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    What Can Contact Center AI Solutions Really Do in 2024-1

    What Can Contact Center AI Solutions Really Do in 2024?

    What Can Contact Center AI Solutions Really Do in 2024?

    Contact center AI solutions are here, and they’re already being used across pretty much every industry. In the past, call centers have had to deal with all kinds of issues—high interaction volumes, unpredictable staffing needs, rising customer expectations, and persistent agent attrition, to name just a few.

    While there have always been ways to overcome these challenges, there has never been a one-size-fits-all solution. But with the advent of generative AI, companies may be able overcome all of these challenges and more—if they nail the implementation.

    A ton of noise surrounds AI technology, from the promise of game-changing customer service to the scary prospect of alienating your employees. Is artificial intelligence really worth all the hype? Let’s jump in and find out.

    What are the key uses of AI contact center solutions?

    Powering speech analytics and predictive analytics

    Starting off our list, speech analytics isn’t a new piece of technology. However, modern contact center AI solutions are taking it to an entirely new level, as they’re capable of transcribing and analyzing customer calls in real-time.

    AI tools can analyze agent interactions and comprehend customer intent, monitor agents to ensure they adhere to scripts, and even automate customer sentiment analysis. They can paint a picture of the customer’s mood, based on tone, language, vocabulary, and more.

    This data is used for more than just analyzing speech patterns, though. AI-powered analytics tools can gather and analyze interaction data in various ways to support data-driven decision-making for your business.

    For example, they can pinpoint specific moments where CSAT scores may suffer based on the customer’s tone and emotions. Using this information, you can adjust that agent’s training to prevent similar instances in the future, and find common patterns so you can update call scripts to avoid repeat issues.

    AI analytics tools have uses beyond what happens within the calls, too. Using predictive analytics, you could identify customers on the verge of churning and intervene with a bespoke offer to keep them on board.

    Predictive analytics can also be used to track activity on a per-customer basis (for creating personalized experiences) or on a wider scale to help forecast demand and staffing needs.

    Deploying conversational AI and virtual agents

    Naturally, AI is also being used to power chatbots, one of the first large-scale uses of GenAI in call centers. These advanced conversational AI bots can interpret text and customer sentiment and, like with voice analytics, they can do much more when directly connected to the customer.

    You can use contact center AI solutions to deploy chatbots and virtual agents capable of handling a wide variety of everyday interactions, so human agents are free to handle more complex issues.

    Virtual agents can draw from your internal knowledge center and personalize each interaction based on historical data, customer behaviors and preferences, demographic information, and more.

    Intelligently routing calls

    As we’ve discussed previously, contact center AI can build atop your existing automatic call distributor (ACD) to add even better functionality.

    AI-powered routing can analyze and interpret customer issues and direct them to the appropriate agent or department. It uses sentiment analysis and speech analytics to understand the problem, the customer’s personality, and past interactions, in order to direct the call.

    This functionality not only helps reduce the number of times customers have to repeat themselves—which 61% find frustrating—but also impacts other metrics. Wait times can be lowered when AI solutions are added, plus they can lower hold time and average handle time (AHT), too.

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    Coaching agents in real-time

    Coaching opportunities are essential to improving the customer experience, but they’re usually limited to the times when your agents are free from their customer support duties. However, by implementing call center AI solutions, you can deliver feedback even while a call is in progress.

    AI can analyze agent interactions in real-time and offer guidance during the call. If you train your AI tools on your internal knowledge base and documentation, they can even provide suggestions and insights by analyzing the conversation and pulling up relevant information for agents.

    Paired with sentiment analysis and speech analytics, these AI tools can go one step further and notify management when a call is escalating, so they can intervene and prevent a negative experience before it happens.

    Auto-scoring interactions

    Automation goes hand in hand with contact center AI, and this includes the ability to automate your quality assurance processes. Using ‘virtual evaluators’, you can automatically review selected interactions and score agents based on predefined criteria, such as resolution, tone, product knowledge, and more.

    This dramatically cuts down the number of manual evaluations required, relieving the pressure on your QA evaluators so they can take a more detailed approach for the interactions that matter. Plus, it can help create feedback quickly, leading to faster coaching and overall process improvement.

    The combination of time savings and streamlined coaching can help your QA process become more objective and consistent, eliminating human bias and adding extra context to evaluations. And in compliance terms, the additional QA coverage offered by auto-scoring can help identify lapses so you can take corrective action.

    On top of this, most auto-scoring tools allow you to adjust the criteria to align better with your internal requirements, so you can create scoring models to target specific industries, scenarios, teams, and more.

    Analyzing 100% of conversations

    One of the biggest upsides of AI technology is the ability to analyze every single conversation that comes through your contact center, regardless of the communication channel. This opens up your teams to act on all possible coaching opportunities and identify trends and patterns within your interactions.

