#lowcodeautomation

Artificial intelligence (AI) has reached a tipping point in the public consciousness. Much of this has been driven by technology developments related to AI tools, including ChatGPT. However, for enterprises shaping forward-looking AI strategy, a critical part of the conversation that needs to be addressed is the issue of private AI vs public AI. It’s important to understand the data privacy and regulatory implications of each approach, especially for public organisations or private sector companies in heavily regulated industries. Let’s explore both approaches to better understand the potential impact of each...

The Appian Platform for process automation is your gateway to the productivity revolution with an architecture powered by AI. Discover the next-generation, AI-powered platform for process automation.

Right now, developers are doing the impossible - building applications in record time that truly transform industries, improve business processes, and unlock radical productivity. And they’re doing it with two tools: Generative artificial intelligence (AI) and low-code. Combining generative AI and low-code enables developers to build powerful applications at a whole new pace. This makes these employees more valuable and productive than ever, as well as reducing both time and costs in the development process.

There's no question that this year, we're seeing dramatic upheavals in the data and analytics space. AI, of course, is the subject du jour, but any discussion of AI and its potential must, by necessity, involve the data teams that provide the information that makes AI successful. Here are what industry leaders and experts see as the most important technologies shaping the growth of data-driven enterprises.

The French Ligue Nationale de Rugby (LNR) is using the Appian Platform to optimize game-day and tournament organizational processes. 50% reduction in game-day hotline calls, 24% reduction in legal workload from management and compliance app delivered in less than five months.

Case management is a specific type of knowledge work in which processes are less structured, interactions are more ad hoc, and events and milestones are difficult to predict. It is often a core operational element of an organization. Getting the building blocks of case management right is critical to helping organizations deliver a continuum of products and services to customers, stakeholders, and constituents.

2023 is looking likely to be a breakout year for artificial intelligence (AI) and machine learning (ML). Some industry-watchers predict that recent breakthroughs in AI might lead to a new revolution in society akin to the industrial revolution, the invention of the internet, or the advent of the smartphone. A wide variety of Industries have been using AI for decades, which brings up the question: What are some common AI/ML use cases? What use cases should business and IT leaders track, as they shape a holistic process automation strategy?

Appian is now branding itself as the “End to End Process Platform”. This branding reflects their use of new AI/ML/Large Language Model technologies with RPA (robotic process automation) and process mining to solve complex business process challenges quicker than ever.

How can you find time to drive efficiency across your organization when there is so much digital work to be done? This is one area where hyperautomation and digital transformation initiatives intersect. Let’s demystify some of the gray areas surrounding what hyperautomation technologies and tools can help you accomplish as you shape automation strategy and select tools.

Appian has rolled out Appian Protect, a new set of security offerings providing data monitoring and end-to-end encryption for cloud and mobile applications. Appian Protect gives Appian customers more control over their security posture, with top-tier encryption capabilities, 24x7x365 monitoring, defense-in-depth data protection and a host of compliance accreditations.