6 Generative AI Use Cases 2024: Real-World Industry Solutions

AI in Customer Service and Support: 5 Trends That Are Changing the Game

ai use cases in contact center

The contact center industry has experienced three distinct generations of AI & automation. Notably, make sure that the voice AI solution you choose gives you the freedom to consistently customize your bots, with developer APIs, integration options, and flexible frameworks. Going forward, we’ll see AI continue to evolve, and regulations will transform alongside it, driven by new discoveries, emerging customer concerns, and evolving risks.

ai use cases in contact center

Consider people up the business chain and give them confidence that the contact center can take the reigns of the project so it’s not imposed upon them later. As such, they need a blueprint for implementing conversational AI, and Cirrus – the CCaaS vendor that uses AI education as a core differentiator – is giving it to them. Now, large language models (LLMs) have wiped away much of that engineering – allowing contact centers to leverage these use cases more quickly and cost-effectively. Gartner research underlines this, finding that 47 percent of enterprise GenAI investment has focused on service – alongside sales and marketing. Across various environments, ElevateAI acts as a knight in shining armor, offering access to NICE’s premium Enlighten AI models without incurring additional legwork or cost. For instance, a healthcare or financial firm may turn to ElevateAI to parse all their interactions, ensure compliance, and satisfy internal standards.

You can foun additiona information about ai customer service and artificial intelligence and NLP. AI plays a pivotal role in self-service options within customer support, fundamentally transforming how customers access and receive support. By integrating AI, businesses can offer sophisticated self-service platforms that not only enhance the customer experience but also improve operational efficiency. One of the primary applications of voice recognition in customer support is in Interactive Voice Response (IVR) systems. Modern IVR systems powered by voice recognition can understand and respond to customer queries in natural language, making them more intuitive and user-friendly than the often irritating and time-consuming traditional touch-tone IVRs. Customers can speak their queries and requests naturally, and the system can guide them to the appropriate solution or service, reducing the need for human intervention and streamlining the support process. And I think about how data plays a role in enhancing employee and customer experiences.

ElevateAI’s purpose-built, proven APIs can provide a powerful starting point for organizations of any size to gain immediate benefits. However, these typically proved too expensive, too complex, or generic, with little-to-no contact-center-specific training. Moreover, they offer embedded AI to help guide and automate elements of these experiences.

“Here, GenAI plays a crucial role in analyzing vast amounts of contact center data to proactively identify root causes of issues,” he explains. Therefore, the vendor may gain much greater mindshare and – in the future – reaffirm its place as a leading candidate on more CCaaS shortlists. Indeed, Gartner estimates that – as of the beginning of 2024 – only 33 percent of on-premise contact centers have migrated to the cloud. For many contact centers, however, adopting ChatGPT this game-changing technology has been difficult due to the complexities of integrating AI with on-premises infrastructure. There must be an understanding and acceptance of where limitations may exist along with the identification of hurdles that must be overcome to take advantage of this revolutionary opportunity. As a result, companies will be better equipped to drive revenue growth, foster customer loyalty, and maintain a competitive edge in dynamic markets.

Voice Automation Catches Up with Digital Automation

At its most basic, the “AI-first contact center” rethinks existing processes and its customer access strategy based on the new opportunities that AI has created. It uses AI Agents as the first point of contact for all interactions on voice and digital channels and automation at scale to reduce manual work and deliver favorable outcomes and positive impressions. Customers should come away satisfied from interacting with an agent in an AI contact center, where it’s an AI Agent, or an AI-assisted human agent. The speed, consistency and convenience in turn boosts customer loyalty and retention while reducing the burden agents and increasing their satisfaction. Despite growing interest among many on-premises contact centers to expand their operations by adopting contact center as a service, most platform vendors are finding it difficult to become exclusive as-a-service providers. In fact, many businesses are discovering that a combination of on premises and as a service is producing more than satisfactory results.

