Artificial intelligence (AI) is revolutionizing the way companies handle customer support, promising improved efficiency, lower costs, and enhanced customer experiences. If your manager has asked you to evaluate AI for customer support, you likely have many questions: What should you look for? How do you measure success? What tools exist in the market? This guide will walk you through a structured approach to evaluating AI in customer support to ensure your company makes the right decision.

Understanding the Role of AI in Customer Support

Before diving into the evaluation process, it's essential to understand how AI is used in customer support. AI can power a variety of support functions, including:

• AI chatbots: Automated bots that handle customer inquiries without human intervention.
• AI-powered customer support: AI enhances traditional support by providing recommendations to human agents.
• Agent assist AI: AI suggests responses and actions for human agents, improving efficiency.
• AI helpdesk solutions: AI integrates with ticketing systems to manage and categorize support requests.
• Generative AI for customer experience: AI can generate personalized responses and insights based on past interactions.

For more insights, check out Harvard Business Review’s analysis on AI in customer support.Step 1: Define Your Business GoalsBefore selecting an AI customer service software, identify what your organization aims to achieve with AI. Common objectives include:

• Reducing support costs through automation.
• Improving response times with AI chatbots.
• Enhancing customer satisfaction (CSAT) scores.
• Increasing ticket deflection rates to reduce agent workload.
• Supporting agents with AI-powered suggestions.
• Providing 24/7 support to customers across time zones.

Step 2: Identify Key AI FeaturesNot all AI support tools are created equal. Evaluate AI solutions based on the following key features:

• Natural language processing (NLP): Enables AI to understand and respond in a human-like manner.
• Integration capabilities: Seamless integration with your existing CRM, helpdesk, and customer service AI software.
• Agent assist capabilities: AI providing real-time recommendations to agents.
• Automation and deflection tools: AI-driven chatbots that can resolve common issues without human intervention.
• Multichannel support: AI should work across live chat, email, social media, and voice channels.
• Analytics and reporting: Insights into AI performance, customer interactions, and ROI.

For a deeper understanding, refer to McKinsey’s report on AI in customer service.Step 3: Research AI Vendors and TechnologiesThere are numerous AI customer support chatbot providers, and choosing the right one requires thorough research. Some well-known AI-powered customer support solutions include:

• Google Agent Assist: Provides AI-driven support suggestions to agents.
• Zendesk AI: Offers AI-powered customer service automation and insights.
• Freshdesk AI: Automates ticketing and chat support.
• IBM Watson Assistant: A robust AI chatbot customer service solution.
• Drift and Intercom: Focus on AI-driven conversational experiences.

Considerations When Choosing a Vendor

• Scalability: Can the AI solution scale as your company grows?
• Customization: Does it allow customization to match your support workflows?
• Security and compliance: Does the AI adhere to industry regulations?
• Cost-effectiveness: What is the ROI for AI in customer support?

Step 4: Measure the Success of AI ImplementationOnce AI is deployed, it’s important to track its impact. Key performance indicators (KPIs) to monitor include:

• Deflection rate: The percentage of tickets handled by AI without human intervention.
• Customer satisfaction (CSAT) score: How AI impacts customer experience.
• Average handling time (AHT): Whether AI reduces the time required to resolve issues.
• Ticket resolution rate: The percentage of issues resolved by AI.
• Agent efficiency: How AI improves agent productivity.

For best practices, explore Forbes’ insights on AI and customer service metrics.Step 5: Conduct a Pilot TestBefore fully committing to an AI-powered customer service solution, run a pilot test. A pilot allows you to:

• Assess how AI interacts with customers.
• Identify any gaps in AI’s ability to resolve issues.
• Gather feedback from customers and support agents.
• Evaluate whether the AI aligns with your business goals.

Step 6: Optimize and IterateAI in customer service is not a set-it-and-forget-it solution. Continuous optimization is necessary to improve performance. Regularly:

• Train AI models with new customer data.
• Update knowledge bases to enhance AI responses.
• Analyze AI analytics to refine workflows.
• Collect feedback from customers and agents for further improvements.

Step 7: Get Leadership Buy-inSecuring internal buy-in is crucial for AI adoption. Present the business case to leadership with:

• Data-backed insights: Show the impact of AI on ticket deflection and support costs.
• Case studies: Share success stories from other companies using AI in customer support.
• ROI calculations: Demonstrate the cost-benefit analysis of AI investment.

Final ThoughtsEvaluating AI for customer support requires a structured approach, from defining goals to selecting the right AI-powered customer service solution. AI can enhance efficiency, reduce costs, and improve customer satisfaction—but only when implemented strategically. If done correctly, AI can become a valuable asset for your customer service operations, helping your team focus on complex issues while AI handles repetitive tasks.For further reading, explore resources from Gartner, Forrester, and IDC on AI in customer support trends.