    These AI-powered insights also allow QA and training managers to create personalized programs for individual agents. That way, you can cultivate consistency among agents and ensure that they adhere to internal standards and compliance guidelines.

    In addition, this comprehensive analysis enables you to create a broad overview of your performance and the quality of your customer support. You’ll be able to identify common points and create targeted solutions in advance, ensuring a more positive customer experience in the future.

    Assisting QA evaluators

    Finally, the addition of contact center AI solutions can support and empower your QA evaluators by alleviating some of their manual workload. AI assist tools can automatically summarize and score interactions for typical attributes like resolution, sentiment, and empathy, giving the evaluator foundational insights that reduce time to score.

    The availability of these AI summaries improves existing workflows by reducing evaluation times and eliminating manual steps. Evaluators can assess agent performance at a glance and quickly pick out areas for improvement.

    What are the benefits of contact center AI solutions for QA managers and evaluators?<

    Increases efficiency and scalability

    The biggest benefit of using contact center AI solutions is the built-in automation, which can increase efficiency across virtually every aspect of your operations. These solutions automate menial tasks, such as data entry and after-call work, giving agents more time to actually help customers and solve problems.

    They enable your agents to get ready for the next call faster so they can focus their efforts on more complex customer issues. Your call center AI solution can filter out simple queries, leaving the issues that require a human touch for the human agents. This not only improves AHT and first call resolution (FCR) rates, but can also have a noticeable impact on CSAT scores.

    Plus, using these solutions can help your teams scale up or down as needed without hiring extra staff. You’re able to spin up additional resources to handle increased call volume, and the AI can also collect data and pass it on to the agent, speeding up the workflow and contributing to quicker resolutions.

    Reduces spending on contact center operations

    Naturally, adopting call center AI solutions can help reduce spending within your budget by assisting in a number of areas. Automation alone can save hours spent by human agents dealing with tedious labor like data entry. This frees up agents to handle complicated support issues instead of dealing with time-consuming routine questions.

    Additionally, leveraging AI for analytics can help you identify and predict the traffic flow of your contact center, giving you a better idea of how to staff your agents during peak times or periods of low interaction volumes.

    Gives access to advanced data insights

    You most likely already have some form of data analysis for your call center. However, adding AI solutions can expand the scale of your analytics far beyond what your teams can do manually.

    They’re able to identify trends and patterns in call volume, customer sentiment, and mood. This offers a way to analyze and point out areas for improvement within your workflows and even with individual agent coaching sessions.

    Not to mention, you can gain deep analytics insights from call center AI solutions, such as root cause analysis, personalization opportunities, and at-risk customers who may be about to churn.

    Enables real-time agent feedback

    With the speed and flexibility of contact center AI solutions, they can analyze calls in real-time and offer coaching and feedback to your agents while they’re still on the phone.

    This enables your agents to have more confidence when speaking to customers since they can see and apply the feedback immediately while it’s still fresh in their minds. It can also point out areas to improve on for next time.

    These tools are useful for identifying both strong and weak performance, giving agents a meaningful way to chart their progress over time. You can also recognize and reward this strong performance, to help reinforce positive behaviors and boost agent morale.

    Keeps QA scoring consistent and objective

    Without human bias being involved, call center AI solutions help make your overall QA evaluations more consistent and objective. This makes it a fairer process, giving agents confidence that their scores aren’t affected by bias or inaccurate analysis.

    This goes beyond just making it more convenient, it also ensures consistency across the board. Rolling out this type of functionality helps make sure that each team within your contact center falls under those same guidelines, which will trickle down into your overall CSAT scores, too.

    Improves agent experience and reduces attrition

    Adding AI tools doesn’t just improve your broader contact center operations, the benefits we’ve mentioned impact your agents on the ground floor too. Using call center AI solutions helps your agents identify their strengths and weaknesses in a simple and easily digestible manner, showing them what they need to improve on.

    Plus, it helps automate all the menial, repetitive work your agents need to complete in their day-to-day work. After-call work and data entry are no longer their concerns, instead they can focus on the meaningful part of the job: supporting customers and building relationships.

    This isn’t just a cool feature, it actively improves morale across your teams. Agents will have more energy and significantly less cognitive load when trying to perform multiple tasks at once, relieving their stress and boosting performance and job satisfaction. It can also help reduce the chance of burnout or agent churn in the long run.

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    Boosts CSAT and other essential KPIs

    Finally, integrating contact center AI solutions can significantly impact several metrics and key performance indicators (KPIs).

    With the addition of AI tools to your workflows, you can personalize customer interactions and gain key insights, as we’ve discussed before. However, they extend beyond these two outcomes.

