Intelligent Automation, the next step in the digitized enterprise, is the use of Artificial Intelligence and other smart tools to automate various operations of a business.  Its benefits and use in businesses are being recognized the world over.

Here’s what Intelligent Automation is all about.


What is Intelligent Automation?

Intelligent Automation is the incorporation of intelligent technology such as Machine Learning (ML), Deep Learning (DL), Intelligent Character Recognition (ICR), Natural Language Processing (NLP), Process Mining (PM), and Data Mining (DM) into an interconnected and interoperable process that enables automated learning and adaptation in all business activities.

Intelligent Automation eliminates time-consuming labour, creates an efficient interface between humans and technology through applications such as chatbots, and evolves with use.  The continuous learning aspect of AI enables accurate predictions and flagging of potential risks and threats to operations, which can, in turn, trigger automated remediation and course corrections in time.

Intelligent automation addresses an advanced variant of mechanisation in which machines imitate human activities and have mental capacities, including regular language handling, discourse acknowledgement, PC vision innovation, and AI. Such kind machines with mechanised knowledge grasp the tremendous measure of organised and unstructured information, examine, comprehend and learn it in a hurry, and cleverly computerise cycles to get more functional effectiveness along with business proficiency. The idea of robotization in the computerised world is developing, and innovation is advancing, adding more abilities of human minds into machines step by step. As per Endlessly showcases Analysis done last year, the BFSI mechanical mechanisation market is supposed to develop at a CAGR of 75% and is expected to arrive at USD 835 million by 2020. The report additionally says that the quick reception rate demonstrates that BFSI organisations will zero in on putting resources into preparing and responsibility for computerization advances, when contrasted with putting resources into proficient administrations to robotize processes, over the determined period.

[Source: HappiestMInds]

The three parts of Intelligent Automation

The intelligent automation stage gives many advantages across ventures because of the utilisation of a lot of information, accuracy of estimations, investigation and coming about business execution. The three components\parts of Intelligent automation are :

Robotic Process Automation (RPA)

The first part of Intelligent automation is Robotic Process Automation (RPA). Robotic Process Automation (RPA) is the utilisation of programming robots, or "bots," to finish tedious, rules-based errands inside or between PC frameworks. The bots play out this work through existing UIs, so there is a compelling reason needed to develop unique programming reconciliations.

With RPA, clients train bots to work programming nearly as a human wouldn't (really at the keystroke level, yet utilising a similar UI and creating similar outcomes). Processes that require numerous projects to finish can likewise be finished along these lines. Once prepared to play out an undertaking, bots can then scale to fulfil evolving needs.

Artificial Intelligence (AI)

The most basic part of intelligent robotization is artificial intelligence or AI. By utilising AI and complex calculations to examine organised and unstructured information, organisations can foster an information base and plan expectations in light of that information. This is the choice motor of IA.

Business Process Management (BPM)

The last part of Intelligent Automation is Business Process Automation. Task management centres around individual assignments while BPM notices the entire start-to-finish process. Project the executives allude to a one-time extent of work while BPM centres explicitly around processes that are repeatable. Through consistent interaction reengineering, associations can smooth out their general work processes, prompting expanded efficiencies and cost-reserve funds.


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How does Intelligent Automation Work?

Many organizations are putting resources into automation like never before as compared to previous eras. As indicated by IDC, worldwide advanced change spending will top $2.1 trillion by 2020.

[Source: Workato]

It assists representatives with taking care of business quicker, and better. For instance, experiences remarks, connections, and dealing with the groups in light of the fact that astute automation is working for them on the most value-based and redundant exercises. We generally say, 'I lack the opportunity and energy to do that since I want to do this. Presently, we possess more energy for subjective work.

The worker experience is basic, however, so is the client experience. Holding up in a line to get a train ticket, standing by to see a bank specialist, this can be all settled by keen automation. The reception of intelligent automation is very high. The term was formally begun in 2017, however, over half of the organizations all over the planet have previously executed it. That will ascend to 70%, as per Deloitte, in the approaching two years.

In any case, simply 15% have had the option to scale these changes. So today, the critical test for all organizations is tied in with scaling, executing such advances across divisions, and across organizations inside a similar gathering.

