What is AI? The Essential Guide for Contact Centers

In today's rapidly evolving digital landscape, adopting AI is no longer optional. It's essential for staying competitive—especially in sales, marketing, and service where it is currently most prevalent.

But this technology is new territory for everyone. In order to have confidence in AI—and choose AI tools you can trust—you need to have a fundamental understanding in place.

That's what this guide is for. It will lay down your foundational knowledge of AI so that you can chart out the right path forward for your business, your contact center, your professional career. 

Table of contents

• What exactly is AI?
• AI vs automation
• Types of AI
• Benefits of AI
• Stats about AI
• How to use AI for contact centers
• How to get started with AI

What exactly is AI?

AI stands for artificial intelligence. It refers to machines that can simulate human intelligence in different ways. For example, AI can:

• Learn from data
• Recognize patterns
• Use reasoning to make decisions
• Understand natural language
• Generate its own content
• Understand images
• And more

Unlike traditional computers and automation, AI can mimic more sophisticated abilities of the human brain. Image source

AI vs automation

People tend to use the terms AI and automation interchangeably, and they both bring benefits to your business, but the two are very different. In simple terms, automation performs the same tasks over and over in exactly the same way, while AI gets better at the task over time. It can also come up with its own tasks and insights.

Here are some simple examples of automation vs AI:

Coffee maker

• Automation: You program it to brew coffee at the same exact time every morning.
• AI: Coffee pot picks up on patterns and learns what time to make coffee on different days of the week, and what type of coffee to make, based on your behavior.

Thermostat

• Automation: You program it to set a specific temperature for certain times of the day or days of the week.
• AI: Learns your heating and cooling preferences over time and adjusts the heating or cooling of your home accordingly, also in accordance with weather patterns, optimizing energy usage.

Email

• Automation: You set up rules so emails automatically go into certain folders.
• AI: Picks up on your patterns and starts moving emails into folders on its own.

As you can see, automation cannot think for itself; it requires a human to define the tasks and the rules, and it will only ever do the assigned task. AI, on the other hand, can identify tasks and create rules on its own, based on observation and experience. And the more it performs the task, the better it gets at it and the more it can do.

Hatch automation vs Hatch AI

Now that you know the basics of automation vs AI, let’s look at how Hatch automation and AI work together for home service businesses and call centers.

Hatch automates your outreach to leads and customers. So rather than having to keep track of who needs what outreach and when, and then also creating and sending those messages every time, you only need to set up your audiences and message campaigns once, and then Hatch will automatically enroll contacts into those campaigns as they meet that criteria.

Whether you’re targeting new leads, quoted prospects, aged leads, or current customers, your outreach is on autopilot and all you have to do is jump in when the contact responds. This saves you time while increasing response rates and preventing missed opportunities. And it’s automation because you’re still coming up with the content for the message templates and determining the rules that define the audiences (Hatch makes this easy though, with our Audience Builder and campaign templates).

With Hatch AI, on the other hand, you can now add AI bots to campaigns that will actually conduct conversations with your contacts over text.

So while automation is handling your outreach and increasing response rates, AI is handling the conversations that result from the automated outreach.

Types of AI

No matter how you’re categorizing it—and there are many ways to do so—there are several types of AI. For example, AI has several different subsets. Here are some of the common ones, as well as examples to help you better understand each one.

• Machine learning AI: Can identify patterns based on data (e.g., email spam filters or recommendation engines like Spotify).
• Deep learning AI: Uses multiple layers of “neural” networks to process information and understand data on a deeper level (e.g., image recognition).
• Robotics AI: Can sense, interpret, and interact with its environment (e.g., self-driving cars).
• Natural language processing AI: Can understand and respond to conversational commands rather than needing coding or special formats (e.g., Hatch AI chatbots, Siri).

Hatch AI uses natural language processing, so you can give it instructions using everyday language, and it will also converse with customers this way.

In terms of application, AI also has three types: Generative, predictive, and prescriptive.

Let’s take a look at each one through the lens of a home improvement call center looking to set more appointments.

• Predictive AI uses data to make forecasts and predictions.
  
  
• Prescriptive AI makes suggestions and recommendations.
  
  For example, a CRM that analyzes historical appointment data, customer demographics, and lead characteristics and suggests strategies for targeting leads, timing your campaigns, or offering incentives.
  
  
• Generative AI comes up with its own content, like images, blog posts, chat messages, charts, and more. To learn more about this type of AI, head to our guide to generative AI.
  
  For example, with Hatch AI, you give it prompts and instructions, and it will come up with its own text messages to qualify leads and book estimates. 
  

Hatch uses generative AI, meaning you can give the bot prompts and it will generate text messages on its own. Learn more about how Hatch AI works here.

Needless to say, mixing and matching these different types of AI results in countless uses across every industry.

Benefits of AI

AI has several benefits to sales and service teams and call centers. Here are some of the many benefits from a sales, marketing, and customer service perspective.

• Boost productivity. Even with automation, business applications still require manual human work such as data entry and rule configuration. AI reduces this, allowing reps to get more done in less time.
• Improve the employee experience. AI can augment your agents’ performance, alleviate workload, and eliminate repetitive tasks so they can focus on more gratifying ones—all of which can help improve employee retention.
• Increase customer satisfaction: AI equips your business to provide quicker service, highly tailored interactions, convenient self-service options, and more—which is essential for retention, upsells, reviews, and referrals.

