In response to the pandemic, digital transformation has accelerated across all industries. As organizations settle into a “new normal,” they must consider where to focus their continued transformation efforts. Global spending on artificial intelligence reached $50.1 billion in 2020 and is expected to more than double by 2024. More than two-thirds of workers in a recent survey said they wanted their employers to deploy more AI-based solutions in the workplace. And more than 80% of those team members believe AI improves their performance at work, giving them a more productive, efficient workday.
As businesses that have not adopted AI realize they’re missing out on crucial opportunities, they’re faced with a new question: not whether to implement AI, but rather how to do so in a meaningful way that can scale with their company. Instead of sprinkling in AI as an afterthought, organizations that want to get the most out of their AI solution need to be intentional about building it into their tech stacks.
Support Automation Platforms Transform Your Data into Answers
A number of obstacles can hinder businesses in their efforts to implement AI. Many organizations work with a collection of point solutions awkwardly stitched together. That means team members constantly move between systems – sometimes dozens of them – to find answers and accomplish tasks, wasting time and risking information falling through the cracks. All that data exists somewhere, but it might not be easy to find. It also might exist in multiple locations in slightly different forms, without a single source of truth.
Your team should be able to find accurate information quickly, without relying on shoulder-tapping a co-worker or spending an hour scrolling through a handbook. It’s not enough for data to exist somewhere. Team members should be able to access and interact with it. To do that, they should not have to bounce between point solutions. Team members expect an integrated system that can do it all: store information, index it, surface it quickly, and deliver it clearly. They need an AI-powered solution to handle repetitive tasks so team members can focus on higher-level work.
Implementing an AI-Powered Support Automation Platform
Point solutions aim to solve one discrete problem, while platforms are connective, engaging with the systems already in use. Where point solutions can be static, platforms are generative, meaning they’re buildable, flexible, and able to evolve to meet new needs. A support automation platform uses a centralized knowledge base, cloud storage, a powerful helpdesk, and robust API integrations to simplify how organizations solve problems for customers and team members. By connecting to a company’s tech stack, the platform can automate repetitive tasks and make data instantly accessible, letting team members spend more time creating and less time searching for solutions.
While the prospect of change can be overwhelming – even to an organization weighed down by disorganized data and disconnected systems – there are some simple ways to implement an AI-powered support automation platform and reap the benefits quickly.
No. 1: Power your helpdesk with a centralized knowledge base
Helpdesks come in many forms, but at their core, they exist to solve problems, answer questions, and support an organization’s team members and customers. Most helpdesks consist of a team of workers who respond to requests for assistance via phone, email, and ticket systems. Helpdesk support teams face a daunting task with requests coming in from multiple sources. And while those support teams have expert knowledge, they receive questions – often the same ones repeatedly – at a volume that delays response times and causes frustration on both sides.
More often than not, the answer exists in a document, but it may be hard to find. Or different company sources may contain conflicting or outdated guidance on the same topic, but no one’s noticed the discrepancy and fixed it. As customer and employee expectations for self-serve solutions grow, many organizations have realized their systems of record are not good systems of engagement. Just because everything is recorded somewhere – in legacy systems, cloud storage, and even as tacit knowledge held by team members – doesn’t mean the people who need it can find it or use it. A centralized knowledge base brings order to the chaos as a searchable database that houses all the answers.
By adding key documents like company policies, operating procedures, product specifications, and troubleshooting guides to a knowledge base, organizations can build out a hub for their most frequently asked questions. Because AI and machine learning enable document mining, it’s easy to unearth inconsistencies and update guidance as needed. You’ll be able to see what team members and customers ask most often and what answers you’re still lacking.
No. 2: Integrate the apps you already use
An AI-powered support automation platform can go beyond cloud-stored data and connect smoothly to the popular business apps your team is already using, such as Salesforce, ServiceNow, Jira, and Google Workspace. Integrating apps instantly adds the information stored and processed there to a company’s centralized knowledge base, eliminating the silos that slow down work. Instead of digging through those systems, team members can find data in seconds from all sources with one search.
How do they reach those answers? By interacting with a conversational chatbot on your website and through your organization’s favorite communication tools.
No. 3: Answer questions quickly with automated live chat
An organization with a rich knowledge base can introduce an AI-powered conversational chatbot that mines documents to respond to customer and team member questions. Because the chatbot uses natural language processing (NLP), users don’t need any special training when they encounter the bot. The bot identifies and understands acronyms, asks questions to clarify requests, and directs team members to the information they’re seeking – whether it’s contact information, data analysis, or benefits resources. Administrators can create guided conversations customized for a variety of tasks, and team members can instruct the bot to follow workflows that use robotic processing automation (RPA) to complete actions like emailing a document to the right person, all while tracking the progress of a given process.
The bot can be integrated into various chat interfaces for customers and team members, meaning questions are answered 24/7 in a self-serve capacity that users increasingly prefer. Most organizations with bots deflect 90% of all inquiries, minimizing the number of support tickets filed. As the chatbot answers frequently asked questions, it learns from each interaction and asks for user feedback to improve with use. While an AI-driven bot frees up a support team from repetitive tasks, it should also be able to seamlessly escalate to a human expert when a question falls outside its knowledge base. And every time a human gets looped in, the bot learns new information so it can answer without help the next time. Over time, the bot will escalate fewer and fewer issues, and support teams can get back to creative, human-centered work.
An AI-Powered Platform Grows with Your Business
By incorporating AI into Data Management and helpdesk processes, companies can improve productivity and eliminate tedious tasks while empowering teams with access to actionable information. An integrated platform solution can grow along with a company’s needs, and the beauty of AI is its ability to learn and improve with use. Simple steps such as developing a knowledge base, integrating widely used apps, and introducing a conversational chatbot can help a company start the process of implementing AI across processes. As an organization’s knowledge base grows, support automation can handle more tasks, initiate more processes, and answer more questions. By choosing a platform rather than a point solution, organizations can use AI to transform their resources, support their team members, and satisfy their customers.