How to find new growth points amid uncertainty Gartner analyzes the top ten strategic technology trends in 2023

Geopolitical conflicts, global supply chain turmoil, epidemics and extreme weather... Affected by multiple factors, most CEOs said in surveys that they believed the global economy may experience a recession next year.

Recently, Gartner released the top ten strategic technology trends that enterprises need to explore in 2023. Gartner pointed out that in order to increase profits during economic turbulence, enterprises must shift their focus from cost savings to new ways of operating excellence while accelerating digital transformation. Gao Ting, senior research director of Gartner’s innovative technology research team, introduced that from the perspective of business goals, they sorted out these ten strategic technology trends around the three major themes of optimization, expansion and development to help enterprises cope with future uncertainties. Certainty, he brings an in-depth interpretation of the top ten trends.

Trend One: Digital Immune System

The concept of “digital immune system” was first proposed in the 1990s. At that time, it referred to a set of fully automated defense systems. Virus solution, today it has been given a new meaning: a set of software engineering methods, techniques and practices used to build stable systems.

In the traditional field of software engineering, a software quality system based on testing is mainly relied on to ensure the robustness of the software. Today, testing alone is no longer enough, and a digital immune system is needed to "vaccine" it. Similar means can be used to improve the robustness of software systems. Therefore, the "digital immune system" is not a single technology, but a set of combinations of various methods and modules, including observability, artificial intelligence enhanced testing, chaos engineering, automatic repair, site reliability engineering, application Six core modules of supply chain security.

Gartner predicts that by 2025, investing in digital immune systems will enable companies to reduce system downtime by up to 80%, and the reduced losses will directly translate into higher revenue.

Trend 2: Application of Observability

"Observability" refers to a logic: judging the internal status of the system by observing the information output by the system department , and then optimize the system, and when this logic is extended from "IT observation/IT monitoring" to enterprise operations, we call it "application observability".

Observability application process: In the first step, the enterprise makes a decision and generates corresponding data results after implementation; in the second step, the enterprise collects feedback data on the decision and overlays usage scenarios to interpret the data; third The third step is to apply AI analysis to provide suggestions for decision-making; the fourth step is to optimize decisions based on the suggestions and form new decisions; the fifth step is to generate new data results...

Applying Observability ProcessWith this continuous feedback loop, enterprises can achieve more accurate data-driven decisions.

Gartner gave an example of the use of observability applications in Tesla. The company has launched "insurance pricing based on real-time driving behavior" measures in some states in the United States. The price of each car insurance is based on five dimensions of data. Scoring adjustments.

Trend Three: AI Trust, Risk and Security Management

As AI applications become more widespread, algorithm fairness and AI security have received more attention. Gartner's survey shows that 41% of enterprises have experienced AI privacy leaks or security incidents.

Gartner pointed out that if enterprises actively manage AI trust, risk and security issues, it will help more AI projects move from the proof-of-concept stage to the production stage, bringing greater business value. Gao Ting gave an example of an interpretable AI model created by a Danish company. Through this model, we can understand the causality between the high mortality rate of female breast cancer and certain gene combinations, helping the company discover more precise and effective treatment drugs, and promote targeted drugs. research and development.

Trend 4: Industry Cloud Platform

Industry cloud platform is essentially a new cloud service model.

The traditional cloud service model divides the cloud into IaaS, PaaS and SaaS layers. Enterprises can either use IaaS PaaS as infrastructure and build their own applications on top of it, or directly purchase one-stop SaaS solutions. , the infrastructure part is customized by the cloud vendor. The industry cloud platform is another market segment in addition to the above two usage paths.

The essence of the industry cloud platform is to combine the IaaS PaaS layer of the current public cloud and use it as a technical base to disassemble the SaaS specific customized solution into reusable functional modules to provide customization for enterprises. development.

The advantage of the industry cloud platform is that it has more business functions than "IaaS PaaS" and is more flexible than the one-stop SaaS model.

Gartner predicts that by 2027, more than 50% of enterprises will use industry cloud platforms to accelerate their business projects.

Trend Five: Platform Engineering

Platform engineering is actually a complementary form of DevOps.

DevOps was formed because enterprises wanted to integrate "operation and maintenance" with "development". However, during the implementation process, some enterprises simply understood it as "letting developers be responsible for operation and maintenance work", resulting in a lack of development resources. excessive application. In response to the problem of too heavy development burden, the new architecture of platform engineering came into being.

