Cookiebot-Enabled: Enhance Your Website Traffic and Conversions

Cookiebot-Enabled: Enhance Your Website Traffic and Conversions

Brian Lv13

Cookiebot-Enabled: Enhance Your Website Traffic and Conversions

Back to The Intelligent Enterprise

Digital Employees the Key to Your Organization’s Digital Transformation

by David Yang, Founder and Chairman of the Board, ABBYY

There is a great opportunity to augment software developers, sales consultants, healthcare providers and payers, the legal industry, finance and accounting, and even the transportation industry with digital workers. The underlying benefit LLMs provide human workers in these fields is automating access to information faster and more accurately.

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The Wall Street Journal recently reported that 36 percent of emerging technology job posts during September were associated with artificial intelligence (AI). The research indicated that many companies are upskilling their staff with AI skills, while Goldman Sachs predicts 300 million jobs will be completed by AI. We are experiencing a new moment in our life history where human workers can work alongside digital workers. The accelerant? Large language models (LLMs).

Large language models are used in generative AI applications like ChatGPT, which famously became the latest tech hype when GPT4 was released March 14, 2023. It impressively understood and generated human-like text by analyzing patterns in large datasets, enabling it to perform a wide range of tasks, including natural language understanding, translation, and content creation.

In fact, GPT4 was able to pass a simulated version of the Uniform Bar Examination with a score in the top ten percent of test takers. A few months later, with billions more datasets available for analysis, it could reason like a human, not just summarize information. In an example where it could understand humor, GPT4 was asked what is funny about an image and to describe it panel by panel.

It was able to read the images, interpret the meanings, and reason the absurdity of the size of the charging cable connecting to the smartphone. As generative AI advances faster than Moore’s Law, it will continue to gain more abilities, such as multimodal and interdisciplinary composition, integrative ability, vision, real-world scenarios, interaction with the world, understanding of emotions and intentions, and process inconsistent explanations, to name a few.

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LLMs and digital employees

Digital employees, also referred to as digital workers, non-human workers, or intelligent agents, are software-driven entities capable of autonomously performing end-to-end knowledge-based processes using a diverse set of skills. The specific tasks and responsibilities of digital employees vary based on their job role, industry, and the objectives set by the manager or employer.

Digital workers are not to be confused by robotic process automation (RPA) bots. The significant difference being that RPA bots cannot read and understand unstructured data, which comprises 90% of enterprise data, and are designed for a specific, structured task. Digital workers, powered by LLMs via intelligent document processing solutions, augment human roles by undertaking entire business functions and can independently manage tasks like processing invoices and proactively answering queries without being pre-programmed. Typical digital employees can handle customer inquiries and utilize corporate knowledge bases, training materials, and corporate information systems, such as help desk, CRM, and ERP tools, vital for their duties. They can also undertake intellectual tasks such as data analysis and problem-solving and adhere to company policies and procedures including privacy policy and confidentiality.

More advanced digital employees will be able to collaborate with team members to achieve collective goals, engage in training and development, participate in meetings, and report to supervisors or managers, provide updates, seek feedback, and obtain guidance on tasks and projects.

There is a great opportunity to augment software developers, sales consultants, healthcare providers and payers, the legal industry, finance and accounting, and even the transportation industry with digital workers. The underlying benefit LLMs provide human workers in these fields is automating access to information faster and more accurately.

LLMs can be added to ERP, CRM, EHR, and BPM systems via low-code / no-code intelligent document processing (IDP) solutions to boost performance and business results. In the legal field, briefs, motions, and contracts can be reviewed and executed faster. In healthcare, providers can accelerate the approval for patients to see a specialist, and payers can automate many aspects of case management and the review of explanation of benefits to expedite payments.

Across all industries is the improved performance of accounts payable automation. From logistics to pharmaceuticals to financials services and everything in between, invoices and purchase orders are the heartbeat of a company’s revenue. Accounts payable (AP) clerks benefit from having critical data automatically available within ERP systems that enables them to elevate the type of work they perform. Most organizations that use AI-powered AP automation systems see a 400 percent increase in employee productivity, 91 lower lower invoice processing costs, and 81 percent faster invoice processing time—which means more revenue.

The time to train digital workers is also significantly faster. Rather than taking months to train a legal clerk or healthcare administrator, digital counterparts can be trained on relevant LLMs within two to six weeks.

But it’s not just in software where digital employees can contribute toward a more digital organization. We’ll also see it in autonomous vehicles.

Imagine a transportation company with 100 trucks, where 90 trucks are operated by human drivers while ten trucks are controlled by digital drivers that operate 24/7 non-stop without requiring any fuel but are limited to routine routes. The ten digital drivers can work alongside human drivers and could potentially spare humans from urgent, undesirable routes.


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Human workers welcome AI counterparts

The stigma of using AI among the workforce is lessening. In fact, human workers are embracing the performance enhancement results digital workers are offering. A recent global ABBYY survey, State of Intelligent Automation: Impact of the Economy on AI Priorities , found that 60 percent of IT leaders implementing AI attributed an increase in higher value work; 62 percent reported employees are happier; and 59 percent said employees are more innovative. Furthermore, nearly half have had an increase in staff retention levels since introducing AI in automation.

To further the dialogue of the impact of digital workers with human workers, leaders are invited to join the International Digital Workers Association. The goal of the association is to unite efforts in maximizing the economic benefit and to develop industry API standards. The association will also spearhead industry standards for information security, privacy, and confidentiality, and define ethical norms. Visit https://www.digitalworker.pro/association to learn more.

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David Yang

Founder and Chairman of the Board, ABBYY

David Yang, Ph.D., is a physicist by training and a Silicon Valley-based entrepreneur with a focus on AI. He is the founder of ABBYY and is a Board of Director, and the co-founder of Newo.ai , the creator of the drag-n-drop builder of the Non-Human Workers, Digital Employees. Yang is a TEDx speaker Will robots ever become part of the human family , a member of Band of Angels, founded 12 companies, and holds numerous patents and scientific publications. The World Economic Forum in Davos named him one of the top 100 World Technology Pioneers.

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  • Title: Cookiebot-Enabled: Enhance Your Website Traffic and Conversions
  • Author: Brian
  • Created at : 2024-08-21 15:30:22
  • Updated at : 2024-08-22 15:30:22
  • Link: https://tech-savvy.techidaily.com/cookiebot-enabled-enhance-your-website-traffic-and-conversions/
  • License: This work is licensed under CC BY-NC-SA 4.0.