Business productivity has faltered over the last decade, but the rise of generative AI (Gen AI) promises to reverse the trend and potentially contribute trillions of dollars to the US economy by 2030. With 70% of CIOs recognizing Gen AI’s game-changing potential to boost productivity and over half planning to deploy it by 2025, anticipation for Gen AI’s impact is high.
Nonetheless, many enterprises face an epic challenge bridging the gap between anticipation and implementation. Shifting regulatory requirements, an aging workforce, and barriers to tech adoption hinder business productivity and growth. This blog explores five generative AI use cases to help enterprise IT leaders overcome these challenges and supercharge productivity.
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1. Accelerate the claims process from beginning to end
In today's competitive insurance industry, optimizing property and casualty claims is a must for insurers seeking to meet ever-rising customer expectations while managing costs. For example, Appian Connected Claims uses automation and AI to streamline traditionally labor-intensive and error-prone manual claims processes.
This cutting-edge solution accelerates claims processing and ensures superior accuracy and efficiency while ultimately delivering a seamless claims experience to policyholders.
Gen AI further enhances the claims process by analyzing claims data in real time, identifying potential fraud, and reducing the risk of claims leakage. Additionally, Gen AI can analyze historical claims data and identify patterns to expedite claims processing and decision-making.
Example: Through an AI-powered approach to claims management, Global Excel Management selected Appian’s Connected Claims Solution to expedite claim settlements, reduce costs, and enhance the customer experience. Using Appian's adaptable workflows, Global Excel successfully implemented a claims portal and First Notice of Loss (FNOL) intake process in less than 12 weeks. Connected Claims also allows business users to configure workflows without IT intervention, expediting the onboarding process for new institutions and policies.
Built on the Appian Platform, Connected Claims tracks claims as they move through every stage of the life cycle.
Now that we’ve examined how Gen AI expedites insurance claims processing, let's delve into another powerful Gen AI application: boosting employee productivity through internal chatbots.
2. Boost employee productivity
Another effective generative AI use case involves building internal chatbots directly connected to your institutional knowledge base. Employees can query these bots for immediate, precise answers. This saves valuable time and enhances productivity by granting employees instant access to the information they need. By seamlessly integrating Gen AI into your internal communication systems, you can foster a culture of efficiency and empowerment, where knowledge is readily available at the click of a button. Moreover, with Gen AI's ability to continuously learn and evolve, these chatbots can adapt to user inquiries, ensuring consistently accurate and relevant responses over time.
Example: The Texas Department of Public Safety implemented an AI-powered chatbot application that allows employees to mine proprietary documents in a centralized system where information is viewable by more than 10,000 stakeholders. As a result, agency employees can immediately get answers to questions that the agency director used to have to field. Additionally, the new system’s faster turnaround time allows the state’s Office of Procurement and Contract Services (OPCS) to ensure the integrity of the underlying contract data.
Now that we've explored how Gen AI accelerates insurance claims processing, let's pivot to another vital application: harnessing Gen AI to turn unstructured data into actionable insights.
3. Convert unstructured data into actionable insights
In today’s digital economy, organizations need a way to automatically classify, process, and extract information from unstructured data, like paper documents, videos, and emails, and make that information actionable in real time. Intelligent document automation converts this unstructured data into actionable insights, using AI and ML capabilities enhanced by humans as needed.
Complementing these tools, Gen AI can summarize key facts and action items from documents based on predefined settings, allowing you to extract the information you need from large volumes of documents much more quickly.
Example: A government agency used generative AI to process critical identity document applications. This information used to take weeks to review because employees had to match job descriptions on the job applications to predefined job codes. However, by using a generative AI plug-in, the agency was able to create an application to automate this matching process quickly.
The agency’s new AI-powered application takes the unstructured text of job descriptions and instantly recommends the top three codes for that job. Thanks to this AI-powered process, the agency has significantly reduced the time it takes to process applications, boosting productivity and enabling reviewers to focus on more critical tasks.
Having highlighted Gen AI's transformative potential in expediting insurance claims and elevating employee productivity, let's focus on how it revolutionizes customer service operations.
4. Streamline and personalize customer service operations
AI expedites the customer journey by supporting self-service, handling repetitive tasks, and prioritizing complex interactions that require empathy and personalization.
Conventional chatbots provide rules-based, generic responses. But AI-powered chatbots and virtual assistants use natural language processing to personalize recommendations and anticipate customer needs.
