Generative AI seems like it's shaking things up for process automation, like other industries. But in reality, artificial intelligence is less of a shake-up and more of a natural complement to the capabilities that support a process automation initiative. Imagine a world where AI can turn a PDF into a digital interface, or sort all the emails in an inbox and generate responses for an employee to review. Turns out, these things are actually possible—and they’re just the beginning of what AI can do for businesses. What else can AI do for process automation? How will it change process automation best practices? What things should organizations keep in mind when building an intelligent automation tech stack? Read on for four predictions about how AI and process automation will work together to generate value for businesses moving forward.
Process automation technology is powerful: it helps organizations mold their business processes to increase their effectiveness, free employees from repetitive work, and empower their operations to adjust to change.
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 before are on the scene, process automation technology promises to be more powerful than ever. Before generative AI’s boom, which started in late 2022, AI had already played a role in process automation platforms like Appian, automatically tuning the data fabric for developers and assisting in intelligent document processing (IDP). But now, the power of generative AI is fueling 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 and streamline their processes even more quickly. For example, Appian is working on a few specific ways to innovate with generative AI and process automation. Developers can currently train AI skills to process and classify content, such as emails or documents. We also just released a feature that allows developers to instantly generate digital forms from PDFs via AI document understanding. Our roadmap includes features like self-service analytics through AI-powered queries of Appian data fabric and development of workflows through natural language prompts.
Innovations like these, which make process automation more intelligent, will make it easier for organizations to orchestrate efficient, impactful processes.
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.
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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.
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.
Organizations will 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. 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.
Hear from Appian Founder and Chief Partner Officer Marc Wilson in Forbes: Four Myths About Digital Transformation And How To Debunk Them By Modernizing At The Data Layer.
In the past, many organizations have invested piece by piece in various automation technologies. Without a unified 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 journeys, especially when organizations try to scale their automation programs.
That’s why modern organizations are moving toward automation platforms that unify these technologies. In order 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 technologies seamlessly work together on a strong data management foundation.
The Appian Platform is your gateway to the productivity revolution with an architecture powered by artificial intelligence.