Generative AI is shaking things up for process automation. Artificial intelligence is the perfect complement to the capabilities that support a business process automation initiative. Imagine using AI to turn a PDF into a digital interface, or sort all the emails in an inbox and generate responses for an employee to review. These use cases already exist—and they’re just the beginning of what AI can do for businesses. What else can AI do for process automation? How will intelligent automation change process automation best practices? Read on for four predictions about how AI and process automation will work together to generate value for businesses moving forward.
1. AI will supercharge process automation technology
Intelligent process automation technology is powerful: it helps organizations mold their business processes to increase their effectiveness, free up employee time spent on repetitive work, simplify complex tasks, and empower their operations to adjust to change.
Technology spotlight: Generative AI
Now that generative AI and more powerful large language models (commonly called an LLM, learn about the differences between generative AI and LLMs here) than ever are on the scene, AI business process automation technology promises to be more powerful than ever. Before generative AI’s boom, AI had already played a role in digital process automation platforms like Appian, automatically tuning the data fabric for developers and assisting in intelligent document processing (IDP). Now generative AI is fueling even more productivity gains, allowing developers to quickly build internal chatbots, summarize documents, create email response generators, and more.
Generative AI capabilities paired with process automation technology will help organizations automate repetitive tasks and streamline their processes even more quickly. Appian continues to innovate in the realm of AI-powered automation. Developers can currently train AI skills to process and classify content, such as emails or documents, helping in automation workflows for tasks like invoice processing, accounts payable, and processing customer requests. Developers can also generate full interfaces from PDFs via AI-powered document understanding and automatically create unit test cases using our AI Copilot capabilities. We’ve also released self-service analytics and business intelligence through AI-powered queries of Appian’s data fabric using natural language processing.
Innovations like these, which make intelligent process automation even better, will drive operational efficiency now and into the future.
2. Successful process automation efforts will make use of multiple technologies—including AI
Too often in automation’s history, companies have applied a self-defeating strategy by using robotic process automation (RPA) or IDP as the only technology in their process automation initiative. Many automation initiatives have failed because they stretched a single technology far beyond what it can do. RPA or IDP alone just won’t scale to support an organization-wide automation strategy. And now that AI can step in to assist or power other technologies to automate business processes, technology like RPA definitely shouldn’t be your sole focus.
Technology spotlight: Intelligent automation
Intelligent automation technologies are those that can automate manual tasks using artificial intelligence. These cognitive automation technologies are especially useful for business operations that involve decision-making. Intelligent automation tools can do things like understand human language with natural language processing and make cognitive decisions based on data. Appian has a wide range of intelligent automation technologies that all work together in a unified platform.
Going forward, organizations will continue to need a wide range of automation capabilities, including RPA and IDP—the difference is, these capabilities will now be strengthened by AI.
3. AI-powered automation will only be as good as the data supporting it
Any solid process automation initiative using AI will require a strong data management foundation. AI will only be as good as the data supporting it, so programs will need to make data accessible and usable for AI process automation.
Technology spotlight: Data fabric
Organizations should look past data warehouses and data lakes to more flexible data management strategies like data fabric, which allows IT teams to connect data in a virtualization layer. Data lakes and warehouses require data transformation and movement. Data fabrics, on the other hand, don’t require any migration at all. When a data fabric is embedded into process automation technology like Appian’s, it means you can use no-code connectors to bring data from different systems into one application so that the data can actually be put to use in real time.
4. Organizations will increasingly take a platform approach to process automation.
In the past, many organizations have invested piece by piece in various automation technologies. Without a unified automation solution to orchestrate the individual technologies, they ended up with disconnected islands of automation. This has led to complex automation challenges across both employee and customer experiences, especially when organizations try to scale their automation programs.
Technology spotlight: Process automation platforms
That’s why modern organizations are moving toward automation platforms that unify these technologies and help automate their repetitive processes. To avoid islands of automation while successfully operationalizing AI, organizations will adopt platforms that unify automation technologies and AI in one place, where a full range of AI-powered business process automation technologies seamlessly work together on a strong data management foundation.