So the way that they’re really handling that to give better customer experience, and to engage more with their customers, is focusing more on becoming customer-centric. Which are things like more personalization, being more data-driven, having greater availability for their agents. And all of these options that, for us as consumers, are really exciting because we can reach out to a business in many different ways at many different hours of the day, 24/7 access to get our questions answered. Augmented Reality (AR) and Virtual Reality (VR) are emerging as influential technologies in customer support, offering immersive and interactive ways to solve problems and enhance the customer experience.

The platform’s key features include Ai Recap for summarizing calls and meetings and Ai Playbooks for real-time and context-sensitive suggestions to agents. Dialpad also has robust transcription and sentiment analysis tools, giving instant insights from conversations and letting agents adjust as customer sentiments shift. AI analyzes data from various sources — including IoT sensors, historical performance records and user feedback — to predict when a product or service might fail or require servicing. By processing vast amounts of data in real time, AI can detect patterns and anomalies that human analysts might overlook. This proactive approach greatly enhances operational efficiency and improves customer satisfaction. Artificial Intelligence is currently being deployed in customer service to both augment and replace human agents – with the primary goals of improving the customer experience and reducing human customer service costs.

Additionally, the platform’s architecture makes it easily scalable, allowing businesses to efficiently manage demanding workloads and customer interactions as they grow. When you choose Cognigy, you get an AI workforce that drives operational ai use cases in contact center excellence and exceptional customer experiences (and a partner you’ll love to work with!). Advancements in other related technologies, such as augmented reality (AR) and virtual reality (VR), will likely come more to the forefront.

Their innovative software listens to conversations in real time and offers immediate feedback to agents, advising them on potential adjustments in tone, pace and conversational style. While the technology is still relatively new, it’s already significantly impacting a range of business processes. Generative AI offers contact centers a new opportunity to enhance customer experiences, boost efficiency, and transform employee productivity. For many contact centers, one of the biggest benefits of generative AI is the ability to create more powerful self-service experiences for customers. Generative AI solutions build on the ability of conversational bots and assistants powered by natural language processing and machine learning. Ultimately, AI customer support is rapidly progressing to deliver next-generation assistance that is anchored in empathy, efficiency and technology-forward solutions.

The Forrester Wave CCaaS leader then applies GenAI to monitor the trend in sentiment and alert the supervisor when it drops significantly. That final part is crucial, keeping a human in the loop to lower the risk of responding with incorrect information and protecting service teams from GenAI hallucinations. Imagine walking into your favorite coffee shop, and the barista knows your order without saying a word.

GenAI in Software Development

For example, a customer can create a digital version of themselves to try on clothes in a VR environment before making a purchase. This type of advancement might transform the way a customer interacts and connects with a business. The enterprise-ready generative AI platform delivers prematch summaries and postmatch analysis.

On audio and video calls, agent assist can instead sift through knowledge bases and data stores to show the agent the most relevant articles and insights in real time. Avaya announced it is partnering with The Beyon Group, a global leader in enterprise CX, to create the Avaya Communication & Collaboration Suite delivered through the Beyon cloud. As a result, the next time a customer interacts with a brand’s customer service department, their experience will be connected to their previous interactions, allowing agents to never miss a beat and help facilitate a seamless interaction. With AI solutions handling more repetitive tasks and queries, agents have more time to focus on valuable, strategic, and empathetic interactions. The ability for AI solutions to optimize self-service experiences is one of the biggest benefits of embracing AI in the contact center today. With solutions like Engage by Local Measure for instance, companies can take advantage of skills based call routing solutions that assign customers to agents based on their abilities and previous interactions.

  • Many contact center providers offer the capability to score conversations via sentiment.
  • These innovations, once the hallmarks of businesses at the cutting edge of technology, are now setting new standards for personalized, efficient and insightful customer interactions within the customer service industry and beyond.
  • This strategic use of data and technology illustrates the power of AI in customer experience and how it can keep companies competitive.
  • This means companies will need to ensure they’re informing customers when they’re interacting with virtual agents and chatbots.
  • CCaaS is a crowded market, with vendors announcing massive release waves, moving into adjacent markets, and rolling up competitors to differentiate and grow.
  • According to EU rules, companies will need to disclose which content is created by generative AI, publish summaries of data used for training, and design models to ensure they don’t generate unsafe or dangerous content.

