In some cases, AI is already better than humans. In a lot of other cases, there is still a lot to learn. [shutterstock: 568431658, whiteMocca]

In some cases, AI is already better than humans. In a lot of other cases, there is still a lot to learn. [shutterstock: 568431658, whiteMocca]

The High Art Of Artificial Intelligence

Are we experiencing an unprecedented technological advance through artificial intelligence (AI)? There is a lot out there that suggests this! Still, it will take a long time for machines to truly become equal or superior to humans. Until scientists have developed super-intelligence (strong AI), we humans will continue to co-exist and work well with weak AI.

While strong AI can replace humans, weak AI is an extension of our cognitive skills and gives us already today great advantages in mastering specific challenges. AI will become a core component of the modernization of society and the economy. It will support us immensely in coping with global challenges – for example, in developing more intelligent cities and safer and congestion-free traffic, in lowering energy consumption and optimizing our power grids, in cutting down on carbon dioxide emissions, and in protecting the internet more effectively.

In light of the demographic development, boosting productivity through AI will become a competitive factor.

Stimulate intelligence

Weak AI and rule-based systems already offer us considerable benefits and potential. They manage financial transactions, make forecasts, and simulate weather and economic developments. AI detects anomalies, for example, in the form of credit card fraud. It is an excellent means of making diagnoses and prognoses in medicine. Particularly notable is that artificial intelligence can first evaluate radiological images before the radiologist makes a final diagnosis. When it comes to recognizing patterns in texts, images, handwriting, materials and substances, AI is more advanced than humans. It is crucial for predictive maintenance and repair.

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“When it comes to recognizing patterns in texts, images, handwriting, materials and substances, AI is more advanced than humans.”

Artificial intelligence has great potential in the realm of economics and business. It not only relieves workers from having to do repetitive or even dangerous tasks, it is also much faster in analyzing data volumes, making decisions based on this, and completing tasks. What’s more, robots will further automate production, which will open many new doors. For example, countries such as Germany will become a more attractive production location, thus increasing its competitiveness. There will no longer be any economic reasons for outsourcing production to low-wage countries. Whole new business areas will emerge as a result of AI joining up with connected products, processes and machines (Internet of Things; IoT).

AI is developing more and more into a disruptive core technology. It will revolutionize our working lives and current software applications! Just like humans, machines are also capable of making mistakes. As long as human health, life and death are not at stake or people are not being assessed, mistakes are acceptable. Using a percentage tolerance level, we humans will define probabilities which allow us to decide if a computation is correct. We will no longer have to complete tasks or process steps ourselves, but will have to monitor and optimize machines while they handle them.

Information is the key

Our human cognitive skills are overwhelmed though by the flood of information. We don’t even use 80 percent of the information we gather! With every passing day and year, the information multiplies. Industry 4.0 and the Internet of Things will increase global data volumes by a factor of 10 by 2020. Today’s barrage of information is ideal for artificial intelligence applications. Still, ERP software like SAP is not capable of processing the bulk of this information. What’s needed is a context-sensitive software that can efficiently manage and store data volumes and, if necessary, scale horizontally. This is and has always been the intrinsic purpose and capability of enterprise content management systems such as Doxis4 from SER. Just look at DHL Express for an example of this: 8.5 billion documents are currently being stored in the Doxis4 information repository. These documents are accessed by one million users per day on average.

“Already 20 years ago, 80 percent of all information in a business context was unstructured.”

Already 20 years ago, 80 percent of all information in a business context was unstructured. This remains the same today. In the information repositories of SER’s Doxis4 ECM software, all of this information can be found – including SAP data (both current and archived data), emails, documents, social media content, websites, machine data, images and videos.

In the age of artificial intelligence, information is finally becoming a production factor. Information logistics will become one of the strongest influencing factors of value creation. The information repository, the core of ECM software, functions as a safe for the new currency in business: information. Used as a digital archive, this information repository stores empirical values and has the ability to remember.

Information management is technological and complex, which is a challenge for companies today. In addition to SAP, numerous other business applications are being used and their content is stored in separate databases and structures. This is already a source of woe for the productivity of knowledge workers. This situation will have negative consequences on the future outcomes of AI. AI needs data from various information sources to be able to learn and make forecasts. The integration of information silos spread out across companies is strategically more important than ever for IT teams.

Contact with new technology

The human-computer interface is no longer limited to a keyboard, mouse, scanner and camera. Soon all types of devices, products and software applications are supposed to respond on demand. Not in a technical language, but in the same way we would communicate from person to person. We will be able to have a human-like dialog with the machine for the first time. The possibilities of natural language processing (NLP) for ECM are currently the topic of a joint research project of the Austrian Institute of Technology (AIT) and SER.

“In contrast to humans, virtual agents do not need user interfaces.”

No more user interfaces

In contrast to humans, virtual agents do not need user interfaces. In the future, user interfaces for capturing data and for searching, forwarding or filing information will not exist in the traditional sense. As evident already in financial transactions, humans will only get involved in the business process if the system registers an anomaly or is out of control. With such algorithm-based ECM systems, business processes and many decisions can be automated for the most part. Speaking of proactive information management: Predicting our needs, it gives us information in the context of our work, actions and decisions, and we don’t have to search for it.

The companies most likely to become early adopters of AI-based ECM systems will be those of the financial services sector where the administrative staff is primarily processing information. Accounting teams must deal with huge amounts of data and its growing complexity due to new legal regulations and stricter compliance requirements. Automated inbound invoice processing is one means today of automatically processing or even of automatically posting inbound invoices.

AI must serve and provide value

The art of artificial intelligence must be to serve and provide value to people and businesses in equal measure. We are only at the beginning of these epic developments and the end is nowhere in sight. Despite all the hype, digitalization is not so far advanced in companies that we can consider it a given. Digitalization is a prerequisite for artificial intelligence.

Until AI is fully developed, we should take the time to push ahead with digitalization. This requires powerful deep learning memories. These and many more aspects are all reasons why ECM systems need to be at the top of the agenda for most companies. For already 20 years now, the ECM system Doxis4 has been using neural networks for classification and extraction. ECM systems are highly valuable and practical – they just need to be deployed. It’s the first step in the right direction!

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