Most businesses probably realize that change is constant. The question is then, how can these changes be planned for and guided through as smoothly as possible. Well-planned change management strategies can help lower the possibility of difficulties and help bring about streamlined transitions.
Automated Self-Service is quickly becoming necessary for streamlining support processes, enhancing efficiency, and empowering both end-users and support personnel. Unlike traditional support models which rely heavily on human intervention, it uses the latest technologies and predefined workflows to enable users to resolve issues, access resources, and perform tasks autonomously.
IT departments have many plates to juggle. Anything that can help keep them focused on their primary function of maintaining the technology environment in an organization might be welcomed. An IT Service Catalog can be such a tool.
When it comes to technical support, there are two main options: Help Desk and Desktop Support. These can be in-house/on site or delivered remotely via third-party cloud-based software (SaaS) solutions. There is often some confusion over the use of the terms Help Desk and Desktop Support.
Customer expectations are higher than ever, and traditional service models often struggle to keep up. Long wait times, repetitive requests, and rising ticket volumes put constant pressure on support teams. That's where Artificial Intelligence (AI) is making a difference.
AI in customer service automates routine tasks, speeds up resolutions, and helps agents focus on complex, high-value interactions. It is transforming how contact centers and help desks operate.
In this article, we look at what AI in customer service means, why it matters, and the strategies and benefits organizations can gain by implementing it.
First, let's define AI: Artificial Intelligence (AI) refers to systems that perform tasks normally requiring human intelligence, using technologies like machine learning (ML), big data, foundation models, deep learning, neural networks, and natural language processing (NLP).
A well-known, user-facing example is OpenAI's ChatGPT. Increasingly, these technologies integrate with customer service software to handle repetitive tasks, personalize interactions, and scale support.
AI in customer service automates interactions, speeds up response times, and helps agents deliver accurate, personalized support.
It enables:
According to McKinsey high-quality customer service can boost revenue 2–7% and profitability 1–2%. AI-powered chatbots can handle queries 24/7, reduce call volume, and free human agents to focus on complex problems.
Common AI models include:
It's important to note that AI shouldn't replace human agents, only support them. AI handles repetitive inquiries, while agents take on complex, high-empathy cases. Companies using an "AI + human" approach report higher job satisfaction among agents, where they spend more time problem-solving and less time on routine tasks.
AI in customer service uses automation and intelligent tools to improve efficiency, deliver faster support, and enhance the customer experience. Contact centers and help desks are increasingly turning to AI to streamline workflows, handle high ticket volumes, and boost satisfaction.
Service Level Agreements (SLAs) document expectations between service providers and customers. These contracts outline standards for response and up time, and business operating hours, among others.
However, even the most well-crafted SLAs are susceptible to breaches. An SLA breach occurs when the agreed-upon services fall short of stipulated standards. It erodes trust and can result in financial penalties and damaged reputations.
IT help desk workloads and tickets are high-volume, busy, and always feel like they're getting busier.
A massive time-saver is to use help desk scripts and templates, sometimes called "canned responses", to handle ticket volumes of internal or external customer interactions faster and more efficiently.
IT help desks are busy operations. Customers, whether internal or external, are calling and, in most cases, sending support tickets via online forms and Live Chat.
IT Service Management (ITSM) teams don't have time to write every single response message from scratch. You need a ready-to-use set of examples to cover the most commonplace scenarios, such as printer, password, and third-party software (SaaS) problems.
When it comes to customer service and IT support, Service Level Agreements (SLAs) are essential for ensuring high-quality customer service and maintaining contracts between in-house teams, customers, and service providers.
As call center and IT help desk managers, your ability to maintain high SLA scores can significantly impact both customer satisfaction and the efficient running of contact center or IT operations.
IT Service Management (ITSM) help desks can implement and deliver services in one of three ways: reactive, proactive, or predictive.
In many respects, these three levels represent different stages of the ITSM maturity model. Measuring ITSM maturity is a way of assessing "how good your organization or system is at self-improvement." If you're still delivering reactive IT services, then that suggests a lower level of maturity, which results in higher staff turnover, higher costs, and lower key performance indicators (KPIs), customer satisfaction, and service level agreement (SLA) scores.
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