Computers continue to control vast swathes of our lives – and the trend shows no sign of abating. One day we may work alongside robots, but for the moment we need to nurture AI to reach its potential. This is why it is imperative enterprises get their data in order first to feed AI’s enormous appetite to tap into valuable benefits.
Artificial Intelligence (AI) is becoming more and more sophisticated, capable of complex decision making and understanding complex nuances in our world – but it will be some time before machines become our equals – or surpass us.
For AI to deliver it needs quality clean data – and lots of it. Having accurate, verified data is essential for AI to work. AI projects fail because the data isn’t good enough. But this data also needs to be properly managed to gain value from it. As AI and deep learning evolve it makes absolute sense that ECM should play a relevant role in this new approach to content management.
Digitalization is key
The companies that harvest the benefits of AI first, will be those that are happy to accept change. But digitalization will be key. Digitization may be a topic on the CTO’s agenda, but are they actually practicing it? Can and do they want to change their information management strategies, business models and processes to adopt AI? Many are playing a dangerous waiting game.
True AI isn’t fully developed yet, but that doesn’t mean you shouldn’t push ahead with digitization. This means getting your data in order. Without a deep learning repository, AI applications will be starved of the data they need to run. This is why Enterprise Content Management (ECM) systems still need to part of companies’ ongoing IT strategies. All AI technologies of deep content analytics (deep CA), ontology, and natural language processing (NLP) are covered in cognitive services and accessible via ECM applications. There is also the potential to integrate into statistical and semantic modeling, for example.
Data is crucial
Information is the diet of AI. And it won’t be short of food. Thanks to technologies such as Industry 4.0 and the Internet of Things (IoT), we are producing more and more data. By 2020, it is estimated the global volume of data will increase tenfold, leaping from 4.4 zettabytes to a staggering 44 zettabytes.
ERP systems like SAP are incapable of processing such enormous amounts of information. What is necessary is context-sensitive software that can manage and store large volumes of data and, if required, scale it horizontally. This has always been where ECM comes into its own.
Information logistics will becoming one of the key influencing factors in value creation. Information logistics makes sure the right information reaches the right person in the right way at an agreeable cost. If you already understand the value of data and store it in an ECM you will be pleased to hear you are one step ahead.
Of course information management is complex and challenging for many enterprises. In addition to SAP, other business applications are being used data stored in separate databases and structures creating silos. The integration of this silos is paramount. AI needs access to all this information if it is to become a valued and accurate tool in decision making.
At the same time the way we interact with machines is changing. The possibilities for natural language in ECM processing, for example, are extensive. Part of ECM’s promise is to provide useful business insights from the data being managed. AI will push these boundaries. ECM, for example, will provide inbound and outbound communication. We will be able to ask a computer questions about documents and they will find us. Wearables with sensors will process information about us and send it to medical insurers, for example, where it can be put in an ECM repository for voice retrieval. The possibilities are endless.
Thinking ahead
AI will be pivotal in shaping our societies and economies in the future. It will help us solve big societal problems such as developing smart, eco-friendly cities. It will enable humans to make breakthroughs in areas such as healthcare, transportation and education. It will also be a critical factor in demographic development.
AI is valuable when the best possible solution or decision must be made based on analyzing enormous amounts of data. AI has made important advances recently in the area of complex challenges such as language control and processing, for example.
The take away for CTOs is don’t be complacent. AI will have a huge impact on business within the next decade. The integration of data silos is critical moving forward. Just because you have been successful in the past it doesn’t mean you don’t need to change the recipe. Disruptive companies are the force behind digitalization and will fast eat your market share if you don’t start taking AI seriously.