Example: Aviva France revolutionized its customer service operations by leveraging AI to streamline claims processing. Handling 80,000 inquiries annually, agents previously faced time-consuming manual processes and disjointed systems.
With the help of an AI-powered process automation platform, Aviva France digitized manual tasks and optimized cross-functional collaboration. The result? Same-day claims processing surged from 1% to 25%, while settlements skyrocketed by an impressive 530%, demonstrating the transformative power of AI to boost efficiency and speed in customer service operations.
[Learn about the differences between generative AI and large language models.]
With four compelling use cases already explored, it's time to spotlight another facet of Gen AI's capabilities: document extraction and classification. Let's examine how this transformative technology revolutionizes data management and analysis.
5. Turbocharge document extraction and classification processes
Gen AI offers remarkable potential for optimizing document extraction and classification. Now, let's delve deeper into these capabilities and explore real-world examples of how enterprises leverage Gen AI to drive efficiency and innovation in data management and analysis.
Email classification: Automatically Interprets and categorizes emails, streamlining communication while expediting responses to customer inquiries.
Document classification: Automatically identifies and organizes information within documents, expediting document routing and processing.
Data extraction: Automatically retrieves data from various document types, optimizing accuracy and boosting operational efficiency.
Example: Leroy Merlin had a problem. The prominent home improvement retailer faced significant challenges in expediting their return, refund, and exchange procedures. Manual approvals, coupled with fragmented oversight in fulfillment and data silos between systems, resulted in prolonged approval processes and frequent order cancellations, ultimately leading to a decline in customer satisfaction ratings. Moreover, inaccurate data contributed to financial losses.
By leveraging robotic process automation (RPA), Leroy Merlin automated refund payment transactions, seamlessly capturing data from various payment portals. However, integrating generative AI into their processes propelled the retailer’s operational efficiency to another level. For example, AI-powered document processing streamlined up to 90% of their manual processes, boosting customer satisfaction and propelling business growth.
[Go deeper into using gen AI. Check out these seven AI/ML use cases.]
Now, let's explore actionable tips and tactics for implementing Gen AI in your organization, drawing insights from real-world examples from successful organizations like Leroy Merlin.
Tips and tactics for implementing Gen AI in your organization
Process automation platforms are the perfect tool for implementing Gen AI use cases. The best of these platforms leverage the latest large language models to digitize tasks like document summarization and identifying PII (personally identifiable information). Additionally, these cutting-edge platforms use Gen AI to automate development tasks and expedite the development lifecycle.
Yet, many enterprises have only scratched the surface of Gen AI's enormous potential. To unlock the full potential of Gen AI and reap its benefits, effective implementation is a critical success factor. Here are some practical tips and tactics to help you harness the power of Gen AI in your organization successfully.
Workflow integration: Make sure AI is seamlessly integrated into your processes and set up to collaborate with human decision-makers.
Task automation: Streamline operations by automating manual tasks, such as searching for, matching, and summarizing data. This boosts efficiency and frees up human resources for more strategic work.
Data: Invest in a strong semantic layer over your enterprise data to ensure you can use it to train your algorithms and/or query it in real time to get fast answers to your questions. A data fabric is a great way to do this.
Security and privacy: Prioritize the security and privacy of your AI implementations. Take measures to protect sensitive information, particularly with a secure and trustworthy AI integration.
So, Gen AI's promise is vast, but harnessing its transformative potential requires careful integration into existing processes and systems.
Unlocking the value of Gen AI
Many companies are currently experimenting with Gen AI for content creation, software development, data extraction and analysis, and customer service. However, AI-centric organizations are truly making a difference, transforming strategic areas of their business with fewer resources and greater velocity. The rapid advancement of Gen AI is reshaping entire industries, from financial services and healthcare to government and supply chain management.
The crucial question is: How do you unlock the value of this truly transformational technology in your organization? As Piyush Kumar, Global Head – Strategy, Strategic Partnership & Solutions at Wipro, noted in a recent interview:
“It all boils down to the basics. You should have your data strategy dialed in. The best organizations take a top-down approach, where the C-level buys into the critical business value and differentiation AI can drive. This may be easier to achieve with the news hype and promise of generative AI. Picking the right use cases to showcase the value has always been key. Focus on early wins with low-hanging opportunities while you build and invest toward the bigger vision.”
[Download the 2024 AI Outlook and go deeper into operationalizing AI for maximum value.]
