How AI will transform Digital Process Automation in 2024
By Charlie Thomspon, SVP EMEA, Appian
Like all industries, generative AI seems to be shaking things up for digital process automation (DPA). 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.
As the world ponders what AI can make possible in the future, AI-powered DPA is already performing complex business tasks – like turning a PDF into a digital interface or sorting all the emails in an inbox and generating responses for an employee to review.
So, what else can AI do for process automation, and what should organisations keep in mind when building an intelligent automation tech stack? As AI-led potential shifts responsibility toward professional developers and more challenging but transformative use cases, here are some ways in which AI will continue to complement DPA to generate value for businesses.
Super-charging DPA technology
Digital Process Automation involves using advanced digital tools, particularly low-code development tools, to automate processes and optimise business operations. It helps make business processes more effective, freeing employees from repetitive work and facilitating change that enables businesses to adapt and shift their approaches more easily.
Now that generative AI and large language models (LLMs) are more powerful and prevalent than ever – and so is DPA.
While AI was already playing a role in process automation before the boom of generative AI, the power of this new technology is now fuelling even more productivity gains, allowing developers to quickly build internal chatbots, summarise documents, create email response generators, and more.
Generative AI capabilities paired with process automation technology will help organisations automate and streamline their processes even more quickly. This will include self-service analytics through AI-powered queries of data fabric and the development of workflows through natural language prompts.
Innovations like these, which make process automation more intelligent, will make it easier for organisations to orchestrate efficient, impactful processes.
Making use of multiple technologies
Historically, many companies have sought to launch automation initiatives relying solely on robotic process automation (RPA) or IDP. This approach is limiting because it stretches one technology far beyond its capability and cannot scale to support organisation-wide automation. Multiple technologies are needed to power a diverse and successful automation strategy.
Looking ahead, organisations will continue to need a wide range of automation capabilities, including RPA and IDP, but these capabilities will now be strengthened and diversified by AI, increasing its potential.
AI-powered DPA relies on good data
AI is only as powerful as the data it can learn from so it is important that data is accessible and usable for AI-powered DPA.
Organisations 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 virtualisation layer. Data lakes and warehouses require data transformation and movement. When a data fabric is embedded into process automation technology, it is possible to use no-code connectors to bring data from different systems into one application so it can be put to good use.
Businesses will need a unified approach to truly leverage AI-powered DPA
In the past, automation adoption has sometimes been executed piece by piece, rather than taking a wider view of how automation can impact a whole business. Without a unified approach, this results in disconnected islands of automation that are unable to communicate with or learn from each other – presenting complex challenges for both employees and customers, particularly when trying to scale.
In order to avoid islands of automation while successfully embedding AI, businesses must take a unified approach. Adopting a platform that gathers AI and automation technologies in one place enables these capabilities to work together seamlessly on a strong data management foundation.
AI-powered DPA’s potential will soon exceed even the predictions outlined here. By harnessing new technologies, developers and business leaders will be able to continue to improve productivity and efficiency. With AI-human collaboration, employees are freed up to work on more complex and enriching tasks, with true AI-human collaboration the ultimate goal for a successful modern business.