An Intelligent Approach to Business Automation


Humans, Bots & AI Working Together in a Seamless Process

Intelligent automation can power new business process models, enabling organizations to gain greater value from data, systems and human resources. With the right technologies complementing each other in the most relevant ways, it's possible to raise operational efficiency, product quality and service excellence to unprecedented levels.

What is Intelligent Automation?


It's a business automation strategy that integrates Robotic Process Automation (RPA) and Digital Process Automation (DPA) with emerging Artificial Intelligence (AI) technologies like machine learning, natural language processing, and machine vision.

Working together in a way that leverages the unique strengths of each technology, this digital transformation toolset enables end-to-end — and enterprise-wide — process optimization.

Robotic Process Automation

Robotic Process Automation

A Quick Refresher: RPA & DPA


The intelligent automation ecosystem

This type of execution engine can operate on any application or system to automate rule-based tasks – provided these are digital, use structured data, and require minimal exception handling.

Like humans, RPA's software robots (or 'bots') work at the presentation layer rather than the application programming interface (API). This means that they can automate manual tasks, accelerate efficiency, reduce human error and improve compliance without disrupting underlying systems.

Common use cases for RPA include scraping data from the web, collecting social media stats and fulfilling change of address requests. By delegating these high-volume and time-consuming tasks to bots, human workers can focus on work that's more strategic, creative and complex – to deliver better value.

Quick to implement and easy to scale, RPA can deliver ROI fast. It's not, however, a holistic process transformation solution.

Digital Process Automation

Digital Process Automation

DPA is a modern approach to business process management (BPM). This type of solution focuses on optimizing entire processes by automating manual tasks and orchestrating the flow of work from one resource to the next – synchronizing activities, people, data and systems. Beyond this, DPA platforms provide visibility into process performance with analytics and insights —driving continual process improvement.

K2's low-code DPA platform provides users with visual, drag-and-drop designers and wizards for rapidly building custom business process applications that include forms, workflows, data connectors, and reports. With minimal coding required, companies can accelerate development cycles to reduce IT backlogs and allow business users to be more involved in creating their own digital assets.

Often, enterprises struggle to achieve business optimization at scale due to multiple, disconnected systems and applications. A DPA platform like K2 can bridge these divides effortlessly – doing away with the need for complex development and integration efforts.

Comparing and Combining RPA & DPA


Key Differences

Focus

RPA uses software bots to automate tasks that are standardized and structured, while DPA uses multiple tools to optimize entire processes, from preengineering to continual process improvement, powered by analytics.

Skills

With RPA, you can achieve quick wins with minimal disruption to processes and systems. DPA is broader in focus and may require technical skills, depending on process complexity and integration depth.

The Value of Integrating RPA & DPA


Rather than pitting these automation approaches against each other, it’s smarter to combine them.

When deployed together, DPA and RPA can efficiently automate tasks and streamline processes that require multiple resources and work across various line-of-business systems. When the unique strengths of DPA and RPA are united, businesses can realize holistic automation that would not be possible with either approach alone.

In other words: organizations can meet a much broader range of automation needs, faster and more efficiently.

Already have a DPA platform?

Integrate RPA to free people from mundane tasks and automate integrations that are not easily accessible via API.

Already have an RPA solution?

Introduce DPA for improved exception-handling and visibility across all processes. A DPA platform can coordinate multiple RPA, human and system activities seamlessly – routing exceptions to humans, orchestrating manual approvals and powering processes that capitalize on the best attributes of both humans and bots.

K2 and RPA Integration


K2 offers native integration with leading RPA vendors, including UiPath and Blue Prism, to enable full lifecycle business automation. This approach allows humans and bots to work together seamlessly – ushering in a new era of cost reduction, operational accuracy, compliance, and agility.

Webinar on Demand

Enabling Transformation with Robotic and Digital Process Automation

Artificial Intelligence

How Does Artificial Intelligence Fit In?

In many ways, AI is a natural partner for business automation efforts. AI can help automate routine tasks, improve user interfaces and analyze large amounts of data. The data analysis, machine learning and predictive analytics capabilities of AI make it possible to automate many basic decision-making processes in an organization. Employing AI in a process also makes it possible to predict what needs to be done and be proactive in the process by analyzing patterns in historical data and anticipating any roadblocks or constraints

User Benefits of AI


Companies like Google, Microsoft, and Amazon are leading the industry in developing complex AI algorithms and the APIs that can quickly and easily be integrated into DPA platforms like K2.

Using these tools to add AI to DPA and RPA helps reduce the amount of time spent on certain tasks, improving customer experience and reducing costs − without building a pool of data scientists and data modeling toolsets in-house. This cost-effective approach opens up at least two broad categories of AI benefits to users deeper in the organization: natural language interfaces and data-driven insights derived from the larger context in which the business exists

Voice Interface

AI-driven natural language interfaces make interacting with an application easier and speeds up the process. The AI interface can automate many of the steps just by understanding the words spoken and the business context of the request. In addition, AI and machine learning make it possible for an application to learn from each interaction and streamline the process for the next time.

One major advantage of AI is its ability to employ natural language responses, conversational dialogue and language translations along with the ability to gauge intent to streamline and automate common tasks such as filling out forms. AI can analyze key phrases within the text of a user's request to get an idea of a person's intent and automatically fill in a form with the appropriate information

Business Context

AI's machine learning component can provide incredible gains in productivity. With each interaction, the system acquires more data about how decisions are made and apply statistical analysis to develop rules around decision-making. Efficiencies are achieved because machine learning looks at historical data and uses predictive analytics to spot trends and make business decisions based on this data.

Use Cases that Support AI, DPA & RPA


Case 1:

"Intelligent" robotic process automation (RPA) can be used to observe, and learn, what people are actually doing, and then automate those patterns so people don’t have to do error-prone redundant work.

Case 2:

Machine learning can be applied during process execution to, for example, trigger a new process or reroute running processes according to predictions.

Case 3:

NLP can take unstructured data, both spoken and written, to understand the intent and automate business processes by grabbing actionable data to reduce the time and resources required to successfully complete business processes.

Looking forward, AI will be instrumental in improving the user experience within the business workflow, by applying other AI techniques on user interactions and browser uses, and by analyzing page flow. As business apps provide better user experiences, we’ll be seeing both better operations and better strategic differentiation for the organizations that employ them.

Intelligent Automation

Business Benefits of Intelligent Automation

Compete on customer experience:

Reduce response times, enhance service levels and elevate product quality. With the support of RPA and AI, humans are able to focus on the more complex customer service cases, to enhance the overall customer experience.

Support compliance and risk management:

Meet regulatory obligations more efficiently, access process data in real time and enable granular reporting to meet your audit defense goals.

Dive deeper into your data:

K2's DPA platform can easily connect and integrate data systems into your process management tools. If data is unstructured, AI can transform this into a bot-friendly format, while also unlocking insights that augment human decision-making capabilities.

Re-think roles:

Empower human workers to shift their focus towards higher value tasks that require strategic thought, creativity and/or professional judgment.

Next Steps


Ultimately, you need to make sure that you understand the unique value that each technology brings to the table, so you can reengineer processes accordingly.

It's also important to hold your intelligent automation strategy together with a foundation that is agile, scalable and user- friendly. With a DPA platform like K2, you can start small and scale as your needs grow by easily integrating RPA and then leveraging AI services from a range of third-party providers as and when you need them.

When intelligent automation is well-planned and executed, organizations can unlock new revenue streams, enhance profitability, transform the customer experience and stay ahead of the pack.