A great experience isn’t just about quality products and services or fast response rates. Users today expect all of that and more. They want easy, on-demand access to information and services from any device at any time. And they expect transitions across devices, locations, and processes to be seamless.
In 2023, AI is everywhere, and not a day goes by without someone developing a new way to use tools like ChatGPT. With the increasing hype about the promise of AI, it’s more important than ever to cut through the noise and focus on how AI can help you deliver real business value. Modern process automation platforms go above and beyond the capabilities of AI alone.
Your teams need constant connectivity to your organization's data and systems to operate effectively and thrive. And with digital transformation spurring a more rapid pace of innovation and technology adoption, this need for connected, democratized data is on the rise. That makes data silos an enemy you can no longer tolerate. Data fabric is the modern answer for eliminating data silos. Data silos occur when data is stored in separate systems or departments without proper integration.
April showers bring May feature releases to the Appian Platform. Get ready for sunny skies ahead with some seriously great new updates to Appian in 23.2. View documentation, release notes, discussion board posts, and tutorials on Community. The AI buzz is everywhere. If you’ve been getting bombarded with requests to “use more AI,” we’ve got you covered.
Artificial intelligence (AI) and automation stand at the vanguard of the future of work. While it’s impossible to predict with certainty how things will change, a few current trends and stats provide a good sense of where the future of AI and automation will take us. As evidenced by the recent interest in generative AI, companies want to experiment with how to reap deep benefits from automation technology.
What can data fabric do for your organization and how does it differ from other data management approaches? This primer will get you up to speed on data fabric essentials and help you explain the basics of this top tech trend. What is a data fabric? A data fabric connects data sets across disparate software systems, whether they’re on-premises or in the cloud, and creates a complete view. It’s both a tool set and an unified architecture layer (also called a virtualized data layer).
Artificial intelligence (AI) is the revolutionary technology that powers assistants like Siri and Alexa, self-driving cars, and personalized recommendations on shopping websites. And it’s safe to say that the AI revolution is continuing to gain momentum across industries and the public sector. AI can be particularly transformative in government procurement, streamlining the acquisition process to save time and money.
Using data to make decisions is actually really hard. Yet nearly every tech company, business, and team touts “data-driven” as the de-facto way that they operate. In practice, this intention to be data-led is often just aspirational—only about a quarter of organizations report that they are actually data-driven, according to Harvard Business Review. It’s easy to see why organizations strive to more effectively use their data.
Artificial intelligence (AI) has captured the collective imagination. Most news stories focus on the impact AI will have on the future and the productivity growth we might see. Yet, the rank-and-file at most companies know the challenges of truly integrating AI into their workstreams. Organizations need results now. Solving real business challenges requires combining the power of AI with human workers in a seamless workflow.
Think you’re ready to start an automation initiative at your organization? Be careful how you choose to proceed. According to an Ernst and Young study, between 30% and 50% of all robotic process automation (RPA) projects end in failure. Yikes. Are those odds you can afford to gamble on?
As automation capabilities grow, so do the related use cases. It’s not surprising that 80% of executives think automation can be applied to any business decision, according to a Gartner survey. But as implementation becomes easier and automation adoption more prevalent, your organization can quickly lose control, with too many automation projects happening in silos.
Processes are the foundation of your organization. They lay the groundwork for how your business operates, from product development and customer service to procurement and financial operations—and everything in between. Even work that isn’t formally defined in a process is likely a part of one. If you’ve ever tried to map or document a business process, you’ve probably learned that there’s no straightforward way to get it done.
Compliance is a core tenet of financial services organizations’ day-to-day operations. And the stakes are high, as regulatory fines are steep and climbing. Know Your Customer (KYC) compliance is just a piece of the overall compliance puzzle—but it’s an important piece. In 2022, global fines for failing to prevent money laundering and other financial crime surged more than 50% according to the Financial Times.
Hyperautomation refers to the use of multiple advanced automation technologies such as artificial intelligence (AI), robotic process automation (RPA), machine learning (ML), low-code, and business process management tools to accomplish end-to-end process automation. Rather than automating a single task, hyperautomation lets you automate multiple tasks within a wider process (and pass work easily between humans and digital workers).
Organizations looking to improve their bottom lines have embraced automation for decades. Simple automation has long been bringing benefits to businesses and public sector organizations alike, despite being limited to supporting small tasks and workflows.
Developing a procurement strategy and planning procurement activities requires many steps, such as aligning procurement goals with overall organizational objectives, conducting market research, identifying sourcing opportunities, and developing procurement plans. Procurement challenges may multiply depending on your industry. For example, if you’re in a federal agency, procurement and the entire acquisition planning process must adhere to strict regulatory demands.
How do you know when a process needs help? Is it slow, bloated, or, worst of all, truly broken? It’s a crucial question for all leaders and teams pursuing speed and growth, to meet digital transformation goals like faster customer onboarding or faster time to market. Often, even seemingly simple business processes are more complex than we realize. Teams and individuals may develop clever workarounds to get past large and small process problems.
There’s a lot of hype about hyperautomation. But it’s clear that as new automation technologies emerge, organizations that take a strategic, holistic approach to embedding them into business processes will come out ahead. So, what exactly is hyperautomation? It’s an approach to process automation that uses a combination of technologies to optimize complex business processes and augment human capabilities.
Insurers have been slammed by inflation, with loss costs surging by $30 billion in 2021 alone. Almost every line of insurance has been hit with rising claims expenses, while replacement costs have risen by 16.3%—nearly twice the consumer price index rise. To combat inflation, insurers need to find better ways to increase efficiency and reduce claims leakage. In addition to economic pressures, insurers are also facing rising customer expectations for a faster and more transparent claims process.