Platform engineering is a set of mechanisms and architecture used to build and operate a self-service internal developer platform that supports software delivery and life cycle management. The platform can cover all operational needs of the entire application life cycle. The platform is The automated tools on the platform complete the subsequent release and operation and maintenance processes to optimize the developer experience.

Gartner predicts that by 2026, 80% of software engineering organizations will have platform teams, 75% of which will include developer self-service portals.

Trend Six: Wireless Value Realization

Since no one technology can dominate, enterprises will use a range of wireless solutions to meet office Wi-Fi, mobile Requirements for all scenarios such as device services, low-power services, and radio connections. Gartner believes that by 2025, 60% of enterprises will use more than five wireless technologies simultaneously. The capabilities of these wireless technologies are no longer limited to network connectivity, and a variety of wireless protocols will directly generate business value, using built-in analytics to provide insights.

At present, the commercial value of wireless mostly appears in the form of vertical fragmented solutions rather than comprehensive one-stop solutions. For example, Shufersal supermarket in Israel puts IoT monitoring chips in plastic baskets to help it solve the supply chain problem. and cold chain management issues.

Trend Seven: Super Applications

The Chinese Internet is no stranger to super applications. Alipay and WeChat are typical super applications - integrating application, platform and ecosystem functions All in one, it has a huge number of users and traffic.

Nowadays, the super application model is spreading from China to Western countries, being copied and imitated. The third-party payment platform PayPal has released its super application app, which provides a combination of payment, savings and other financial tools. Tesla CEO Musk is also a fan of super applications. He has previously promised to turn Twitter into a super application similar to WeChat.

Trend 8: Adaptive AI

Traditional AI systems need to face the changing environment, need to add more training data to iterate the model, and inference often produces general results, rather than personalized results. Therefore, AI models need to move towards a future of online training and online reasoning, realize real-time updates of AI models, and form a forward cycle of training and reasoning to adapt to changes in real-world conditions that cannot be foreseen or obtained during the initial development process, that is, "adaptive AI".

Adaptive AI can dynamically adjust learning and goals based on real-time feedback, which is suitable for operations where the external environment changes rapidly, or where corporate goals are constantly changing and the response speed needs to be optimized.

Trend 9: Metaverse

There is no doubt that metaverse is the hottest word in the Internet field this year.

Definition of the Metaverse

Gartner’s definition of the Metaverse is: a universe constructed through virtual technology A collective virtual shared space that merges physical and digital reality with persistent features to provide an enhanced immersive experience.

Contrary to the common view that the Metaverse is still far away from the public, Gartner found that relevant pilot cases and business models have emerged in the Metaverse. Gao Ting took the Kookmin Bank's "digital human" pilot as an example to analyze the implementation of the Yuanverse vision. The current supporting technologies behind digital humans, such as "ray tracing" rendering engines, natural language processing, knowledge graphs, facial expression recognition and other technologies are at the critical point of commercialization. When these technologies mature, the business model of "digital humans" will exist Realization possible.

Gartner predicts that by 2027, more than 40% of large enterprise organizations worldwide will use a combination of Web3, augmented reality (AR) cloud, and digital twins in Metaverse-based projects to increase revenue.

Trend 10: Sustainable Technology

Sustainability runs through all of the above strategic technology trends in 2023. Enterprise organizations need new sustainable technology frameworks to improve the energy and material efficiency of IT services, enable sustainable development through technologies such as traceability, analytics, renewable energy and artificial intelligence (AI), while also deploying to help customers IT solutions to achieve their sustainability goals.

In recent years, extreme weather has occurred frequently, and both China and the West have paid increasing attention to sustainable development. China has proposed "carbon peaking in 2030 and carbon neutrality in 2060" #​”. What attitude should enterprises take to deal with "double carbon"? Should it be regarded as the icing on the cake, or regarded as a burden on the enterprise, or should it be implemented into specific businesses to form a long-term mechanism for implementation?

Gao Ting pointed out that "double carbon" is undoubtedly the long-term strategic goal of the country. At this stage, energy companies and high energy-consuming industries have taken the lead in being included in carbon emissions and carbon trading. With the advancement of "double carbon", all All enterprises will be included in the larger framework. If companies prepare early and use some sustainable technologies to proactively "reduce carbon", they may be able to benefit from "carbon reduction" like new energy car companies and turn burdens into benefits.

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