If you have a legacy system with customized capabilities and valuable features but nearing end of life, refactoring the system is a potential choice for modernization. Insurance platform modernization usually involves one-to-one code migration, which can often be more costly and time consuming than expected and typically tends to miss some of the integration and data architecture modernization that is foundational for getting the full value of digitization.

Today’s AI may be able to pass the Turing test, but I think we can all agree that doesn’t make it human. AI is a tool—a powerful one, but a tool nonetheless. And just like any tool, it can make our work easier, but it can’t do it for us.

What is hyperautomation for insurance? It might sound like just another buzzword, but let’s peel back the layers to see how hyperautomation works. Imagine this: you go on a deep dive to evaluate your insurance company’s processes and operational models. You discover inefficiencies, lag times, and that your team manages transactions with disparate, often manual processes. It’s clear you need a new solution. And the solution you need doesn’t currently exist.

With the explosion of artificial intelligence (AI), innovative companies are harnessing enterprise AI at scale for a variety of business use cases, including repetitive task automation, product and service development, supply chain management, customer service operations, decision-making systems, and more.

In many state and local government organizations, contract management is a manual process that is often cumbersome to oversee. Employees often feel overwhelmed trying to track deliverables and payments and ensure compliance. Manual contract management leads to delays and inefficiencies in procurement processes, resulting in missed opportunities to identify and acquire the right products or services at the best possible cost, which wastes taxpayer dollars.

Organizations are increasingly turning to business process management (BPM) to boost efficiency and meet aggressive business goals. BPM is a discipline and set of practices that enable organizations to optimize processes for greater efficiency, effectiveness, and business agility. Organizations buy commercial-off-the-shelf (COTS) BPM to facilitate this process. Data and software integration can be time- and resource-intensive with COTS BPM software.

In today's hyperconnected world, where negative reviews on social media can wreak havoc on a company’s reputation, delivering an exceptional customer experience isn't just a luxury—it's a business imperative. Companies are locked in a fierce battle for customers that is primarily based on their ability to deliver outstanding customer experiences (CX). According to research by The Conference Board, 65% of CEOs globally prioritize investing in strategies to improve CX.

Business process management solutions often tout their analysis and optimization capabilities, but few provide the full set of tools needed to build a process, measure its performance, and identify and implement improvements. And when you’re looking for information on how to optimize a process, it’s easy to quickly get lost in the information-overload about the best methodologies and tools. That’s likely because the answer to process improvement isn’t straightforward.

Intelligent automation happens when robotic process automation (RPA) meets artificial intelligence (AI), bringing simple actions and cognitive tasks together for lightning-fast processing. Intelligent automation in insurance is a powerful tool that reduces both human error and the need to perform repetitive tasks manually. Imagine AI extracting data from an invoice then a bot entering that data into a software program.

In the life sciences industry, where breakthroughs in research and healthcare are fueled by data, data silos can be a big problem. Data silos might be caused by things like legacy systems, departmental divisions, disparate data formats, or lack of interoperability standards. Data silos can manifest at any point in the product lifecycle and make it hard for the right people to access and use the information they need, when they need it.

Enterprises looking to increase productivity and optimize business processes are increasingly turning to artificial intelligence (AI). AI can meet these expectations—but only with the right enabling technology. Intelligent automation at scale across the organization can offer a strategic approach to incorporating AI into complex business processes.

The potential impact of AI in banking appears boundless. A 2023 McKinsey report found that effectively incorporating generative AI tools into business operations could lead to annual operational savings ranging from $200 billion to $340 billion for the global financial services industry. These cutting-edge technologies can also enhance customer satisfaction, attract more potential customers, and improve employee experience.

In just a few months, enterprise AI has rapidly evolved into a strategic partner for organizations that want to stay ahead of the disruption curve. Whether enterprises are leveraging predictive analytics for strategic decision-making, using machine learning algorithms for supply chain optimization, or applying generative AI and large language models to enhance customer service, it’s clear AI will help business in many ways.

The latest automation trends are paving the way for what Gartner defines as "hyperautomation"—the philosophy that everything that can and should be automated will eventually be automated. However, many businesses seeking to harness the latest automation technology don’t know where to start. This blog highlights five timely trends in automation that should be on your digital transformation roadmap in 2024.

Artificial intelligence (AI) can transform the way your enterprise does business—but if you can’t quickly implement AI in your business processes, you’ll just as quickly fall behind competitors. This is where low-code AI tools can help. Over the past decade, low-code platforms have enabled software engineers, professional developers, and employees with minimal coding experience to build new digital, automated solutions using drag-and-drop interfaces.

The business of governance is not easy. Public sector organizations face a range of obstacles from corruption to lack of transparency to red tape—obstacles that have the potential to erode public trust in institutions and hinder economic development. That’s probably why, in virtually every country around the world, popular culture lampoons the intricacies of government bureaucracy.

Insurers’ profitability (and survival) is being threatened by a myriad of challenges—rising policy lapses due to higher premiums, customer churn from tightening budgets, and skyrocketing customer expectations. Squeezed by these pressures, insurers must find ways to improve efficiencies in their core processes. But there is a way forward for insurers: Business process management (BPM), an approach to improving organizational processes that is designed to optimize work.

Over the past year, interest in artificial intelligence has surged due to the proliferation of generative AI and large language models. These tools captured imaginations, demonstrating a technology brimming with possibility. While many focused on the potential of these tools, some companies made AI practical. For example, last year, Appian released packaged AI tools for processing content at scale and quickly building interface forms.

Aligning HR practices with business objectives improves operational efficiency and enhances employee engagement. HR casework usually spans multiple disconnected departments and systems—exactly the kind of process end-to-end case management can help you connect. Some common use cases for HR case management include: Staying compliant with complex and evolving regulatory environments requires speed, flexibility, and a unified view of data and workflows that can be easily audited.

Before low-code, enterprise IT teams had to use either traditional development or commercial off-the-shelf software to provide business solutions. But when low-code development entered the scene, teams discovered they could create custom, enterprise-grade software applications up to 10x faster.

As business leaders cautiously navigate the uncertainties of 2024, marked by the mainstreaming of AI, heightened regulatory oversight, cost pressures, and supply chain disruptions, the need for agile and efficient business processes has never been more pressing. Amidst this backdrop of uncertainty, cloud BPM shines as a beacon of opportunity, offering organizations a transformative approach to streamline operations, drive innovation, and achieve better business outcomes.