To broaden the skylines of business process automation by a significant degree, Intelligent Automation consolidates the errand execution of RPA with the AI and investigation capacities of programmed process revelation and cycle examination as well as mental advances.

[Source: Deloitte]

What are the major challenges for Intelligent Automation?

There are various major challenges a company or any organization faces, followings are mentioned below :

Establishing a Robust Governance

Corporate administration applies to all organizations, from enormous multinationals to new companies. Great corporate administration helps in diminishing the expense of capital because of the decrease in risk. Be that as it may, numerous associations disregard this essential part of maintaining an effective business.

Focus on Risk Management

Board individuals should lay out a successful framework for risk oversight and the executives. 'Risk' isn't bound to consistent risk. Notwithstanding, a more extensive term incorporates all dangers of an organization - network safety, lawful, and monetary. Successful gamble the executives prompt better independent direction.

Creating a proper IT environment and technological ecosystem

Carry out an interaction to manage project changes. However a couple of ventures carry on with their life cycle without change, you should guarantee to control changes instead of permitting them to control you.  An IT biological system is "the organization of associations that drives the creation and conveyance of data innovation items and administrations. Innovation biological systems are item stages characterized by centre parts made by the stage proprietor and supplemented by applications made via independent organizations in the outskirts. The centre company's item has significant but restricted esteem when utilized alone yet considerably increases in esteem when utilized with the corresponding applications.

Teaching necessary metrics and assigning tasks

Teaching Necessary metrics and arranging tasks is a basic part of the show that frequently happens days prior to something new being instructed. Arranging, creating and coordinating guidance are probably the greatest obligations of the organizations.

At the point when you really plan illustrations, every day showing assignments becomes a lot simpler and more fruitful. Numerous employees feel that they lack the opportunity and energy to devote to cautious tasks arranging.


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How is Intelligent Automation different from RPA and Hyperautomation?

Before we go into details about Intelligent Automation, it is important to understand the fundamental difference between Intelligent Automation, RPA, and Hyperautomation.

  • RPA is a subset of Intelligent Automation. It is used to automate routine, repetitive, and predictable tasks through orchestrated activities that emulate human action. It eliminates time-consuming tasks such as swivel chair data entry. It is driven by rules.
  • Intelligent Automation is the use of Artificial Intelligence tools to process higher-function tasks that require some level of reasoning, analysis, judgment, and decision. It is driven by AI and is in turn a subset of Hyperautomation.
  • Hyperautomation is the interconnection of different automation tools serving multiple processes in order to create a common platform that unifies systems, data, and processes of an enterprise.
A chart showing how RPA, IA & Hyperautomation are interconnected

How does Intelligent Automation work

Intelligent Automation includes one or more of the following tools that serve multiple functions:

1. Intelligent Data Capture

Data is, building on Sherlock Holmes’ impatient cries, the clay that makes the bricks of an enterprise.  The automated capture of data in the digital format and its classification and storage as a logical entity depends on intelligent processes that can recognize the data.   OCR and ICR processes are increasingly leveraging AI and ML tools for the smart capture of data from various sources.

An effective intelligent capture solution that is part of Intelligent Automation will:

  • Extract structured, poorly structured, and unstructured data.
  • Pull data from multiple sources.
  • Classify extracted data according to pre-set rules.
  • Make available the data for other

2. Intelligent Process Automation (IPA)

An efficient and successful company has structured processes that follow predictable steps and have (largely) predictable outcomes.  Such processes can be easily automated to remove bottlenecks caused by manual delays in intermediate steps. Intelligent Process Automation (IPA) is a collation of technologies that help in such well-defined processes.

Intelligent Process Automation typically includes Digital Process Automation (DPA), Robotic Process Automation (RPA), and Artificial Intelligence (AI).

  • Digital Process Automation or DPA, derived from Business Process Management practices, is the automation of various operations of a company and the optimization of the workflow. It typically involves the automation of tasks that involve human interaction such as in HR, management, sales, and marketing. It often involves external users such as customers, vendors, and other stakeholders, and helps in creating better user experiences. Some examples of the use of DPA include automatic background checks, transferring data across multiple applications (e.g. between ERP and ordering system), generating login credentials, setting up accounts, and automatic email announcements.
  • Robotic Process Automation or RPA is the automation of time-consuming, labour-intensive repetitive tasks that follow a predetermined set of rules. RPA is used to automate smaller processes that are part of larger, complex ones. RPA is frequently used in extracting information from invoices to input into ERPs.
  • Artificial Intelligence or AI includes technologies such as ML, NLP, and computer vision, that enable systems to analyze, reason, judge, and decide based on available data. This is done by recognizing patterns in data and learning from past decisions to make increasingly intelligent choices.