AI can help alleviate agent workload in several capacities. Data source

• Reduce costs: AI optimizes your call center, reducing costs associated with inefficient or insufficient operations, employee turnover, inaccurate data, and more.
• Drive revenue: Not only can AI provide the content, data insights, and suggestions to help you earn more revenue, but it also frees up your agents to focus more on creativity, strategy, and relationships—all of which are key to differentiating your business from competitors.
• Scale your business growth: Automation is the key to scaling, and with AI taking automation to the next level, scaling is that much better. For call centers in particular, it is paramount to delivering exceptional customer experiences at scale. (Plus, with Hatch, you can actually clone your AI bots!)

Hatch AI alleviates one of the biggest burdens for call centers: keeping up with incoming leads. 

Stats to support the benefits of AI

• Businesses can achieve a 29% reduction in customer service costs through AI chatbot automation.
• AI driven scaling can reduce customer service costs by 20-40%.
• AI data-driven companies outperform competitors in customer acquisition and retention by 23x.
• Contact centers that use a hybrid AI/human model deliver 3.7x more value than those that rely solely on AI or solely on humans. Balancing AI and live agents optimizes efficiency and maintains the human touch, aligning with customer preferences.
• AI improves agent productivity by up to 60% by providing real-time data, historical context, and recommendations.
• 72% of agents report that AI helps lessen their workload, alleviating burnout and enhancing satisfaction.
• AI-enhanced support can reduce call times by 10-20% and increase efficiency by 50%.
• It’s predicted that by 2025, AI-driven contact centers will handle 95% of customer interactions.
• Companies leveraging AI to augment human capabilities experience a 60% increase in customer satisfaction, outpacing competitors.

How to use AI for call centers

Given all its different types and subsets, there are infinitely many ways to use AI. We’ve talked about how home service businesses can use AI, but in this guide we’re going to focus more on the call center, which is focused on using AI for on sales, marketing, customer satisfaction, and administrative operations.

Converse with contacts

Until now, chatbots have been automated, which means a human has to program it with exactly what to say. AI chatbots, on the other hand, require initial configuration and then can converse with customers on their own, qualifying leads, booking appointments, answering customer service requests, and more. Hatch is one of many generative AI tools for contact centers.

Hatch AI bots can converse, qualify, and book appointments.

Lead & customer routing

AI can combine lead/customer information with employee information to identify the right sales rep for a lead or technician for a project. Not only does this save your schedulers or operations managers time, but it also enhances the success of the customer interaction. An example of this would be LeadAssign’s AI lead routing or ServiceTitan’s Dispatch Pro.

Copilots for agents

AI features within CRMs, communication platforms, and other business applications can provide real-time assistance to agents through coaching, response suggestions, surfacing needed information quickly, and more. This saves time with onboarding and coaching, and equips agents to provide better customer experiences.

TalkDesk Agent Assist is a great example of an AI copilot.

Data analysis

With automation, you can set up a platform to pull certain data for you. This saves time, but you still have to know what you’re looking for. AI, on the other hand, can analyze data, enrich it with other data sources, and generate insights, suggestions, and predictions. This helps with sales forecasting, transcribing conversations into bullets and action items, detecting customer sentiment, and the list goes on.

How to get started with AI

AI is rapidly becoming a regular part of everyday business applications. The faster you can educate yourself on it and start incorporating it into your business, the more closely you can align with both industry and consumer trends and future-proof your business. Here are eight steps for getting started with AI:

1. Educate yourself on AI: You don’t have to become an AI expert, but you do need to internalize enough knowledge so you can make informed decisions. Find a crash course from a resource you trust, be it a YouTube video, ebook, or podcast (this guide is a great start!). Our AI vetting checklist is also helpful.
2. Pick your AI objective: Are you going to use AI for sales forecasting? Agent assist? Or talking directly to customers? Make sure you know what business objective you’re trying to achieve with AI.
3. Set clear, defined goals: Once you have your objective, you can figure out what you’re going to measure and then set goals. Examples of goal areas you might focus on include customer pain points, the customer journey, or performance benchmarks.
4. Add one tool at a time: This will allow you to see exactly how the addition is impacting your business. Adding too many at once will muddle your process and make result allocation nearly impossible.
5. Adjust your metrics: With AI alleviating the quantitative burdens of your agents, they can focus on qualitative objectives, so you may need to shift your metrics to be more quality-focused. Your calls per hour might shift to appointment set rate, for example.
6. Assess your IT infrastructure: Make sure your existing tools and software can integrate with AI. We recommend cloud-based solutions as they can accommodate new technology and scale with your business.
7. Train your agents: Train your agents on how to use the AI tool, the value of the AI tool, and show them why AI isn’t replacing them, but rather is empowering them to perform better. You may also want to do prerequisite education on the value of AI in general.
8. Be transparent: AI has come into the world and evolved rapidly, so there are security and ethical concerns. Having full transparency and awareness around these topics as you move to implement AI will reassure your customers and your team moving forward.

Understanding AI is the first step

As you can see, AI can be used both internally to help your agents carry out their roles as well as externally by interfacing with customers. It can act as a copilot, a coach, perform tasks for you, and even perform tasks humans can’t do.

The use of AI is a top contact center trend that is rapidly gaining momentum. But in order to start implementing it, you need to have confidence in it. And in order to have confidence in it, you need to understand it. 

Hopefully this guide has given you the fundamental understanding you need to confidently move forward with AI in your business and/or career.