Technologies Of The Future Gartner-2022: What Businesses Should Think About Now
Technologies
In August 2022, Gartner released the traditional Hype Cycle for Emerging Technologies report, highlighting the most promising innovative technologies. Let’s see how they work in practice.
The Gartner Hype Cycle for Emerging Technologies study is an annual collection of technologies that are not so long ago but are causing a lot of buzzes. Scientific works and marketing research are devoted to them, start-ups arise around them, and investors invest huge funds in their development, hoping for a return in a few years.
The 25 promising technologies that analysts named in 2022 are divided into three groups:
The first group is associated with the development of immersive experience, that is, the experience of immersion in an artificial, digital environment: this is the digital twin of the client, decentralized identification, NFT, digital people, metaverses, super-applications, internal personnel marketplaces, web3;
the second is everything related to the application of artificial intelligence: autonomous systems, causal AI, basic models, design using AI, Machine Learning for code generation;
Technologies
the third largest group is innovations in the field of technology delivery optimization: for example, extended FinOps (Augmented FinOps), computing storages or platform development.
If Gartner rather describes the technological aspects of each of these trends, then we will try to approach them from the standpoint of practice: what new qualities have allowed this or that technology to become promising? How will it be useful to us in life and what will change with the start of its widespread use? And, of course, which of the technologies noted by analysts are the most relevant for Russia?
Client’s Digital Twins
This technology could revolutionize the field of queuing systems.
The technology is not new, its essence is that it allows you to test a product, process or business model without the need for risks in the real world. Digital twins make it possible to “digitally” test hypotheses, reducing the cost of conducting many experiments.
However, earlier we mainly talked about digital twins of some industrial facilities, perhaps entire cities. And much less about digital twins in queuing systems that are able to model and predict the behavior of customers, taking into account their personal properties.
Technologies
We can already, for example, use video analytics and other technical means to minimize queues in stores and airports – the system predicts peak loads based on the data it has. Banks model the behavior of a client or a group of clients depending on their financial situation, interests, etc. If the trend identified by Gartner enters our lives tightly, then we will see a fundamentally different approach to organizing processes in retail, healthcare and other areas .
Decentralized identity
Trends are also connected with the topic of personalization, and identity management, which represent the development of the topic of distributed registries, and blockchain. Decentralized identity, NFT, web3 – these technologies somehow give us an idea of how a person in the future can create and manage his digital twin. I think in the coming years it will become an important part of our lives.
For example, as a client of a certain store or bank, I want to independently manage my personal data and decide who, why and how to transfer them. I don’t want to give anyone access to them at all, I am against spam and ads that are annoying and therefore do not work. With certain companies, on the contrary, I am ready to share information about myself, because I want to receive targeted offers and the best quality of service – that is, convenience and personal benefit.
The new approach can significantly change the consumer market and the principle of organizing marketing chains, which are not very effective today. All that I, as a client, will need is to have my own container (that is, an isolated storage area with information about me) in some kind of secure trusted cloud, and provide access to this container to whom I consider necessary. At the same time, in fact, the neural network of the supplier of goods or services, or any of its other technological means, simply communicates with my container, without extracting my personal data from it and without transferring them to the information systems of the supplier.
It turns out that you can indirectly find out everything about each client: what product or service he needs at the moment, and what is categorically not interesting. At the same time, the supplier will not have to pay money for ineffective advertising (and these costs greatly affect the cost of the product), and will not have to deal with regulators related to personal data.
So, if earlier the supplier addressed me as an individual, and it was not always pleasant and profitable, now he can turn to my digital twin. We tune in to the level of interaction that we are both interested in. He makes me a personalized offer with a very high level of probability that I will accept it. And I get a product or service at a good price.
Autonomous systems
Among a number of trends in this block, the so-called autonomous systems are the most interesting for me as a practice. These are software systems capable of simulating phenomena of a high level of complexity that cannot be described using a classical model, mathematics, or neural networks: for example, urban transport. In the case of an autonomous system, we endow a person, a car, or a certain number of objects with certain properties and run them within one learning model that has freedom of action.
In principle, when it comes to clients, this is also to some extent an autonomous system. Every person has behavioral characteristics. We can describe the set of clients within some industry object (medical organization, bank) and thus launch a behavioral model.
Technologization of development
Another block of trends that I consider promising is related to the technologization of development. Augmented FinOps automates traditional DevOps and expands the understanding of the concept of continuous development CI / CD (the concept of continuous integration and continuous deployment of software during development). AI and machine learning can take user feedback, financial management, budgeting, and cost optimization to the next level.
The internal personnel market or personnel marketplace involves the selection of internal employees and in some cases temporary workers for projects designed for a limited time without the participation of a recruiter.
This approach can be successfully applied to the formation of teams of developers, analysts, and process design departments. The COVID-19 pandemic has significantly accelerated all DevOps processes as a way of modern development. Today, more dynamic hiring is already practiced, where a company can quickly mobilize large, complex teams and manage them remotely to create secure and modifiable code. This big trend will grow every year with some newly applied technologies, including those aimed at strengthening security.
It seems to me that it is too early to talk seriously about some of the trends highlighted by Gartner. Outwardly, these digital innovations look attractive, for example, metaverses. But there is one caveat. Until a fundamentally new generation of devices—higher-quality actuators—can be created that can provide mass access to this technology, it will remain of little use to anyone. Also, in my opinion, the significance and prospects for business of such technologies for the development of “clouds” as “platform engineering” or “cloud sustainability” are still not very clear.
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