3. Intelligent Communication Management

Communication is a critical aspect of business and includes internal interactions as well as communication with external vendors, clients, and customers.  Intelligent tools are being increasingly employed in communication management in applications ranging from first-level customer support (e.g. chatbots), content creation,  crisis management, and strategy development. This again leverages multiple tools such as OCR, Voice recognition, NLP, and ML.

4. Intelligent Data Management

The collection of all business information into structured databases is passé in the era of big data. AI and ML tools can manage data more intelligently than simply categorizing data in database tables. Intelligent data management uses tools from various areas of operation such as Business Intelligence (BI) and Online Analytical Processing (OLAP), Cluster Analysis, Network Analysis, Data Mining, NLP, ML, and cloud computing. It provides an efficient informational platform for better storage, security, analytics, and decision-making in various areas of business operation.


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How is Intelligent Automation used in different industries?

The mixup of man-made and Intelligent automation is beginning to significantly impact how business is finished in virtually every area of the economy. Intelligent Automation frameworks sense and integrate tremendous measures of data and can mechanize whole cycles or work processes, learning and adjusting as they go.

Intelligent Automation in Commerce

The worldwide retail market was supposed to be around 26.7 trillion U.S. dollars by 2022 contrasted with 24.8 trillion U.S. dollars in 2019.

With additional clients buying on the web and issues like late conveyances of items. With the assistance of Intelligent Process Automation and Artificial Intelligence, a web-based business industry will actually want to adjust to the impending times. Mechanizing tedious cycles behind internet-based exchanges makes web-based shopping more pleasant for clients and permits web-based business organizations to construct long-haul associations with their clients.

At the point when a client makes any e-shopping or e-buy, different cycles need to happen behind the scenes before the buy is made and it arrives at its last objective. Subsequently, each physically finished advance following a buy is likewise vulnerable to human mistake, which is lamentable for both the merchant and the client. Automated machines can improve speed, exactness, and effectiveness. Utilizing them limits human blunders while entering information into the framework, making them ideal for redundant errands. For instance, when you shop on the web, man-made consciousness (AI) can make the cycle more straightforward by tolerating extra instalments and cash transformations, getting the proper transportation records, and giving discounts.

Intelligent Process Automation can make processes in the online business industry more splendid, quicker, more effective, and adaptable. It empowers Human Resources to turn out to be more useful. Fortunately leisurely developing quantities of web-based business ventures are becoming mindful of the benefits of Intelligent Process Automation and are embracing it to work in their organizations.

Intelligent Automation in Intellectual Property

On the off chance that an individual makes or concocts something outstanding and valuable, it's a good idea that the person ought to reserve the option to utilize this creation and gain monetary advantages, while no other person could expect to be such a right. Practically speaking, it could be difficult to control the use of IP objects since they are elusive and have no actual cutoff points. Various individuals can duplicate and consume such merchandise despite the fact that it's unlawful. The role is indispensable. It mainly focuses on accuracy and efficiency.

Intelligent Automation in Insurance

The Insurance Automation market has been developing dangerously fast and it is expected to reach almost US $600 billion every 2022. While the banking and monetary administrations space embraced this pattern sometime in the past, the reception of robotization in the protection business has been a lot slower. Insurance agencies are simply beginning to send off pilot mechanization programs, with both RPA and Intelligent Automation, and the effect of these advancements on the area is supposed to be huge.

[Source: Gartner]

Benefits of Intelligent Automation

There are a few clear advantages of automation that should be visible in numerous computerization projects and are generally referred to as essential positive outcomes. Among others, they include:

Cost savings

The use of Intelligent Automation in the mundane, labour-intensive activities of a company can result in significant cost savings.  McKinsey showed that 45% of current paid activities that cost an equivalent of $2 trillion in total annual wages, can potentially be automated using AI tools. Furthermore, the manual performance of redundant, automatable tasks decreases the productivity of the company and low productivity can cost employers around USD 1.8 billion dollars annually.

