Achieving The Future of Automation Through AI And Machine Learning

By Sean Shahkarami, CEO — Opilio

Most businesses today now rely on some form of automation to support their processes, such as auto-generated invoices or payroll checks, for example. Auto-scheduling posts on social media accounts is another.

These, and other similar forms of automation, streamline business processes by cutting down on manual work and saving businesses time and money. Most, however, do not enhance the impact of the particular task being automated — they simply put it on autopilot.

By integrating artificial intelligence and machine learning into automation, businesses can go beyond streamlining processes to making them smarter. AI-powered automation transforms common business processes into intelligent processes, making them adaptive, insightful, and self-optimizing.

The following are some examples of how today’s businesses are leveraging AI to enhance the performance of their automation processes.

AI-powered recommendation engines

Recommendations are a foundational element of customer service. In the retail world, sales associates assess a customer’s needs and make recommendations based on their knowledge of the products they sell. Even wait staff at restaurants are often called upon to recommend a dish based on a diner’s appetite and tastes.

Digitalization has automated the customer service process by providing consumers with a variety of options to choose from. An e-commerce website is a basic example of this. 

Rather than providing a digital customer service rep, basic websites provide a menu to help consumers navigate to the items they want. The future of automation leverages AI to empower virtual customer service reps that analyze consumers’ preferences and interests to make intelligent recommendations.

An emerging automation trend involves combining conversational AI with intelligent recommendation engines to revolutionize the service websites can provide. Rather than providing a navigational menu, businesses can simply provide an AI-powered virtual representative.

Conversational AI allows visitors to a specific website to express their needs just like they would upon entering a brick-and-mortar store and being greeted by a sales rep. They state, “I need a supplement for high blood pressure,” prompting a series of relevant questions that ultimately result in an intelligent recommendation based on the visitor’s unique needs and profile. Rather than forcing consumers to search through a site and explore descriptions in search of the right product, businesses can now provide AI-driven automation that assesses the need and provides solutions.

AI-powered predictive analytics

In the industrial space, preventive maintenance has traditionally meant regular maintenance. Essentially, businesses automate the maintenance process by ensuring equipment is regularly maintained. Digitalization has improved this process by providing alerts when maintenance is needed and automating the ordering of parts needed to conduct maintenance.

With AI-powered automation, businesses can move from preventive maintenance to predictive maintenance. Predictive analytics, which analyzes historical data to predict future outcomes, allows businesses to enhance their maintenance by uncovering needs that arise outside of normal patterns.

In manufacturing, for example, businesses can utilize sensors on equipment to track vibrations, temperature, and pressure. Data gathered by the sensors can be used to predict failures and prompt action to avoid them, as well as fine-tune maintenance schedules. Ultimately, this type of predictive maintenance leverages automation to decrease downtime and improve productivity.

Predictive analysis has applications that go far beyond equipment maintenance, however. In finance, for example, predictive analytics can increase revenue cycle velocity by better predicting cash collections. Organizations can use those predictions for data-driven financial forecasting.

Similarly, in the HR sector, predictive analytics can drive automation in training that leads to greater outcomes. Market, company, and employee data can all be assessed to help companies predict future skill gaps, and the results can then be used to trigger personalized training paths designed to ensure employees are future-ready.

AI-powered computer vision

Computer vision transforms video monitoring into an intelligent business process. Rather than simply providing video access to processes — such as security cameras that allow safety inspectors to scan for potential dangers — computer vision creates an end-to-end automation that monitors areas, detects problems, and triggers responses designed to minimize negative impacts.

Automated visual inspections leverage AI for quality checks, detecting defects in products at various points in the production process. When a problem is detected, computer vision systems can log the defect, trigger a rejection, halt manufacturing, or request human interaction — all in real time. AI can further automate the process of determining the cause of the defect and initiating the process for performing any needed repairs to production equipment.

Computer vision can also automate document processing. Using AI, computer vision can streamline data entry by extracting and classifying information provided in forms, receipts, invoices, and other business documents. It can then validate all necessary information has been provided, issuing alerts and requesting completion when needed, as well as manage the data workflow by routing information to the proper recipients and tracking its movement through the entire business process.

Artificial intelligence propels automation into the future, empowering processes that are intelligent, innovative, and impactful. In virtually every industry, AI-powered automation holds the keys to unlocking enhanced efficiency and scalability. 

Shifting from simple to intelligent automation allows businesses to better resource employees, better serve customers, and more effectively compete in today’s tech-driven business world.

Sean Shahkarami is the CEO of Opilio, a leading AI company aimed at changing the way businesses mobilize their data. Opilio is at the forefront of automating data management, delivering innovative solutions that streamline workflows, eliminate manual tasks, and allow organizations to allocate resources more strategically. Opilio’s use of machine learning and AI empowers businesses to unlock their data’s full potential, facilitating accurate predictions and data-driven decision-making across all areas of their operations. Opilio also offers seamless ERP integration through partnerships with industry leaders, providing tailored solutions for its clients. One of Opilio’s standout capabilities is its expertise in custom API development, enabling seamless data flow between systems without the need for disruptive platform changes. Opilio empowers organizations across industries to optimize operations, foster collaboration, and remain at the forefront of innovation, making it the preferred partner for businesses seeking comprehensive solutions.