    Leveraging these tools allows you to operate 24/7 and even provide multilingual support for global languages and regions. That way, your business can expand to a worldwide market and support all your customers whenever they need it without having to staff entirely new call centers.

    Not to mention that these tools can also help streamline processes too, such as with intelligent call routing, to help increase these metrics. All the features AI brings can impact your KPIs depending on your specific implementation.

    The virtual elephant in the room: Addressing common concerns about contact center AI

    It’s no secret that AI also raises awkward conversations about its impact as a whole. Will it put people out of work? Can AI be fully transparent about how it works, and how can we use it properly? Let’s explore.

    Agents fear losing their jobs

    Of course, the biggest question is: “Who’s going to get replaced first?”. 39% of customer support specialists are worried about AI replacing their jobs in the coming years.

    The best way to frame it is by showing them that AI is not a replacement, but a tool that can help them do their jobs more effectively. Call center AI solutions can allow agents to focus on more meaningful tasks and customer interactions, and even lead to greater upskilling opportunities.

    A great way to convey this is by running workshops and educating your staff on what these tools can do and how they can use them in their day-to-day work. One company was able to expand its call center to an omnichannel one with an AI solution, leading to a 40% reduction in the number of incoming calls and an increase to 80% for its call answer rate by simply offering SMS functionality.

    Customers worry that interactions will become impersonal

    Another common concern is that customers will no longer have a human connection when trying to resolve their issues. 81% of consumers said they wanted more self-service options, but only 15% of them were highly satisfied with the tools provided to them.

    Not to mention that nobody wants to deal with purely automated customer service. They can be clunky and inaccessible for those not used to them, or increase stress in already stressful environments.

    The best way to keep your customers happy is to show them that there will always be human agents and human oversight, ensuring that nothing gets left to pure automation. You can even let customers fully opt out of AI interactions and go directly to a live agent if necessary.

    Everyone is concerned about data privacy and security

    Another huge concern is keeping data safe and secure, whether it’s your own or your customers'. Contact centers already handle a lot of data, and adding AI analytics will only increase it.

    This means that it is your responsibility to keep it safe and away from prying eyes. It is essential to work with trusted vendors who have been vetted for their data privacy and ensure they adhere to important regulations like GDPR, HIPAA, and other industry-and region-specific legislation.

    You should also be transparent with your customers about how their data will be used. Explaining to them how you plan to use AI, and how you collect data and for what purposes, is a great way to show how it brings value while still emphasizing that you’re keeping their private information private.

    We’re all anxious about inaccuracy and bias in AI

    Finally, the biggest elephant in the room: Sometimes AI is just wrong.

    Tools like ChatGPT and Gemini are still incredibly new and immature as far as technology goes. They’re only as effective as the datasets they’re trained on, making them more susceptible to unconscious bias (such as how image generative AI tools are less likely to show persons of color), or “hallucinating” information that isn’t true.

    This means that whatever tools you do use, you need to have a close eye on them at all times. Establishing a process for humans to review your contact center AI solution’s output with regular audits is essential, on top of consistent monitoring and adjustment of your AI tech as time passes.


    AI is here to stay; there’s no way to put Pandora back in her box. It’s already had an impact on a variety of industries. Contact center AI solutions will continue to grow in popularity, offering a wide variety of benefits like in-depth analytics, conversational AI, real-time coaching and analysis, and more.

    But that doesn’t mean it’s a be-all-end-all solution. Integrating any AI tool into your organization needs to be done strategically, and it needs to fit the specific needs of your business. Otherwise, you can easily end up doing more harm than good.

    If you want access to purpose-built AI solutions, check out Scorebuddy. Our embedded AI integrates with leading tools such as Salesforce, Intercom, Genesys, and more, offering:

    • 100% interaction analysis
    • GPT-powered auto-scoring
    • AI assistance for evaluators
    • And more

    Request a personalized demo today for a sneak peek at the future of your contact center.

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      Will AI replace humans in the customer service industry?

      AI is increasingly used in customer service for efficiency and cost-effectiveness, handling routine inquiries and tasks. While AI may take over certain roles, it's unlikely to fully replace humans in the industry. Instead, AI and humans will work in tandem, enhancing customer service experiences by combining the speed and accuracy of AI with the nuanced understanding and empathy of human agents.

      How is AI used in customer service?

      AI is already used in many parts of customer service, such as conversational AI for self-service, intelligent call routing to streamline customer journeys, real-time call analysis to support and guide agents, automatic QA evaluations to reduce time to score, and more.

      As GenAI continues to evolve and businesses work with their own proprietary large language models (LLMs), it’s likely that we will see further implementation in contact centers. Additionally, as more organizations deploy AI solutions, more evidence of their efficacy will build, encouraging more companies to take the leap into AI-powered customer service.