Automation removes the need to perform manual, repetitive tasks by allowing your teams to automate their processes and workflows. With our simple rule builder, you can configure powerful automation rules to handle even the most complex scenarios.
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Rules allow you to automate actions within your system based on criteria that you set. Automation rules are made up of components:
Every rule starts with a trigger. They kick off the execution of your rules. Triggers will listen for events in your Atlassian Cloud product, such as when a comment is added.
View available triggers in Jira Cloud or Confluence Cloud
Actions are the doers of your rule. They allow you to automate tasks and make changes within your site. They allow you to perform many tasks, such as editing an issue, sending a notification, or creating a Confluence page.
View available actions in Jira Cloud or Confluence Cloud
Conditions allow you to narrow the scope of your rule. They must be met for your rule to continue running. For example, you can set up your rule to only escalate an issue if it is high priority.
Where a condition is added on the rule will affect how it works:
Add criteria to an entire rule that can filter which triggers continue your automation. This is especially relevant if using advanced components, where all other components will be automatically wrapped in a rule group. For example:
Trigger: Work item created
Condition on trigger: The assignee of the work item is empty.
Result: The rule only runs for work items created without an assignee.
Add criteria to determine if the rule continues running just for the components in a rule group. Only applies when using advanced components.
View available conditions in Jira Cloud or Confluence Cloud
Branches allow you to create a separate execution path of your rule. They enable the potential to perform multiple actions or conditions.
View available branches in Jira Cloud or Confluence Cloud
Advanced components boost the power of your rule by automating multiple related processes from a single rule.
Olivia is a customer service agent at a bustling, understaffed customer service department. She primarily responds to written support requests, like emails and chats, and can handle 30 to 50 messages per shift. However, her capacity often fluctuates based on the complexity of the tasks.
To free up her time, bots quickly answer customer questions or acknowledge receipt of the query and when customers can expect a reply. This keeps her workload manageable, stress levels low, , and helps her stick to her schedule.
That’s the power of intelligent automation.
In this article, we will discuss the definition of intelligent automation, key components, and details about how you can leverage IA for customer service within your organization.
Intelligent automation (IA) describes the intersection of artificial intelligence (AI) and cognitive technologies such as business process management (BPM), robotic process automation (RPA), and optical character recognition (OCR).
Sometimes called “cognitive automation” or “hyperautomation,” IA allows businesses to automate repetitive tasks and processes. In , intelligent automation helps agents provide faster support in addition to stand-alone options like .
To put it simply, artificial intelligence is a tool for efficient problem-solving, while intelligent automation combines several tools and technologies (including AI) to automate tasks, workflows, and processes. Since the technology is constantly combining and evolving, there are some blurred lines between the definitions of artificial intelligence, intelligent automation, and other methods of business process management (BPM). Here are the basics:
Intelligent automation benefits businesses by streamlining manual, routine tasks. It increases operational efficiency, reduces human error, and can lower business costs.
Here are a few benefits of intelligent automation and why they should matter to business leaders:
Intelligent automation uses several technologies to achieve necessary functionalities, but the five basic components of intelligent automation include artificial intelligence, robotic process automation, business process management, automation tools, and data.
So, let’s demystify these components and how they make intelligent automation possible.
Artificial intelligence (AI) is essentially the brains of the operation. AI often powers intelligent that assist with sentiment analysis, personalization, and problem-solving to streamline support interactions.
AI refers to the ability of computers and software to assist with, and sometimes perform, cognitive tasks humans are traditionally responsible for. For example, making decisions, understanding context, and personalizing responses. Using data, AI continuously learns, making it a powerful tool for problem-solving.
AI makes intelligent automation possible using these techniques:
Together, these techniques and algorithms help the software “think,” better comprehend customer requests, and enhance support.
Robotic process automation (RPA) is the task handler and rule follower. It’s also a key component of chatbots but primarily uses pre-defined business rules to influence bot outputs instead of learning from interactions and delivering humanistic replies.
RPA allows bots to execute repetitive, back-office tasks and processes like data entry and extraction, filling out forms, processing orders, moving files, and more.
For example, RPA bots can follow predefined rules to automate tasks and workflows. However, they’re unable to make decisions or think for themselves. So, to achieve intelligent automation, you must use robotic process automation with AI.