This helps businesses to better understand customer needs and wants, paving the way for the creation of better products and services. It can also ensure companies have the insights they need to improve retention rates and reduce churn. In the evolving world of customer experience, companies can also leverage AI to build voice bots, capable of interacting with users over the phone through speech recognition. They can understand natural language, interpret intentions, and minimize call queues.

AI-backed systems and devices are proving to be better at analyzing human emotions, their tone and sentiments. Speaking of the lack of security and governance solutions offered by initial generative AI solutions, compliance will be a major focus area for contact centers in 2024. Throughout 2023, countless companies encountered the risks of using “bring your own AI” tools in the contact center. Additionally, many early-stage models lack the security, compliance, and governance components to protect businesses and their data. This has led to many startups, CCaaS innovators, and vendors producing specific models for the contact center. Though there are numerous use cases for these next-gen AI technologies, they appear particularly valuable for the contact center.

“As the market matures and contact centers gain a deeper understanding and confidence in the capabilities of AI, we’re expected to see an increase in external applications,” he predicts. “These types of bots are both much faster for brands to develop, and a lot more human to interact with as an end customer,” Caye says. “Here, the main challenge is helping the agent be more efficient, have more context, and get better coaching, – all of which can be addressed and improved with GenAI,” Caye notes.

Former Five9 CEO on GPT-4o: Hundreds of Millions In AI Agent R&D Just Became Obsolete

Call escalation — handing off a call to a more senior agent — can be handled manually. But the ability to automate call escalation using software reduces the risk of dropping a call due to human error during a handoff. This feature can also streamline workflows by automatically identifying the appropriate higher-level agent for an escalation and transferring the call accordingly.

ai use cases in contact center

Chatbots can also hand crucial information about a customer over to an agent when a conversation is escalated, reducing the need for a customer to repeat themselves. As AI solutions grow more advanced, with new algorithms and frameworks to explore, the use cases for AI in customer support are evolving. Today’s companies can leverage AI for everything from increasing conversions with proactive outreach, to generating responses for customer queries. Local Measure’s AI-powered tools in Engage, such as Smart Notes and Smart Tasks, offer an intuitive way to streamline daily workflows in the contact center, minimizing operational costs, and improving customer service results.

While many are familiar with AI for chatbots and basic data analysis, the real magic happens when you push the boundaries of creativity. Here are three use cases of AI in customer experience that can transform how businesses interact with customers. Generative AI solutions pose several security and safety challenges in customer service, mainly if they’re not implemented correctly. In the future, companies must implement more advanced strategies to control how employees use and train generative AI tools. Companies like Salesforce and Dialpad are producing generative AI copilots specifically tailored to the needs of customer service leaders.

These datasets are necessary for testing algorithms, training machine learning (ML) models, and evaluating new health technologies before implementation. With AI-generated synthetic data, healthcare organizations can safely and ethically explore innovations, upholding patient confidentiality while benefiting from realistic test environments. Hospitals and clinics can use generative AI to simplify many tasks that typically burden staff, like transcribing patient consultations and summarizing clinical notes. GenAI healthcare tools reduce the time clinicians spend on paperwork by pre-filling documentation and suggesting relevant updates based on patient data.

You can even use voice bots to enhance the employee experience, and boost productivity. For instance, “Agent Assist” tools can monitor conversations and send real-time guidance and directions to your employees and supervisors, boosting workplace efficiency. They rely more heavily on algorithms for natural language processing (NLP), text to speech (TTS), and speech to text (STT).

