--This paper introduces an innovative Applicant Tracking System (A TS) enhanced by a novel Robotic process automation (RPA) framework or as further referred to as MLAR. Traditional recruitment processes often encounter bottlenecks in resume screening and candidate shortlisting due to time and resource constraints. MLAR addresses these challenges employing Large Language Models (LLMs) in three distinct layers: extracting key characteristics from job postings in the first layer, parsing applicant resume to identify education, experience, skills in the second layer, and similarity matching in the third layer . These features are then matched through advanced semantic algorithms to identify the best candidates efficiently. Extensive performance benchmarking shows that MLAR outperforms the leading RPA platforms, including UiPath and Automation Anywhere, in high-volume resume-processing tasks. When processing 2,400 resumes, MLAR achieved an average processing time of 5.4 seconds per resume, reducing processing time by approximately 16.9% compared to Automation Anywhere and 17.1% compared to UiPath. These results highlight the potential of MLAR to transform recruitment workflows by providing an efficient, accurate, and scalable solution tailored to modern hiring needs.

Kofax is a well-known supplier of clever automation answers for organizations across various enterprises. While there are a few different merchants in the market that offer comparative arrangements, Kofax hangs out in numerous ways. UiPath is one of the main players in the mechanical cycle automation market. While both Kofax and UiPath offer comparative arrangements, Kofax is known for its further developed capacities in archive automation, process coordination, and mental catch. Kofax likewise has a more grounded presence in specific businesses, like medical care and protection.

Salesforce, the world's largest provider of cloud-based customer relationship management (CRM) services, uses its AI platform Einstein to analyze trends and provide data-driven predictions. UiPath's robotic process automation (RPA) platform automates repetitive office tasks -- such as managing inventories, processing invoices, onboarding customers, and entering large amounts of data -- to reduce an organization's dependence on human employees. But over the past 12 months, Salesforce's stock declined 14% as UiPath's stock plunged 53%. Let's see why both stocks lost their luster, and if either one is a good turnaround play for 2023 and beyond. Salesforce expects its revenue to rise 17% in fiscal 2023, cooling from its 25% growth in fiscal 2022, as its adjusted EPS rises 3%. Its growth is decelerating as the macro headwinds force many companies to rein in their spending on big software deals.

The viral awareness and adoption of artificial intelligence foundation models such as OpenAI LP's ChatGPT have created both an opportunity and threat to automation platforms generally and robotic process automation point tools specifically. On the one hand, large language models can reduce complexity and accelerate the adoption of enterprise automation platforms. The flip side is that software robots are designed to improve human productivity through intelligent automation and GPT models could cannibalize some, if not many, use cases initially targeted by RPA vendors. This reality is causing customers to rethink their automation strategies and vendors to evolve their messaging rapidly to position foundation models as an accelerant to their platforms. In this Breaking Analysis, we provide you with a perspective on how foundation models could have an impact on automation platforms. We review Enterprise Technology Research data that quantifies the ascendency of OpenAI.

Given the rapid growth that robotic process automation leader UiPath Inc. has shown over the last few years, it's no wonder that the small robotics process automation pond isn't enough for the company to swim in. Instead, it wants to be the big fish in the expanding enterprise automation lake. I covered last year's Forward IV conference, where UiPath cemented its leadership position in RPA, while looking to expand into the platform-centric enterprise automation space. At that time, its vision was ahead of its product execution in a clear example of growing pains for the recently public company. In spite of UiPath's slowing growth (a common phenomenon as companies mature), this year's Forward 5 conference doubled in size from last year's pandemic-constrained Forward IV – and the increased excitement among customers, partners and UiPath employees was palpable.

Executives across industries are turning to automation to deliver on cost optimization and enhanced productivity objectives, Saikat Ray, VP analyst at Gartner, told CIO Dive in August. The robotic process automation software market will reach $2.9 billion by the end of 2022, up 19.5% from 2021, according to Gartner. In recent years, large UiPath bank customers have been using automation tools to facilitate initiatives that include data extraction and data transfer efforts to support the merger of BB&T and SunTrust; reduction of manual work for Wells Fargo contact center agents through digital personal assistants; and the delegation of some structured, rule-based repetitive tasks to bots at JPMorgan Chase. From JPMorgan Chase's perspective, one of the next steps on its automation journey will include using bots to tackle more sophisticated tasks, including delving into unstructured processes and unstructured data, and using machine learning to facilitate these efforts, said Shefali Shah, managing director of global digital transformation and integrated intelligent automation at JPMorgan Chase. Diana Caplinger, executive vice president and head of enterprise enablement and intelligent automation at Truist, said the company is deploying automation in support of "integrated relationship management," an effort to use data across the organization to deliver more personalized service to clients.

We are looking for an RPA Developer to join our team. The right person will be wanting to work within an intelligent, motivated, self-driven team with positive attitude, good communication skills and an effective problem-solving approach. You would also be very conscious of the importance of sharing knowledge and building other team members in the process. Objective: Design, develop, test automation workflows. Job Responsibilities: • Implement & develop RPA (UiPath) solutions in accordance with standard UiPath design principles and conventions using the best practices.

Robotic process automation (RPA) has been well received and is making a significant difference to business processes across organisations. At its next level, RPA is being enhanced by artificial intelligence (AI) to transform business smartly. This is according to speakers at a roundtable hosted by UiPath in Cape Town, where executives discussed AI, automation the future of work. Michael Law, country manager at UiPath, told delegates: "RPA alone was last year. It has transformed areas such as finance and HR. UiPath is now bringing AI and automation together across the organisation."

The Morning Download delivers daily insights and news on business technology from the CIO Journal team. "Once you analyze communications data, you want to automate around it," said Ted Kummert, UiPath's executive vice president of products and engineering. That can include creating apps that can respond to customers' email queries, rout them to the right corporate division, troubleshoot issues with accounts, or fine-tune orders, billing and deliveries--all without a customer-service worker stepping in. "Businesses still don't have visibility into what people are communicating about, and how to understand that and act on it fast," Mr. Kummert said. Beyond call centers and customer-service departments, he said, Re:infer's natural language processing tools can also be applied to day-to-day communications between internal business units, automating the task of tracking, cataloging and organizing information in real time.

The tech giants dominate the market and companies such as Apple, Alphabet and Amazon are a ubiquitous part of our daily lives. All are tech pioneers and Artificial Intelligence (AI) is widely used by all – from the iPhone's FaceID and Google's search algorithms on to Amazon's cloud computing solutions which are used by millions across the globe. In fact, you might not notice it, but AI is all around us these days – used in smart homes and cities, online shopping, cars, drones, and healthcare, amongst others. But it is far more than just a tool for the mega-caps. There are many smaller companies making use of the technology; this in turn opens up opportunities for investors willing to dig deeper into the world of machine learning so to find the names poised to make a splash in the space.