While Artificial Intelligence (AI) has the potential to be a very powerful tool in information management, the topic is so wrapped up in hyperbole and confusion that it can be challenging to cut through all the noise, causing many to fear the complexity of AI.
The venerable template allows structured form data to be accurately extracted. In the document capture industry, the concept of templates where you specify the location of each data element is a tried-and-true strategy for structured forms. If the form is standardized, giving the software the precise place to look for data will almost always result in better performance over alternatives such as rules-based approaches using keywords or patterns. Even with unstructured data such as on invoices, we find that many organizations have opted for a template approach after finding that more flexible, rules-based approaches fall short. The result is a tremendous amount of upfront effort and a lot of maintenance.
Making an ECM implementation successful requires planning and attention to detail. The best way to create the right solution is to identify organizational goals and priorities. Learn how to manage a successful implementation in our free guide.
These days it feels almost impossible to have a conversation with anyone involved in the world of Information Management without bringing up machine learning and artificial intelligence. Everyone is talking about it; everyone has an opinion; everyone claims to be doing it— or at least thinking about doing it. AI is part of the popular zeitgeist, entering our lives in the form of autonomous vehicles on our roads, Alexa in our homes, and a burgeoning AI arms race between rival world powers. Yet despite all the talk, no one really seems to agree on what its real impact will be. In fact, everyone seems to have a different definition of what ‘it’ even is. There are those telling us it’s nothing new, and its potential is over-hyped, while others tell us that AI and Machine Learning will make us all redundant.
Artificial intelligence is changing the way we do everything. As we look ahead, self-driving cars, hyper-intelligent predictive software, and self-improving robots seem possible.
Minimizing data breaches and privacy compliance are now top strategic and operational priorities for organizations given increasingly onerous data privacy regulatory requirements.
AIIM’s resident Podcaster Extraordinaire, Kevin Craine, recently sat down with Andrea Chiappe, Director of Innovation and Strategy at Systemware, to discuss opportunities in the convergence of analytics, cognitive computing, and machine learning. The following is a short synopsis of the interview. You can find the full podcast interview here.