Time savings

Many repetitive, mundane, manual business processes eat up a lot of time, irrespective of the department and nature of work. For example, low-level, automatable tasks have been reported to consume 30% of IT departments’ time, 47% of the AP department’s time, and 75% of the time of HR and Payroll department staff. This naturally leads to time delays and associated penalties that have a ripple effect on the productivity of the team and company. Intelligent Automation can help avoid such delays and bottlenecks in the daily operations of the company.

Error reduction

It is said that a human being is likely to make 10 errors in every 100 steps when performing redundant work.  Where the human brain can fail due to fatigue from repetitive action, Intelligent Automation can, in fact, improve in performance due to the deep and continuous learning processes involved.  Intelligent Automation can not only eliminate errors but also increase the likelihood of predicting problems and bottlenecks through smart analytics, which can help in early resolution.

Transparency

Intelligent Automation, through centralization of process and data management, can enhance transparency across the board while also logically integrating the business functionalities spread out across the organization. Intelligent Automation can also set up security measures and traceability of information, which ensures better compliance with relevant regulations.

Risk readiness

The adoption of Intelligent Automation by businesses around the world was found to have increased manifolds during the pandemic times. About 55 per cent of products and/or services were found to be fully or partly digitized as of July 2020, compared to 35 per cent in December 2019 and 28 per cent in 2018. Nearly half of 800 executives surveyed accelerated the adoption of automation “moderately” during the pandemic, and roughly 20 per cent reported “significantly increasing” automation.  Intelligent Process Automation has been a key backbone in keeping businesses running with reduced staff, remote work, and digital coordination.

Operational consistency

The ability to coordinate various Intelligent Automation tools into a larger hyper-automation platform within an enterprise can enhance data incoherence and eliminate process barriers.


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What is an example of an Intelligent Automation solution that makes use of Artificial Intelligence?

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Applications of Intelligent Automation

Intelligent Automation smoothes out processes that were generally included in manual assignments or in view of heritage frameworks, which can be asset escalated, expensive, and inclined to human blunder. The utilization of IA range across enterprises, giving efficiencies in various regions of the business.

Procure-to-Pay (P2P)

The procure-to-pay process is best suited for Intelligent Automation because of the existence of repetitive and time-consuming tasks. Vendor management, invoice management, and payment details from multiple sources and vendors lead to complicated manual management. With the increase in transaction volumes, and with more emphasis being paid in modern times to paperless and online transactions, the Intelligent Automation of the P2P cycle has assumed importance to businesses. Intelligent Automation of the P2P process streamlines the purchase process, reduces paper clutter, enhances the transparency of the invoice route, saves time and money, increases employee productivity, and improves vendor relationships.

Quote-to-Cash (Q2C)

The Q2C is the functional reverse of the P2P process;  while the latter is associated with procuring products /services by the company, the Q2C deals with sales of products and services by the company. An Intelligent Automation-enhanced Q2C process can ensure quick and reliable cash flow, fulfilment of orders, and effective bill management.  Specific Q2T tsks that benefit from Intelligent Automation include order fulfilment, new customer onboarding, and account provisioning.

Employee management

The onboarding and offboarding of employees in an organization is a tedious process, especially when the organization exceeds a critical size defined by its competency.  The management of employee paperwork, processing payment of remaining salary and expenses, and ensuring the safe return of company property are some of the activities in the offboarding process that, when performed suboptimally, can hurt the company.  Onboarding activities such as initiation of the employee,  employment paperwork, and HR management are important in preserving employee morale and loyalty.  Intelligent Automation can be used to electronically capture information from documents such as resumes and employee records through robotic process automation (RPA) and automating communication with the employees (i.e., automated welcome emails).

Customer management

A survey by Gartner in 2018 Customer Experience  is the “new marketing battlefront.” While the elimination of humans from customer management is not considered a smart business move, Intelligent Automation can be used as a supplemental tool for first-level communication.  Intelligent Automation chatboxes can save time and provide round-the-clock connectivity to the customer. It can identify and categorize topics of conversation for subsequent routing to the appropriate human agent.