Business process management (BPM) is the operations specialist of the intelligent automation group. For instance, let’s say you want to create an IA function to optimize —or how your business will use tools to manage and adapt to change. BPM can influence implementation planning, help capture data, and streamline creation of your change roadmap.
BPM is a discipline that relies on various software and processes to manage a business’s operations, including modeling, analysis, optimization, and automation.
The primary job of business process automation is to identify and eradicate inefficiencies by reassigning tasks that are time-intensive or prone to human error to AI automation.
Automation tools such as act as helpers. They automate workflows and processes, and enhance existing functionalities.
These integrations and automation tools often serve a specific purpose, like:
Enabling communications between platforms
Streamlining data sharing
Identifying support congestion
Automating general tasks
Assisting with replies
By adding apps and integrations, businesses can customize intelligent automation from end-to-end to effectively serve customers and departments with unique needs.
Finally, data is the key piece of the intelligent automation ecosystem. IA uses raw data to train its systems and set up intelligent workflows. Over time, IA can also continue learning and improving using data from interactions.
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IA uses data to train itself and generate relevant responses to prompts it receives. Data also plays a key role in , ensuring the IA learns from each support interaction and user feedback.
Robotic process automation also uses data to follow predefined rules and compliance standards.
Business process management uses data to detect inefficiencies and enact changes that improve existing processes.
Many employees are hesitant to embrace AI for fear of job displacement. There is some merit to this concern, as a predicts that AI will replace 85 million jobs by . But the study also estimates that AI will create approximately 97 million new jobs.
AI isn’t a replacement for human talent, and businesses should use it as a support aid to enhance productivity.
For customer service, businesses can lead with an to help human agents deliver better support. Here are some ways AI helps customer service teams:
Saves agents time by taking over complex and repetitive tasks
Identifies opportunities for streamlining operations
Analyzes large amounts of data and delivers key insights
Organizes support requests to keep agents on track
Monitors regulatory guidelines to ensure compliance
Businesses can leverage intelligent automation to streamline their processes for various industries, from customer service and sales to marketing and operations. IA can help keep costs low by removing inefficiency from the equation and freeing up time for other high-priority tasks. See some examples of these applications below.
Businesses can use automation to provide predictive suggestions that can speed up processes and improve productivity. Teams can use IA to:
Draft emails and press releases
Create internal process docs
Brainstorm ideas
Help edit text for basic grammar and syntax rules
can use intelligent automation to help write and send personalized replies to customers at scale. AI can save agents time on the basics so they can invest more time into things like , this could include:
AI-suggested macros and help center articles for agents to choose from while assisting a customer
Auto-filled response options using a few contextual words from an agent
These automations benefit existing agents but are also useful to new hires, who may be slower to resolve tickets as they learn details about your business, its offerings, and performance expectations.
Workflow automation helps team members handle smaller, repetitive responsibilities with ease. This also increases productivity by tackling time-consuming sales, support, IT, and marketing tasks.
Administrators can set up event-based (triggers) or time-based (automations) business rules so the AI will automatically address a task when the need arises without human intervention.
AI-driven tools like chatbots can aid in data collection, assess unstructured or , and rapidly generate insights.
A few other ways businesses can use intelligent automation data include:
Generating predictive analytics to aid in decision-making
Gathering key context from customers before escalating tickets
Detecting anomalies
Prioritizing tickets and communications with high profitability potential
Identifying how customer intent relates to purchasing behaviors
Sharing personalized recommendations
Much like gathering data and insights, IA can help businesses drive more sales by providing strategy recommendations and optimizing existing sales processes.
Some ways IA can help create or identify upsell and cross-sell opportunities are through:
Lead scoring
A/B testing suggestions
Real-time product recommendations
Industry and market trend predictions
Customer intent and sentiment analysis
Aside from serving as a worthwhile resource for internal use, intelligent automation can also be a valuable tool for customer self-service.
For example, chatbots can provide conversational support for most minor issues and many customers like using them because of the added layer of convenience.
AI automation can improve customer service convenience by:
Sending help center articles to customers or employees
Answering frequently asked questions around the clock
Routing customers to the best agent or department to resolve their issue
Discover the true potential of by incorporating intelligent process automation into your workflows.
When you equip your support teams with AI-powered tools like chatbots, virtual assistants, and agent workspaces that enhance productivity, you empower them to take customer service to the next level—and maybe even capitalize on sales opportunities.
Learn more about to take customer care to the next level and exceed customer expectations.
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