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What is AI-powered Automation? Its Implementation and Benefits

Introduction

The advent of AI made organizations take account of their manual inefficiencies and set into action a process to implement and revert these obsolete systems that slow down & hinder business growth. We keep guessing how AI will or won’t affect the workforce, their customers, etc.

Quick fact: A study by McKinsey shows that a total of 8% of enterprises will remain successful if their respective industries digitize and automate at the current rate. (Contract.fit)

What is AI-powered automation

Performing manual tasks that are repetitive and require a lot of resources through machines like robots or cognitive technology is called automation. It helps in the simplification of lengthy processes along with improved efficiency in organization-wide operations.

In the pre-AI world, automation had been mostly associated with robots or machines called Robotic Process Automation (RPA). With the rapid advancements in AI and businesses looking to leverage AI and integrate it within their systems, it becomes a necessity that we understand AI-powered systems clearly to minimize human errors and inefficiencies.

AI & Automation together

For an enterprise to gain a competitive edge in the market you must automate all the manual, redundant & time-consuming processes through robotic automation.

AI and automation are two different entities that come together to give rise to what is called Cognitive Automation.

Artificial Intelligence Automation
AI gives results by collecting information and experiences. Automation is a set of pre-decided guidelines to perform redundant tasks.
AI includes learning and evolving from information. Automation does not include learning & evolving.
AI systems understand data & make decisions independently. Automation only follows the instructions fed into the machine.

Automation thus completes a set of predefined tasks and cannot go beyond the parameters of set guidelines predetermined by humans.

It is when AI is further integrated with RPA that we get a system that can go beyond the human guidelines and perform tasks in whichever way they perceive to be the most efficient.

This amalgamation is what we call Intelligent Automation & it has three key components to it. Let’s discuss.

Intelligent Automation. The three components of Intelligent Automation

AI along with Robotic Process Automation (RPA) and a third component Business Process Management (BPM) is grouped under the umbrella term Intelligent Automation (IA).

Intelligent automation or IA helps enterprises gain a competitive and lasting edge over their competitors in the market. This is especially true for medium-sized organizations to streamline their operations and scale their business. Below we’ve discussed the three pillars of Intelligent automation.

1. Artificial Intelligence (AI):

AI is perhaps the most crucial among all the three components of Intelligent Automation. The cognitive abilities of AI models emulate human intelligence that analyzes, and segregates structured and unstructured data using Machine learning and other complex algorithms. According to IBM, this helps enterprises develop a knowledge base and formulate further predictions. IBM terms AI to be “the decision engine of IA.”

2. Business Process Management (BPM):

Business process management is also called business workflow automation. It is the set of technologies that streamline and automate workflows for improved agility and better consistency for a chosen business. BPM is employed across domains to improve interactions and engagement.

3. Robotic Process Automation (RPA):

Robotic process automation uses software bots to complete back-office tasks like data extraction or automatically filling forms. These robots fit well by the insights provided with AI to increase the use cases of automation and undertake even more complex tasks.

Implementing AI-powered automation

AI automation allows businesses to make data-driven decisions that would not have been possible otherwise. Two factors that need to be considered while implementing automation into workflows are discussed below

1. Identifying use cases and choosing tools: It’s recommended that you choose from repetitive & data-driven tasks that can benefit from automation. Choose AI tools and platforms that align with your business needs.

2. Sanitizing data & integration: Ensure that your data is clean, structured, and accessible, and Integrate AI models into your existing systems and workflows.

3. Democratizing the automation model: This model involves empowering individual teams and employees to develop automation, while a central automation team provides support, training, and guidance.

Use Cases & Benefits

AI-powered automation can have large-scale implementations from speeding up automobile production to boosting insurance processes and addressing regulatory & compliance needs. It can help replace legacy systems that were otherwise resource-intensive, costly, and prone to human error to become aligned to scaling businesses efficiently.

1. Supply Chain Management

Use Case: AI can optimize supply chain processes by predicting demand, identifying potential disruptions, and recommending the most efficient routes for transportation and delivery.

Benefits:Lower inventory carrying costs, reduced stockouts and overstocks, improved delivery rates on time, and increased overall supply chain efficiency.

2. Automotive manufacturing

Use Case: AI can optimize supply chain processes by predicting demand, identifying potential disruptions, and recommending the most efficient routes for transportation and delivery.

Benefits: Lower inventory carrying costs, reduced stockouts and overstocks, improved delivery rates on time, and increased overall supply chain efficiency.

3. Healthcare

Use Case: AI algorithms can analyze medical images such as X-rays, MRIs, and CT scans to assist radiologists in detecting abnormalities and diagnosing diseases more accurately.

Benefits: Faster diagnosis, early detection of diseases, improved patient outcomes, and more efficient use of radiologist's time.

4. Finance & Accounting

Use Case: AI-powered algorithms can analyze financial data and market trends to automate trading decisions, optimize investment portfolios, and execute trades at the best possible times.

Benefits: Improved investment returns, reduced risk through data-driven decision-making, and faster trade execution.

5. Customer Service

Use Case: AI-powered chatbots can handle customer inquiries and support tickets, resolving common issues and answering questions without human intervention.

Benefits: Reduced response times, 24/7 availability, scalability to handle large volumes of inquiries, and cost savings by minimizing the need for customer service representatives.

Business Impact

AI-powered automation or Intelligent Automation is a revolutionary step towards transforming the way enterprises do business. It streamlines workflows end-to-end and helps organizations, especially mid-sized enterprises scale even further. Let’s then have a look at the overall business impact:

  1. Efficient Resource Utilization
  2. Innovation-centered growth
  3. Improve Bottomline
  4. Competitive edge in niche technologies

At MetricDust we are adept at weaving together the intricacies of AI-powered automation into a functioning and efficient system for your organization, that helps you improve your topline while also regulating the bottom line in tandem. This is done by streamlining all functional activities for cost-cutting and savings.