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Adopting an Intelligent Approach to Automation Gives Businesses a Competitive Edge
The working ecosystem of humans, bots and AI technologies together help businesses achieve a seamless workflow experience

By Holly Anderson, senior director of product marketing at K2

Evolving and more sophisticated Artificial Intelligence (AI)-based technologies are helping organizations make their automation solutions more intelligent. As AI technology has matured and become more intuitive, the concept of "intelligent automation" has quickly gained traction and is revolutionizing how work is done.

Intelligent automation is a business strategy that integrates AI technologies, like machine learning, natural language processing, and machine vision, with automation. It is the combination of AI with Robotic Process Automation (RPA) technology, which uses AI capabilities to partially or fully automate manual, repetitive human activities, and Digital Process Automation (DPA), a digital solution that optimizes processes through automating manual tasks and orchestrating workflow. The combination of all of these technologies working together cohesively and using the unique strengths of each result is intelligent automation. This digital transformation toolkit of technologies can replace the often mundane and repetitive tasks previously managed by humans (like data entry) and help businesses improve efficiency, reduce errors and obtain end-to-end process optimization.

In March 2019, Forrester surveyed over 300 business and technology decision-makers and found that the business goal of accelerating digital transformation now outweighs the business goal of cost reduction as the primary focus of process improvement. Obtaining digital transformation continues to be a primary objective for businesses in today's competitive and customer-focused market, and process automation is often the cornerstone to a company's digital transformation initiative. Deploying digital technologies like DPA and RPA together helps to advance the integration of intelligent automation, which ultimately helps accelerate the digital transformation process.

Organizations are predicted to increase their adoption of AI-related technologies as AI technology and its capabilities mature. The RPA market is predicted to grow by $3.97 billion by 2025, forecasted to experience over a 30 percent increase. The adoption of DPA is also expected to grow, with the global market of DPA forecasted to expand to over $14 billion by 2024. The anticipated rapid expansion of these two AI-based technologies reflects how AI capabilities can augment automation solutions to solve a wide range of business problems more efficiently. Although it can be challenging and intimidating for IT professionals to deploy an intelligent approach to business automation, organizations that leverage both RPA and DPA with AI technologies can realize a wide range of competitive advantages.

Optimizing and using an intelligent automation-focused strategy can bring the following technologies to life and achieve these business benefits:

Reduce common human errors and improve productivity. "Intelligent" RPA (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 the redundant error-prone work. This automation of certain repetitive tasks helps open up time for employees, liberating them from time-consuming, mundane work so they can instead focus on more strategic, higher-value work. This can also result in improved customer experience. Leveraging the combination of RPA and AI, businesses are then able to free up employees to better hone in and address complex customer service issues, helping to enhance the overall customer experience.

Make business processes more intuitive and strategic. Machine learning can be applied during process execution to trigger a new process or reroute running processes according to predictions. 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.

Leverage actionable data to save time and improve efficiency. The AI-technology of natural language processing can take unstructured data, both spoken and written, to then understand the intent and automate business processes by grabbing actionable data to reduce time and resources required to complete certain tasks. 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.

Unlock multi-layered data to make informed business decisions. DPA technology can connect and integrate data systems into 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. With each interaction, the system acquires more data about how decisions are made, and statistical analysis is applied to develop rules around decision-making.

In looking forward, it is clear that AI and AI-based technologies will be instrumental in improving the user experience within the business workflow. However, ultimately organizations need to understand the unique value that each technology brings to the table first, so they can reengineer processes accordingly to truly optimize the benefits of an intelligent automation approach. When well-planned and executed strategically, intelligent automation can enable organizations to unlock new revenue streams, stay ahead of competitors and achieve their digital transformation goals. 

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About the Author

Holly Anderson 

Holly is the senior director of product marketing at K2 where she leads product messaging, value proposition and customer communications. She has more than a decade of experience with K2 both in-house since 2006. Prior to her time with K2 she was a consultant.

Published Thursday, December 05, 2019 7:35 AM by David Marshall
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