10 December 2019

Artificial intelligence (AI) is developing into a paradigm that will more or less revolutionize almost all other "trends" in 2020 and beyond. Departments can benefit as much as CIOs.

Employees from the specialist departments of practically all companies are increasingly taking on the role of developers. They should, therefore, be given suitable tools such as low-code to no-code development platforms with which they can create and implement digital solutions quickly and without programming knowledge. This and the use of "Digital Twins" is helpful if companies want to reduce time-to-market and operate closer to their customers and their requirements.

The cross-technology digitization of the entire company and its employees is at the top of the CIO 2020 agenda. If CIOs remain too passive, their position in the enterprise will quickly be undermined because others will and must take the initiative.

Because the key to one of the most pressing IT issues is in the hands of the skilled workers: how can data be prepared to drive business? The role of CIOs here is to provide a clear path to data governance. This determines how data is collected, controlled and processed. It also defines the decision-making rights between the core systems, the cloud edges (Fog) and edge systems. Cybersecurity and compliance must also be redefined.

Turning employees from specialist departments into developers and operationalizing data for the business: these core tasks span all the individual trends that will shape the year 2020.

Artificial intelligence

Because AI has a massive impact on virtually all other issues, the deployment scenarios explode. Today's advanced analytics methods encompass the (partially) autonomous investigation of content and now go well beyond the traditional methods of business intelligence (BI). By linking neural networks, multidimensional intelligence is created that can cover an ever-increasing spectrum of application fields. The aim is to enable Artificial General Intelligence (AGI).

The driving technology behind this is usually adaptive and constantly self-improving machine learning (ML), including visual analysis and intelligent platform-as-a-service or serverless computing services. Anti Bias" AI is increasingly used for safer decision-making: it highlights advantages and disadvantages, strengths and weaknesses in order to predict probable behavior or identify possible deviations. Visual Analytics, on the other hand, are suitable for risk assessment and response - for analyzing fraud, optimizing routes or detecting outliers, for example.

IoT, Edge Computing & Augmented Mobility

The Internet of Things (IoT) is one of the longest-running top trends. The topic is set to receive a further boost, as the implementation of the 5G mobile radio standard is gradually gaining ground. This makes it easier and faster to integrate the numerous devices and "things" that are outside LAN and WAN ranges.

However, companies must continue to be patient because the 5G rollout - like the 4G rollout - is progressing sluggishly. It can be assumed that five to ten years will pass before 5G coverage is available throughout Germany.

This will also slow down numerous augmented mobility applications in driving assistance, gesture recognition, factory automation and authentication. Despite this, 3D sensor cameras are now being used in more and more IoT scenarios. In addition, more data glasses will be available on the market in 2020, so that the widespread use of augmented mobility will overcome another hurdle. However, 4G is not sufficient for many augmented mobility applications. If 5G is delayed, this also slows down these use cases and the business benefit.

Another obstacle: IoT projects are often small at first. For service providers, however, they only pay off when they can be broadly scaled and rolled out across national borders. Many providers are unwilling to accept longer periods of lean periods in order to be able to participate in large-scale projects after all.

For cost reasons, IoT will continue to focus on edge computing. At present, it is estimated that not five percent of the data generated in the production environment is evaluated. But even now it is often too expensive to store this data in the public cloud. This is where Edge Computing comes into play, analyzing the data where it arises and making it available to users close to the edge if required - without great latency. Latency-sensitive autonomous navigation, remote monitoring, face recognition, video analysis and, last but not least, augmented reality applications will benefit from this.


This article is published on website.


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