Gartner Top 10 Strategic Technology Trends for 2020
Every year the research and consulting company Gartner publishes studies regarding today's most relevant technologies. The study's objective is to provide a compact overview of which trends already exist and what the next steps of development will look like. The trends for 2020 are collected under the theme: "people-centric smart spaces". These are technologies that will significantly change our behaviour and our living space. Such changes will also serve as the basis for disruptions in the business context over the next 5-10 years. Accordingly, we do not only look at current trends out of curiosity, but also try to align the strategic development of Merlin Project with these trends. In the following, the trends for 2020 are briefly presented and broken down to their essence.
For a more detailed description of the trends, I can only warmly recommend the original Gartner article.
Every process - whether simple or complex - basically resembles an algorithm ("if A occurs, execute B; if A does not occur, execute C") and can therefore be understood and optimized by technological means. Through artificial intelligence and machine learning, more and more processes can be automated and thus no longer require human intervention. However, automation is only a collective term for an entire toolbox: The toolbox includes the discovery, analysis, design, automation, measurement, monitoring and re-evaluation of processes. The possible applications are enormous and are becoming better and better as more data is made available.
A core characteristic of modern user experiences is their diversity. For example, you not only want to initiate the pizza delivery online, but you also want to know how far your pizza delivery person is from your front door right now? No problem! Experiences are enhanced by different, interacting interfaces - like in this example by the mobile application, which is connected to the GPS system of the vehicle.
The democratization of knowledge and expertise. Learning has never been as easy and at such a low cost as it is today. We can either acquire the technical and entrepreneurial knowledge ourselves through the globally available information density of today's world or use the support of artificial intelligence so that the required tasks are performed by it.
These include cognitive and physical improvements in humans. While we are not yet at the stage of creating cyborgs, we are moving in that direction in certain areas. To give just one example, prostheses are already being used today that can emulate the functions of the human body. In addition, technologies such as virtual and augmented reality are being used in the manufacturing industry to provide employees with additional information, such as the status of a machine, projected directly onto AR glasses, thus combining reality and digital.
Transparency + Traceability
The higher the density of data collected for general availability, the more relevant ethics and morals become with regard to their use. DSGVO and GDPR are considered prime examples of the desire for greater security with regard to our data and therefore serve as a basis for what may come to protect our information.
The Empowered Edge
The collection of data no longer takes place only in central data centers, but must be transported directly to the place of action so that efficient action can be taken. For example, an autonomously controlled car could never be safely used in a real environment if the data had to be sent to an external data center for analysis. Technologies such as autonomous driving can only be implemented by collecting and evaluating data directly at the scene of the incident. By 2023, more than twenty times as much data is to be collected at the so-called "edge of IT" than within conventional data centers.
The distributed Cloud
Cloud computing is now moving back into decentralized areas after the initially centralized accumulation in providers' data centers. While the cloud provider still delivers the service, the data center is now located at the end customer. This bypasses the problem of excessive latency and sets new standards for data protection. The trend is moving towards a hybrid cloud environment - a mixture of private and public clouds.
The autonomy of things involves more than just the medially known aspect of autonomous driving. While autonomous devices are currently used primarily outside of public spaces, the trend is towards autonomous objects also being used increasingly in public places.
Since Bitcoin emerged, the topic of blockchain has become a widely discussed phenomenon. I would like to break the topic down to a rather abstract level to build up a basic understanding. Imagine a chain with many individual parts. Each section of the chain symbolizes a data set created by a participant in the network. The data is no longer viewed individually, but as part of this chain. This allows the origin of the chain to be traced and makes it more difficult to falsify the data, since connections to the data set are located on the sections connected to it.
In order to be able to deal with the trends, new standards must be set in the field of security. The proactive recognition of harmful patterns by machine learning algorithms is only one of the possibilities to protect your own data preventively.
While these technologies will individually have a huge impact on all of our lives, the greatest added value lies in their interaction. The new data collection at the Edge and the democratization of knowledge and expertise is creating a flood of usable, structured data. With the help of this data, insights can be drawn that can relieve us in our everyday lives. In the entrepreneurial context, processes are automated (hyper-automation) and optimized, thereby reducing costs and freeing up capital for research and development. Through data-supported research and development, new insights are once again gained that simplify our lives.
Accordingly, a virtuous cycle is forming that is becoming progressively faster. At the same time, however, new topics of discussion are emerging: Will we still have enough work to occupy the entire human race if the level of automation continues to rise? How can we monitor the ethically correct use of our data in the long term, when decision making through automation will soon exceed our knowledge? Even if we cannot yet take a clear position on these issues, one thing remains certain: the future will be an immensely exciting time.