AI Is Looking to ECM To Step Up to the Plate

Apr 25, 2018


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Article ImageComputers are running more and more of our daily lives – and producing gargantuan amounts of data in the process. By 2020, the worldwide volume of data will increase tenfold, leaping from the current 4.4 zettabytes to a staggering 44 zettabytes. We may find this level of data overwhelming, but this tsunami of data is exactly what is necessary to feed the extraordinary appetite of Artificial Intelligence (AI).

Information is the very foundation of AI. When we use AI, we learn from information and use this knowledge to make automated decisions about concrete outcomes. We basically teach AI systems to analyze data and give them algorithms to solve problems. But, to achieve this we need to create a solid groundwork of information to fuel AI.

In contrast to us humans, AI needs large data volumes to learn effectively. Again, different from us, AI is comfortable with handling colossal amounts of data. This makes AI extremely useful when the best solution or the best possible decision needs to be made on an enormous amount of data and a high number of options. For this reason AI has already made important advances, for example, in the area of complex challenges such as language control and processing.

For AI to deliver on results it needs large amounts of clean data. Accurate, verified data is imperative for AI to do its job. AI projects break down for one simple reason. The data has not been filtered properly and isn’t pure enough. In addition, this data needs to be consistently and properly managed to harvest its real value. As AI and deep learning start to grow and establish themselves it is obvious to me that Enterprise Content Management (ECM) has a big role to play in managing content to provide the data nourishment AI demands.

What is required is a context-sensitive solution that can efficiently manage and store large amounts of data and, if required, scale it horizontally. ECM more than fits the bill.

Accelerated Digitization

Despite digitization being one of the latest buzz words, it isn’t as far advanced in enterprises as we would like to think. Digitization is imperative for the advancement of AI. C-level executives are debating digitization, but are they actually putting any of this thinking into practice? The big question is can and do we really want to alter information management and the business models and processes that go with it to adopt AI?

Many enterprises have become complacent, resting on their success – but they may find themselves left at the digital starting gate if they don’t take action. Digital transformation is disrupting industries and moving fast – far faster than many expected.

True AI will take some time to develop, so enterprises should be looking at forging ahead with digitization to get ahead of the curve. Without a deep learning storehouse, AI applications will not have the data they need to satisfy their hunger. This is one of the key reasons that ECM needs to be part of every enterprise’s IT strategy moving forward. ECM systems are hugely practical, they just need to be deployed properly.

All AI technologies of deep content analytics (deep CA), ontology, and natural language processing (NLP) are covered by cognitive services and easily accessible by ECM applications. In addition, there is the potential for innovation – integrating these into statistical and semantic modeling, for example.

Data Management is Pivotal

Information logistics is set to become one of the most important influencing factors in value creation. Information logistics deals with the flow of information through an organization. It routes the right data to the right person in an agreed way, and importantly, at an agreed cost. If you already appreciate how valuable your data is and store it in an ECM you are several steps ahead in the game.

Enterprises around the globe are having to deal with the burgeoning problem of data. Managing data and making it available for collaboration across enterprises is complex. In addition to SAP, enterprises are finding data stored in separate databases, which has created silos that are isolated from the rest of the organization. These silos have already dented productivity. The integration of these silos is critical for AI to work efficiently as an accurate tool in decision making.

The way we interact with machines is also going through a transformation. The possibilities for natural language in ECM processing, for example, are vast. A major part of ECM’s role is to provide useful business insights from the data being managed that can be used in areas such as informed decision making. AI will help achieve something new and different. ECM, for example, will provide both inbound and outbound communication. In the future, ECMs will link into VR systems, allowing maintenance engineers to familiarize themselves with buildings remotely before repairs are made. We will be sending data directly from wearable technology to ECM repositories where it will be retrieved via voice commands. The possibilities are endless.

Star Gazing

AI will be a core element in modeling our societies and economies in the future. Helping us cope with large-scale challenges such as creating safer, smarter cities. It will also be a deciding factor in demographic development and in areas such as health research.

Artificial intelligence has great potential in industry. It not only relieves workers from having to do repetitive or even dangerous tasks, it is also much faster in analyzing data volumes, making decision making faster and more accurate.

When it comes to distinguishing patterns in texts, images, handwriting, materials, and substances, AI is more advanced than humans. AI can first evaluate radiological images before the radiologist makes a final diagnosis, for example.

There is little doubt that AI will have a huge and disruptive impact on organizations in the coming years. Content management is about to undergo a major sift as a result. Enterprises will need to get their data houses in order to tap into the enormous potential that AI offers. Change is never easy, but if they don’t make the leap of faith now they will be devoured by disruptive companies looking for easy prey when it comes to market share.


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