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.
