Companies use a wide range of both artificial intelligence (AI) and automation tools, and each automation tool serves a different purpose, often working together to boost efficiency. In this blog, we’ll explore the differences between AI and automation, how they can complement each other through intelligent automation, and five real-world examples of how they work together. We’ll also highlight the benefits of using AI in business process automation.
Let’s start by clarifying the difference between artificial intelligence and automation.
Automation refers to a broad set of technologies that perform repetitive tasks without human intervention. These tasks may be rule based (often robotic process automation or business rules) or they could involve cognitive automation like AI. Automation can also occur at the task-level or be part of a broader process that passes work between automation technologies and humans. Its primary goals are to save time, reduce human error, and free up workers for more high-value tasks.
AI refers to systems that mimic human intelligence and is a specific type of automation called “cognitive automation.” Artificial intelligence can analyze data, learn from it, and make decisions without being explicitly programmed for every scenario. Artificial intelligence can adapt to new situations by learning patterns and improving its performance over time. It’s worth noting that artificial intelligence can come in several subtypes such as generative AI which creates new content like text or photos, natural language processing which understands and interprets human language, or predictive artificial intelligence which uses patterns to forecast future events.
In short, business process automation tools handle everything from routine, rule-based tasks to more complex problems that require learning and decision-making.
When AI is combined with other business process automation tools like robotic process automation, the result is intelligent automation. This powerful combination enables businesses to automate not only repetitive tasks but also tasks that require some level of decision-making and analysis.
For example, let’s say you use traditional automation to send out marketing emails to customers. Automation can send the emails, but AI can analyze which customers are most likely to engage with certain types of content based on past behavior, making the entire process smarter. And generative AI can even draft the emails first for humans to review for accuracy. By combining AI with other forms of automation, you can make your automated workflows more adaptive, personalized, and efficient.
Here’s a simple breakdown:
Let’s dive into some real-world examples where artificial intelligence and automation are working together to streamline processes.
AI-powered chatbots have become a staple in customer service. Traditional automation could only handle basic, scripted conversations, but artificial intelligence takes chatbots to the next level. AI-powered chatbots can understand natural language, process customer queries, and provide relevant responses using generative AI, all while learning from previous interactions to improve over time. This reduces the need for human customer service agents to handle repetitive inquiries, allowing them to focus on more complex customer needs.
Processing invoices manually is time-consuming and prone to error. Automation platforms have been used to streamline this process, and when combined with AI, the results are even more impressive. AI can read and interpret data from invoices using technology like natural language processing—even from unstructured documents. It can then match them to purchase orders, flag discrepancies, and extract data automatically for use in applications.
Manufacturing companies use AI-driven automation for predictive maintenance. Traditional automation systems can schedule regular maintenance tasks, but AI enhances this by predicting when machinery is likely to fail based on historical data. AI can analyze equipment performance data and predict issues before they happen, enabling companies to perform maintenance only when needed. This minimizes downtime and extends the lifespan of equipment.
AI is transforming HR processes, especially onboarding. AI can process onboarding documents, saving time for HR professionals. It can even suggest potential training opportunities for employees. This makes the entire process more efficient and ensures that HR teams can focus on more strategic tasks.
Financial institutions use AI to detect fraudulent transactions in real time. Automation can flag certain transactions based on predefined rules (e.g., transactions over a certain amount). However, AI goes beyond this by learning patterns of normal behavior and flagging transactions that deviate from those patterns. AI can detect fraud that would be missed by traditional rule-based systems, improving security and reducing financial risk.
There are several key benefits to integrating AI with other business process automation technologies.
Artificial intelligence and broader automation tools work best when combined into intelligent automation. By leveraging AI’s ability to learn, adapt, reason, and create, businesses can make their automated processes smarter and more efficient. Whether it’s in customer service, HR, or finance, intelligent automation offers enterprises a way to streamline processes, reduce costs, and improve decision-making.
As artificial intelligence continues to evolve, the possibilities for automation will only expand. Businesses that embrace this combination will be well-positioned to thrive in an increasingly competitive landscape.