Utilizing AI Hyperautomation Frameworks

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digital visualization of hand during a dial to RPA or AI Hyperautomation

Hyperautomation holds the promise of the business future we’re working toward. Gartner defines Hyperautomation as follows: “Hyperautomation deals with the application of advanced technologies including AI and machine learning to increasingly automate processes and augment humans.”

Here we will outline the basics of two important components of hyperautomation, RPA (Robotics Process Automation) and AI (Artificial Intelligence), their transformative power to realize new revenue, and how a solid foundation of knowledge management and enterprise search is critical for capturing value from your investment in these initiatives.

Basics of RPA

The RPA space is still in its infancy. In a nutshell, RPA is a process automation framework that allows you to automate workflows, or tasks, within your business, by building a process library and leveraging AI tools for machine learning.

Let’s look at two RPA automation examples to help you better understand how it works:

Example 1: Customer Support

Support Staff can save time on multiple and repetitive calls by using RPA to address issues before regular users become aware of them. This is done though using regular diagnostics and work by bots to achieve the objectives.

Example 2: Technology Enabled Auto-complete

RPA can be used to assess the most popular functionalities of tools in use in a department with the use of bots. Interfaces can then be created to enable autocompletion of tasks, so staff does not have to fill out forms multiple times.

Ultimately, hyperautomation processes will pair RPA functionality with AI algorithms. This helps with prospecting and sales by understanding the internal company data your company already has and helping employees cut through the noise so they can find what they’re looking for. This is accomplished by understanding individual search interactions and the content of the queries. For example, if a user has a long, complicated search that they’re trying to resolve, AI algorithms will begin to understand the context, the intent, and predict the results based on individual needs and situations. For example, if you type “restaurants in Boston, Massachusetts” into a search engine, an AI algorithm will analyze the words you’ve used, your location, and other factors to understand whether it’s a local or broad question. This understanding is what gives automation its transformative power.

The Transformative Power of AI

Should everything that can be automated actually be automated? Yes, automation can save you a lot of time, but time savings isn’t everything. At its core, hyperautomation is about using AI to automate repetitive tasks. Sometimes, automation is about efficiency, and getting things done in the most efficient way possible. We are already seeing the impact of AI on business functions as they are increasingly executed by the support of artificial intelligence solutions. For example, automation for data processing, data analytics, and business process automation has been a key driver in the adoption of AI within enterprise companies. In fact, experts predicted that by the end of 2021, hyperautomation would account for over two-thirds of business process automation adoption worldwide. Many claim this milestone has even been achieved ahead of schedule.

AI is already embedded in the digital infrastructure of many organizations and automates millions of jobs. We may not think about it, but things like smart reply options in our email, spam filters, personalized predictive typing, maps and directions, and making travel arrangements are all fully or partially powered by AI tools. Mundane tasks such as data entry, data storage, scheduling, and log analysis are augmented and optimized. AI solutions are capable of completing tasks that would require intelligence if done by a human, but the underlying aim is not to slash the number of employees, but rather to liberate them from tedious work routines – “busy work”– so that their activities can be more fully integrated into the company’s value creation processes.

Realizing More Business Opportunity with Hyperautomation

Hyperautomation is not only helpful for increased efficiencies and timesaving, but it is also the future of profitable business growth. The last year saw an uncommon acceleration in digital migration and a shift from thinking of business transformation as something that happens gradually to something that needs to happen immediately. AI will support the transformation of business processes to an even greater degree moving forward to help companies adapt and rapidly pivot based on up to the minute information. Businesses now need the ability to speedily readjust to transformative events in our world, and circumstances that they couldn’t predict or see coming.

The term “hyperautomation” also implies optimizing or upgrading traditional business processes to enhance flexibility and agility. At the same time, these developments are also a means of discovering and realizing new business opportunities and revenue streams. What is the impact of AI on revenue? AI can be used to analyze and track sales, predict which products will sell best, and recommend the best time and place to place an order. AI is being used more frequently in sales interactions to help salespeople provide the best customer service possible – and in turn, increase profits. AI can also come in handy with the decision-making process when products are being sold. For example, AI can analyze the purchase history of a customer to better understand their preferences and suggest the best products they might like to purchase.

Ultimately, the impact of AI, when used correctly, delivers a better customer experience. As more AI informed are decisions are made entirely using data-driven solutions, efficiencies will rise across the globe. However, the best benefits of these advancements can only be achieved when companies have a solid foundation in Knowledge Management and Enterprise Search. Enterprise Search is powered by AI algorithms that are trained to recognize text from search data and process billions of data queries per day. If you want to see ROI from hyperautomation, you need to be using Enterprise Search. The technology can help you discover new prospects, automate manual outreach, and deliver a better customer experience.

Enterprise Search and robust Knowledge Management allows you to conduct keyword research, prospecting, and automate your internal outreach process. For example, you target specific prospects with relevant messages and the answers they are looking for immediately. If you’re researching keywords related to your company’s service offerings, you can use the information in your enterprise search software to create relevant marketing campaigns and content. Once you’ve developed your keyword research, you can build a prospecting list. This is where you can find, and target leads to ensure you’re reaching the right people and creating the most qualified leads. Additionally, Enterprise Search allows you to use data to make more informed decisions. For example, you can use your internal sales data to find qualified leads. With all of these benefits, it makes sense to use enterprise search.

Your business can better manage customer interactions across your entire organization – from prospect to sales and beyond – when it has Artificial Intelligence working alongside humans doing the heavy lifting of completing repetitive tasks. Hyperautomation’s impact on Enterprise Search AI has already begun to influence the way people search and interact with Enterprise Search results because of its dynamic approaches to solving problems, sorting through data, and finding answers. We are living in an era where automation is the key to unlock any business opportunity and for those business owners who want to realize more revenue, investment, and commitment to hyperautomation strategy is going to be critical in staying ahead of the competition.

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