Although RPA can pave the way for quick wins and improvements, of course if an organization deploys it appropriately, it has natural limitations that make it unsuitable for large-scale business process automation. RPA only affects work between computer systems and user interfaces, and cannot easily respond to circumstances outside of its strict rules-based setting.
Today, companies can no longer rely on an automation strategy that offers only slow, gradual introduction of new processes and solutions. Just as today ends the era of the best applications on HR, Onboarding, Billing, Achieve Yourself... Linear and single-purpose solutions are starting to simply come out. In a digital environment that is undergoing constant transformation and improvement, it is essential to invest in automation solutions that unite people, applications and even robots within the platform and enable the transition from strict reliance on pure RPA.
Intelligent automation or IA finds itself at the center of this effort to orchestrate the overall process. IA is not just artificial intelligence or RPA, but more — it's a next-generation solution that could allow businesses to fully automate 50% or more of all the work they do.
What is IA, what does it include, and why should your business consider investing in these advanced solutions as soon as possible?
Explaining Intelligent Process Automation
IA isn't the only technology - it's the combination of multiple automation tools into a broader, coherent strategy that allows businesses to do more, at less cost. IA involves both a fundamental rethink of the way your teams navigate certain processes and the deployment of new tools that continue to eliminate the need for human input on repetitive tasks. Instead of simply automating one or two process steps, IA can change the workflow from start to finish.
And what's even more important? IA includes technologies such as machine learning and artificial intelligence that use data to evaluate and suggest how the process should proceed. And subsequently, based on previous work, they made changes to their own procedures. Thanks to IA, some workflows can be completely taken out of the hands of employees.
If it seems to you that the introduction of IA is a complex and at the same time large-scale project, you are not mistaken, it really is. For companies that invest appropriately in IA, they do not see digitization as a turnkey project and learn from the lessons learned, but it is an effort that can pay off tremendously over time.
Intelligent Automation vs. RPA: What's the Difference?
In particular, in businesses that have already invested in RPA, there is confusion about the difference between intelligent process automation and Robotic process automation.
RPA is part of IA for automating rule-based workflows. RPA stops when a solution can potentially fail and require an employee's intervention or decision. It would not be possible to solve such complexity with RPA alone. IA brings additional technologies into automation within the overall platform, enabling it to automate end-to-end processes through a smart combination of technology, human interaction and business rules. The firm gains benefits from the use of other technologies such as intelligent document processing, processing unstructured content from different sources of information, or data analysis to gain insights into processes.
As an element of intelligent automation, robotic process automation is a crucial area in which it focuses. But it is only one contribution to a more extensive methodology for changing the way we work.
What are the key elements of intelligent process technology?
In any case, RPA is only one component of intelligent process automation. There are potentially dozens of different specific automation applications that fall into several categories. RPA automates rule-based processes within user interfaces and enterprise systems, such as modifying a database or moving information from one system to another. Other elements of automation include, for example:
- Machine-learning - Within IA, machine learning plays a vital role because it allows businesses to identify patterns in data that are often very unstructured. For example, a firm can use machine learning tools to improve annual and quarterly forecasts by gaining insights from historical sales data.
- Natural language processing and generation. Computers are still getting better at understanding text inputs and converting them into actions without human intervention. These tools can even generate text based on the collected data. In the future, this principle could mean automating most of the key reporting functions.
- Generative Artificial Intelligence - I think we can safely say that the end of 2022 will be remembered as the moment when we realized that much of what had been fantasized about for decades in science fiction had come to pass. Intelligent Automation Platform Kofax TotalAgility (KTA) leverages generative artificial intelligence to enable operations and citizen developers to create more in less time — using natural language. It will help them get started, navigate the low-code platform and suggest what to automate. Just tell KTA what you need, and it will do the rest: processes, data models, UI forms, and document extraction models - in seconds. Professional developers will be helped by Generative AI with the above, and in addition with the creation of test cases, optimization of the data model, analysis of the impact of changes and other activities.
Do you still think this is science fiction? Believe that at the same speed as OpenAI was able to get the first 100 million registered users in 2 months, we at INFOMATIC have the first samples of GPT involvement in processes in lab environments and are negotiating with the first clients about their safe deployment in everyday life.
Understanding the benefits of IA
Why are many businesses rapidly reorienting to IA and process automation? One reason is the pace of change: a firm that is not ready to adopt these technologies could feel a strong competitive disadvantage in the near future.
Other key benefits of adopting smart automation include:
- Reducing the cost of doing business. With higher rates of automation comes more opportunity to shift existing payroll costs to areas where they can deliver the most benefit. Specifically, instead of boring and routine tasks to a high-value job that requires human intuition.
- Better results for consumers. IA delivers improvements behind the scenes of the business, but it can also generate faster and more consistent results for customers.
- Fewer costly mistakes. With fewer human inputs and advanced machine learning, and the involvement of RPA robotization in the automation of parts of the overall processes, many errors are eliminated and time saved. There is no need to search for and repair them.
- Simplified management and supervision with clear audit trails. The interconnected nature of IA and its robust auditing record creation capabilities means it is easy to trace the process from start to finish.
Many industries can take advantage of these benefits. The most prominent areas with potential for this broad spectrum of technologies include healthcare, insurance, banking and financial services, transport and logistics, and B2B sales in general. But also many internal departments within any enterprise, for example, financial accounting offices.
Because IA includes such a diverse set of tools, it is suitable for businesses working at scale that are pursuing opportunities for faster, more consistent, and more valuable work outputs.
How to adopt the philosophy of intelligent process automation?
Of course, you can not just buy software and immediately “unlock” its benefits. Your company needs to make the decision to automate and then set clearly defined and achievable goals.
- Which processes need the most work?
- Which improvements would tangibly affect your economic bottom line?
- What changes through digitalization will most affect people's daily behavior?
Before you take the first steps, understand your final state. Develop and deploy the PoC (Proof of Concept) and MVP (Minimal Viable Product) that enable you to work towards these goals. And then refine them and increase their complexity as your teams gain automation expertise.
My recommendation? Bet on your own people and let them improve under new technologies. They will give you back in faster adoption of digitization and deployment of intelligent automation within your organization. Intelligent automation, or digitalization in general, is not a project for 3 or 12 months. It is a new time in which you have to start functioning and live so that you do not “miss the train”.
Selecting the right suppliers for intelligent process automation is a crucial step. Within an expanding market, you need to look carefully at what individual solutions offer. With the Kofax intelligent automation platform, enterprises get a wide set of tools. This includes the spectrum from intelligent content processing, through workflow automation, through various tweaks in the form of biometric signatures, verification of fraud in photos and documents, through the generation of custom documents to the holistic unification of the automated ecosystem. Get key insights into the efficiency of your processes and deploy new tools to help your teams work smarter.
With so many new technologies emerging today, getting to the front line is essential to achieve a competitive advantage in a timely manner. The opportunities for improvement are limitless — from the incorporation of machine learning applications to the expansion of RPA capabilities into the most certainly emerging wave of automation using generative AI.
Evaluate how your business approaches automation and consider where IA should enter into your strategies and plans to secure the future.
And in conclusion? I hope I didn't bother you too much in the abbreviations, but after all... IA = Intelligent Automation. AI = Artificial Intelligence.
I wish you a happy hand in your future digitization decisions!
Author: Tomáš Dolejš (LinkedIn)