Inventory control

The inventory control process includes activities such as generating work orders, creating invoices, and shipping. As the company scales up in operations or moves into an omnichannel operation, AI can streamline complex back-office processes and prevent supply chain blocks.

Marketing

Marketing is now an omnichannel activity with social media playing a vital role in enhancing visibility. Automated creation and posting of marketing content (including context-specific ads) can help with better reach and visibility to the company.

Future Of Intelligent automation

The worth of intelligent automation in this present reality, across enterprises, is undeniable. With the automation of dreary errands through IA, organisations can diminish their expenses as well as layout more consistency inside their work processes. The COVID-19 pandemic has just facilitated advanced change endeavours, energising greater speculation inside the framework to help automation. As remote work additionally floods, jobs will keep on developing. People zeroed in on low-level work will be redistributed to execute and scale these arrangements as well as other more elevated level errands. Centre directors should move their emphasis on the more human components of their responsibility to support inspiration inside the labour force.

Robotization will uncover abilities holes inside the labour force, and representatives should adjust to their constantly changing workplaces. Center administration can likewise uphold these advances in a manner that mitigates uneasiness to guarantee that representatives stay versatile through these times of progress. Clever robotization is without a doubt the fate of work, and organizations that renounce reception will find it challenging to stay cutthroat in their separate business sectors.


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Adopting Intelligent Automation in an enterprise

Walter Lippman said that you cannot endow even the best machine with initiative. The initiative must come from the human behind the enterprise.

The adoption of Intelligent Automation in a business is not a trivial matter of changing technological tools.  It requires an in-depth understanding of the core competence of the company, its business needs, and changes in the fundamental approach to the running of the business.  Planning is, therefore, an essential prerequisite to the adoption of Intelligent Automation.

The key steps in the adoption of Intelligent Automation in a company’s portfolio are:

  1. Planning:  What are the processes that would benefit from Intelligent Automation?  Answering this is essential to deliver the value promised by Intelligent Automation and will serve as a baseline to stabilize, standardize, optimize and operate the Intelligent Automation tools.
  2. Tool assessment: There are various Intelligent Automation tools that are available in the market that can serve various segments of the industry.   The budgetary restrictions, functionalities offered and service provision are some of the important factors to be assessed before choosing an Intelligent Automation tool.
  3. Installation of the Intelligent Automation solution:  Once the tool(s) is/are chosen, it is installed with the assistance of the tool provide. The modification, and adaptation of the Intelligent Automation tools to the requirements of the company’s activities and needs is an essential aspect here and must be discussed with the solutions provider before installation.
  4. Training:  All stakeholders in the Intelligent Automation solution adopted by the company must be trained to operate/manage the Intelligent Automation.  The training must be periodically updated to stay current.
  5. Performance audit:  Even after the full deployment of the Intelligent Automation tool, periodic performance audits are required to ensure that the system is performing in accordance with the needs of the company. Such audits must be carried out with specific performance metrics that match industry and peer group benchmarks. These audits can be performed by the expert within the company or by the provider if such a service has been promised by them.

Nanonets for Intelligent Automation

Nanonets is an Intelligent Automation software that leverages OCR, AI and ML capabilities to automatically extract unstructured/structured data from PDF documents, images, and scanned files. Nanonets automation handles unstructured data without much difficulty and the AI also handles common data constraints with ease. The Nanonets AI also ensures a high accuracy while processing documents requiring minimal rework or revision.

Some specific benefits of using Nanonets as an Intelligent Automation solution are:

  • The flexibility of using multiple data types
  • Customizability and custom training of models to suit specific needs
  • Dynamic learning of the ML engine for a better fit with the business activities
  • No need for postprocessing, thus freeing employee time for better activities
  • The Deep Learning and object detection techniques overcome common data constraints that affect text recognition and extraction
  • Requires no in-house team of developers

Take away

Intelligent Automation is the future of business management. Intelligent Automation solutions can increase profits and productivity, enhance customer satisfaction, improve bottom lines, and build worker morale.  When integrated as part of routine business management practices, Intelligent Automation can help with visualization, workflow automation, and no-code/low-code tools so that companies stay competitive in this increasingly digitized business world.

Quickbooks Accounts Payable Automation


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