits of AI tools usage, many businesses face a number of stoppers that influence their decisions. The most common ones are the following:

Technical difficulty

Many believe that integrating AI tools with current CRM systems require complicated technical knowledge. However, in reality, modern virtual assistants, such as CoSupport AI chatbots, and other AI tools are user-friendly. They have a customizable architecture that can be adjusted to almost any goal or process. It is easier and cheaper to use the already available modules without changes, but the customization brings more benefit to a company in the long run.

Comprehensive documentation and support are always available to ensure seamless AI onboarding. The vendors of AI services usually provide plug-and-play capabilities, which decreases the need for technical knowledge or expertise of the end users. Finally, pre-built connectors for popular CRMs are usually available to make integration quick and seamless.

High expenses

The second barrier is cost. Initial expenses are high, but the long-term benefits outweigh any spendings. With the help of AI, routine tasks are automated, and operational expenses are reduced. The customer satisfaction increases, leading to a higher return on investment (ROI). Finally, the market offers scalable pricing models, allowing companies to start with small expenses and then add additional services or features if needed.

Risks of disruption

Finally, business owners might have disruption fears. They think that AI implementation projects might require significant completion time, so the performance of customer support tools can be compromised. However, proper planning and phased implementation can minimize disruptions. It means that day-to-day operations can continue even during the active project implementation phase. Finally, companies can perform thorough testing in parallel before deployment to find all errors in advance and address them.

Step-by-Step Integration Guide

Integration process should start with a thorough assessment of current setup and CRM compatibility. It means checking existing workflows, defining goals and needs of AI, and estimating potential barriers. This step should end with the development of a detailed plan, comprising a scope, timeline, resources, and responsible persons.

Then, the selection of the right AI tool follows. Key factors to look at are ease of integration, support, scalability, and cost. The examples can be Zendesk’s Answer Bot and Freshdesk’s Freddy AI. Moreover, if you want to improve the efficiency of the work of AI for customer support solutions, consider automated ticketing, predictive analytics, and customer insights features to be included in a package.

Actual implementation consists of these steps:

  1. Configuration and installation: After the preparation phase, the installation of AI tools starts. It might require setting up APIs, configuring data flows, and customizing AI tools to satisfy specific business needs.
  2. Integration with CRM workflow: This step involves mapping AI functionalities to CRM, meaning automating ticket routing, using predictive analytics, and real-time customer support.
  3. Testing and monitoring: Controlling environment should be used for testing purposes. It helps identify potential struggles to ensure that everything is working as it should. After actual implementation, the monitoring phase helps to adjust the system where needed and ensure constant workflow.
  4. Support phase: It is somehow connected with monitoring but also includes staff training, as people should know how they can operate new AI tools, what benefits they generate, and what functionalities they have. Ensure vendor support to avoid possible disruptions.

Use Cases of Successful Integrations

Without real-life examples, it might be hard to believe in the benefits of an AI-CRM union. Here are some successful cases. Crosscard implemented Zendesk’s Answer Bot to improve the processing of customer support queries. It resulted in a significant reduction in operational costs and response time. Zendesk’s Answer Bot resolved around 10,000 questions by itself.

Another example can be taken from the Photobox company. It also chose Zendesk’s Answer Bot, and this AI tool was involved in 51% of conversations that previously required the use of human agents.

Finally, PhonePe, India’s digital payment platform, used Freshdesk’s Freddy AI to automate around 80% of client queries. The effect was a high level of customer satisfaction. These cases were not characterized by a long integration phase and disruption. It was achieved by means of proper planning, phased implementation, and successful testing.

Final Thoughts

The successful integration cases of PhonePe, Crosscard, and Photobox and minimal disruptions during implementation show that AI and CRM can work together and deliver good results. Some benefits include better customer satisfaction, higher performance, and improved efficiency of work. Addressing barriers and planning everything properly can make the AI implementation process fast and smooth. The key is to have a plan, choose appropriate tools, and ensure constant support and training of all involved specialists.