Instead of replacing staff members with automated bots, use the AI tools you implement to augment your workforce. Ensure your customers always have a way to opt-out of interacting with a chatbot, or escalate their conversation to a human agent. AI for customer support can come in many different forms, from voicebots and chatbots, to AI-enhanced analytical tools. The right technology for your business will depend on the specific use cases you’ve identified for artificial intelligence, and your requirements. With the Engage platform, companies can revolutionize their contact center experiences with intuitive solutions that augment agent performance, and improve customer satisfaction. Investing in predictive analytics enables businesses to minimize disruptions and build a smoother, more seamless customer journey.

CRM systems store a wealth of customer-related data, including contact information, purchase preferences, purchase decisions and any previous interaction touchpoints the business has had with the customer. Using this information, relevant CRM data can be intelligently fed to human agents or chatbots to provide additional context and predictive analytics recommendations as soon as a customer communicates with the contact center. Using generative AI (GenAI) in contact centers transforms the way organizations manage customer service processes by automating routine inquiries and providing real-time resolutions. This reduces waiting times and allows agents to build more meaningful interactions, significantly increasing customer satisfaction. The rise of multimodal AI in 2024 will help businesses implement generative AI tools to deliver a more consistent experience across various channels.

Sentiment analysis can help supervisors identify in real-time which calls require escalation or further support and AI tools can summarize calls and automate note-taking to free up agents to focus more closely on customer needs. These use cases not only improve customer and employee experiences but also save time and money. In customer support, predictive analytics can identify patterns and signals that indicate potential problems or opportunities. For example, it can analyze past customer interactions to predict which customers are likely to face issues with a product or service, enabling support teams to reach out proactively with solutions or advice. This not only enhances customer satisfaction but also reduces the volume of inbound support requests.

Separately, using a model trained and tuned in IBM® watsonx.ai™, the generative AI application extracts and summarizes relevant data and generates stories in natural language. Customers today expect real-time action, and with AI a business can modify the customer journey on the spot. AI tools can adjust a website’s content to highlight products that are more aligned with what a customer is searching for at that moment. By implementing AI, a business can capitalize on customer feedback and user experience to personalize interactions with customers and gain trust and reliability.

5 Ways Artificial Intelligence Boosts Contact Centers – CMSWire

5 Ways Artificial Intelligence Boosts Contact Centers.

Posted: Mon, 04 Nov 2024 12:00:29 GMT [source]

We think of an AI contact center as a facility with AI technology integrated into existing systems, processes and workflows. AI isn’t meant to replace your human agents, but rather provide a competitive edge that allows agents to do their best work and deliver exceptional customer service to high-value ChatGPT App customers. A critical piece of meeting customer expectations is incorporating artificial intelligence (AI). According to CMSWire research, 73% of CX experts believe artificial intelligence will have a significant or transformative impact on the digital customer experience over the next 2-5 years.

That’s why it’s absolutely critical to use genAI only in conjunction with humans in the loop. Contact centers are natural proving grounds for AI; they’re critical to the organization, but they avoid some of the challenges around clinical decision making and have humans naturally looped into automated workflows. She also said that contact centers are great for genAI because there naturally are going to be humans in the loop at all times.

Since the solution is cloud based, firms don’t need to manage any infrastructure, and they can easily deploy AI capabilities into their existing applications. All of this is done with simple and approachable AI, making it extremely fast for agents to become comfortable with the tool. As such, the technology removes the burden that traditionally impacts agents and has proven effective in lowering contact center burnout rates. As a result, its customers can be more self-sufficient, minimizing IT involvement in day-to-day maintenance and support.

AI Academy has put together a video showing customers what generative AI can offer to traditional contact centers. Enable fast and accurate speech transcription into text in multiple languages for various important use cases. Transform standard support into exceptional customer care by building in the advantages of AI. The health and beauty retailer and pharmacy chain needed an infrastructure upgrade to meet the evolving needs of the e-commerce world. Boots worked with IBM to transfer the legacy programs over to IBM Cloud® and worked together by using Red Hat® OpenShift® on the IBM Cloud container platform to build, replicate and test the digital environment. “Each of these stages offers clear ROI and benefits for stakeholders,” concludes Bisley.