We’ve been hearing a lot about AI lately—it seems to be taking the world by storm, and it’s begging the question: what if computers could work for us and also work like us, but better? What if computers could make decisions, solve problems, hold intelligent conversations, write outline drafts or generate pictures?
Finally, how can we use AI to make our lives easier? Use it to become more successful?
Often, we think of robotic process automation (RPA) and artificial intelligence (AI) as separate entities. But with the ever-evolving world of automation technology, that no longer needs to be the case. AI is changing RPA for the better.
While RPA exceeds market predictions, AI continues to drive greater value. According to 2023 predictions from Forrester, 10% of Fortune 500 enterprises will generate content using AI tools. And it won’t stop there.
AI is a cognitive learning technology with limitless potential, from cognitive algorithms to AI-powered industry innovation. And intelligent automation (IA) brings together artificial intelligence, machine learning (ML) and robotic process automation with other technologies to scale automations end-to-end using a digital workforce.
Both RPA and AI have their advantages, but to get the best optimization for your business processes you’ve got to marry the two; that’s where you get intelligent automation. Because as much as RPA focuses on rules-based automation of tasks, especially repetitive tasks, AI is a simulation of human intelligence through computer systems – meaning the two have great potential when they collaborate.
What’s the Difference Between Artificial Intelligence (AI) and Robotic Process Automation (RPA)?
Robotic process automation (RPA) uses software robots to automate repetitive business processes, mimicking human actions to offload dull, routine tasks from human employees. That in turn boosts employee engagement and morale, allowing them to focus on more interesting, cognitive tasks. RPA runs automated tasks efficiently and without error, acting under the instructions for which they’re programmed.
Artificial intelligence (AI) is capable of cognitive learning, reasoning and identifying errors and efficiencies for correction. Within AI technologies is an expanse of applications, including machine learning (ML), intelligent document processing (IDP), optical character recognition (OCR), natural speech, speech recognition and natural language processing (NLP).
By introducing AI-powered RPA robots, you get intelligent digital workers following contextual rules and learning as they go. Digital workers can perform on different levels of automation: independently as ‘unattended’ automation, or with your people as ‘attended’ automation.
Digital workers perform without breaks to improve employee workflows, reduce errors, increase productivity and achieve customer satisfaction by providing quicker service.
In the four primary areas where artificial intelligence and robotic process automation are quickly progressing – chatbots, unstructured content, IoT sensors and analytics – the ability to capture greater insight from unstructured data is center stage in making robots more intelligent.
Together, RPA and AI are the ultimate team-up, called your digital workforce.
Why is Unstructured Data so Important for Intelligent Process Automation?
Unstructured data makes for great automation opportunities. A vast number of companies’ data is sitting on dozens or even hundreds of terabytes of unstructured data. So it’s hardly a surprise that organizations want proven solutions to accelerate the use of unstructured information and unleash the full potential of intelligent robotic process automation.
To close the process gap, the focus remains on analytics, where nearly half of organizations will use a combination of AI and automation software to create a new digital workforce.
Using unstructured data in an RPA process
Think about the following scenarios that may impact the use of unstructured data while building an RPA process:
- When you need to classify documents against specific customers’ taxonomy and behave accordingly
- When understanding the content of documents is relevant
- When you need to apply reasoning before extracting information
- When you need to also discover relations linked to the data you extract to be used in the process
In the above scenarios, the collaboration between AI and RPA extends and improves the reach of intelligent automation by accelerating the use of unstructured information.
AI makes all relevant data immediately useful and actionable in RPA. It analyzes, categorizes and extracts relevant information trapped in unstructured data (such as text fields of various business rules, documents, purchase orders, invoices, emails, survey reports, forms, etc.) to organize it into clean files for robotic process automation.
How Do AI and RPA Work Together?
When you put RPA and AI together, you get intelligent process automation or intelligent automation (IA). IA combines these two, plus machine learning and other AI-based automations to optimize workflows, streamline processes and enact a total digital transformation in an organization.
Intelligent automation software turns RPA robots into a digital workforce driven by cognitive automation, processing tasks in increasing complexity.
RPA and machine learning
With AI, RPA robots can perform their current capabilities with the added ability of decision-making. Machine learning (ML) is where these bots start problem-solving and offering suggestions for improvement.
Machine learning is the branch of AI that uses data and algorithms to imitate human learning functions, improving as it goes. With machine learning models, these AI-powered software robots can help with forecasting and predictive outcomes.
AI and RPA teaming up
AI is the perfect match for RPA to analyze, categorize and extract unstructured data, making it functional to improve the output of complex, even more mission-critical intelligent RPA workflows.
At the same time, RPA is the ideal complement to enable the adoption of effective automation with cognitive capabilities at scale.
As a result, companies can get the benefits of automation from both technologies by using an all-in-one platform to automate end-to-end processes and easily exploit the value of intelligence functionalities.
The integration of Expert AI's artificial intelligence capabilities into SS&C Blue Prism robotic process automation platform delivers improved labor efficiency and productivity while accomplishing higher levels of accuracy in unstructured data access – extending business automation to new strategic areas by automating tasks that once were reserved only for humans.
What is an example of RPA and AI?
There are tons of examples where AI gives RPA bots a boost in capabilities, but here we’ll focus on just a few:
- Email management: Robots scan through email data to detect urgency, issues and purpose, and even extract crucial information to usher in quicker response times and easier organization of topics.
- Invoice processing: With AI-powered robots working through payment processing systems, the invoice processing time is cut down dramatically and made far more accurate.
- Finance transactions: RPA and AI together can ensure security and accuracy in financial transactions by capturing a user’s data from various sources and detecting potential fraud by scanning for inconsistent activities. Machine learning helps with the predictive analysis when spotting red flags in future transactions, based on previous experience.
- Communication experiences: You can use your bots to scan through employee and customer experiences to find where improvements can be made, and any issues that arise can be quickly amended, also ensuring nothing is missed. This is beneficial to employees and customers.
What Are the Benefits of RPA and AI?
Now that you know what RPA and AI are and how they can work effectively together, there’s only one thing left to do: Talk about the benefits! Digital works have the potential to totally transform your automation journey, from good to outstanding.
The list goes on and on, but here’s our summary of the four main benefits you can achieve with RPA and AI together:
- Improved employee satisfaction: employees are freed from boring tasks so they can focus on higher-value projects.
- Efficiency: processes are streamlined for faster time to results.
- Accuracy: fewer human errors result when automating processes, which furthers efficiency.
- Consistency and compliance: because there are fewer errors and work done by following rules, your digital workers keep clear audit trails to ensure your compliance requirements are always adhered to.