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Unlocking business efficiency: The power of generative AI

Generative artificial intelligence (GenAI) seems here to stay. Since OpenAI’s explosive launch of ChatGPT in November 2022, it has captured the imaginations of people and organizations around the globe with its capabilities. With its ability to create, design and optimize processes autonomously, GenAI holds immense potential for revolutionizing business process solutions and enhancing efficiency across various industries. But not all AI is the same. In this blog, we’ll explore what GenAI is, how it has evolved since it first captivated the world in 2022, and ways Conduent is utilizing GenAI as part of our long history of AI deployment in our solutions.

Business process use cases for AI  

At Conduent, AI has been a key component of our business process solutions, in many forms, since the mid-2000s. It plays a crucial role in driving digital transformation and adding value for our clients and their end users.

For example:
Conduent CXNow, our cloud-based customer contact solution, leverages AI to enable features such as virtual assistants or bots to handle calls and chat conversations. CXNow is sophisticated enough that it can analyze speech and voice inflections to determine the sentiment of a conversation and then apply predictive engagement for improving outreach.

For document processing, such as our Digital Mailroom Services and Intelligent Process Automation (IPA), we leverage AI to ingest, classify, extract and visualize data, while enhancing workflows, security, compliance and employee productivity –– reducing manual efforts and boosting the efficiency of day-to-day operations.

But these are examples of traditional AI, so what’s the difference?

What is GenAI and how is it different than traditional AI?

AI is a tool that can be "taught" using training datasets to perform tasks (no human input required). In turn, AI helps organizations automate processes, gain insights from data and enhance customer experiences. GenAI is a subset of AI that focuses on generating new content, designs or solutions autonomously.

Here’s a high-level breakdown of the differences:

Said simply, GenAI doesn’t require human-generated datasets to function. Unlike traditional AI, GenAI leverages techniques such as neural networks and deep learning to create new content, such as images, music, videos, text and code. This is different from traditional AI, which typically focuses on understanding and interpreting dat but rarely on creating new content.

For instance, a generative model trained on a dataset of classical music can create entirely new symphonies in the same style. With the capability to handle high-dimensional data, understand intricate patterns and produce outputs that go beyond mere pattern recognition or prediction, GenAI can be a potent tool for content creation and problem solving that is virtually indistinguishable from human-made creations.

Driving innovation in business processes

GenAI offers several key benefits for businesses looking to optimize their processes:

Optimized workflows: By analyzing vast amounts of data and simulating different scenarios, GenAI can help businesses identify bottlenecks, inefficiencies and other areas for improvement within their workflows. This enables organizations to optimize processes, allocate resources more effectively and reduce operational costs.

Personalized solutions: GenAI has the power to personalize solutions based on individual preferences, behaviors and needs. Whether it's tailoring product recommendations for customers or optimizing supply chain logistics, GenAI can deliver personalized experiences that drive customer satisfaction and loyalty.

Rapid prototyping: In industries such as manufacturing and product design, GenAI can accelerate the prototyping process by generating multiple design iterations in a fraction of the time it would take using traditional methods. This approach enables businesses to iterate quickly, test ideas more effectively and bring products to market faster.

Continuous learning: GenAI systems are capable of learning and evolving over time. By analyzing feedback and performance data, these systems can continuously refine their models and improve their outputs, leading to ongoing enhancements in business processes and efficiency.

How has GenAI evolved since 2022?

In short, as GenAI continues to ingest data and inputs from people, it continues to learn and become more human-like in its outputs. Large language models (LLMs) help train GenAI platforms on large amounts of text and enable them to perform complex tasks. In 2023, OpenAI launched GPT-4, which is reportedly even more accurate with advanced reasoning capabilities. A big difference here is that previous iterations like GPT-3.5, are only trained on content up to 2021. GPT-4 is trained on data up to December 2023 and can also browse the Internet. Another big difference is the number of parameters each iteration is being trained. For reference, GPT-3 has 175 billion parameters. GPT-4 has 1.76 trillion parameters. Most recently, in May of this year, OpenAI surprised the world by rolling out GPT-4o, also called "Omni." This version is planned to be able to hold an actual real-time conversation with you. One example showed GPT-4o offering fashion tips for someone's outfit by viewing them through the person's smartphone camera. Meanwhile, other organizations are building their own closed GenAI platforms, each with varying degrees of functionality and sophistication.

Conduent’s approach to GenAI 

Conduent is now strategically positioned as a leader in leveraging GenAI to drive innovation and enhance its offerings across various industries. Our recent collaboration with Microsoft, using Microsoft Azure OpenAI Service, underscores our commitment to integrating cutting-edge technologies to benefit our diverse clientele, including Fortune 100 companies and government agencies.  

By piloting applications in healthcare claims management, customer service platforms and fraud detection, we’re taking a proactive approach to addressing critical business challenges and improving operational efficiency. Through this initiative, we aim to not only enhance client operating and cost performance, but also prioritize customer experience and optimize business processes. Our GenAI solutions offer three distinct benefits for business processes:

  1. Improved quality by reducing error rates in standardized workflows
  2. Increased productivity through enhanced throughput of transactions
  3. Faster cycle times achieved by streamlining value chain processes

Here are just a few examples of our upcoming GenAI pilot programs:

Document management 

Conduent can enable intelligent data harvesting from healthcare claims documents for faster adjudication by implementing Azure AI Document Intelligence and Azure OpenAI Service. This has the potential to reduce data extraction errors from unstructured documents through contextualized image-to-text conversion and data processing. GenAI is also helpful at quickly interpreting, analyzing and summarizing information. 

Fraud management for payments

Fraud analysis in payments involves time-consuming analysis across multiple structured and unstructured data sets. Leveraging improved data contextualization and summarization capabilities through GenAI, the volume and speed of fraud detection processing for payments can be greatly enhanced. GenAI can perform pattern analysis across large sets of structured and unstructured information in real time. Conduent can analyze more cards, which leads to higher productivity, while the real-time analysis reduces fraud. 

Contact center operations 

Agent responsiveness can be increased with Azure AI Language Service, Azure AI Speech Service, and Azure OpenAI Service. These advanced AI solutions enable the creation of virtual agents to handle rising call volumes, while agent assist aids contact center representatives in addressing customer queries more efficiently. Leveraging GenAI expedites the deployment of virtual agents and agent assist, as it can self-train using historical call recordings or CRM logs. This results in faster cycle times and heightened agent productivity, ultimately benefiting the contact center operations. 

GenAI is not simply about cost reduction or human replacement, but about creating outcomes focused on experience, value and performance. GenAI presents us with an opportunity to further push the boundaries of innovation, applying the lessons learned from years of AI deployment to expand our solutions to drive more value for our clients. By harnessing the power of automated creativity, personalized solutions and continuous learning, organizations can unlock new levels of innovation and competitiveness. As GenAI continues to evolve and mature, its impact on business processes is poised to grow exponentially, driving greater efficiency, agility and value creation across industries. Embracing GenAI is not just about adopting a new technology — it's about reimagining what's possible and transforming the way we work. Learn more by visiting: