Gartner's Top Strategic Technology Trends for 2021

Gartner's Top Strategic Technology Trends for 2021

2021-02-03 | Other

Gartner’s trends for 2021 can be gathered into three topics: people first, location independence and sustainable delivery.

Companies need to focus on sustainable development and accept, that the factors changing their work environment happen and cannot be avoided. We just have to use them the best way possible.

People are most important! People are still the meaning of business and they need digital technology to exist in today's environment.

Location is not of importance anymore: COVID-19 changes the way employees, customers, suppliers and organizational ecosystems physically exist. To sustain this new version of business a technology change in needed.

Independent and stable supply: Whether it is a pandemic or a recession, instability exists in the world. Companies ready to adapt to the environment will overcome the disorder and negative processes and will once again go the way of profit.

The following nine strategic technological trends do not occur individually but enhance each other. Together, they allow for faster adaptation to the environment and processes. This will help guide organizations properly over the next five to ten years. If you want to be successful in the coming years, it is good to focus on training in these sectors. And if you manage an outsourcing center, consider targeting your business to them.


Internet of Behaviors

Internet of behaviors refers to the use of data to change people's lives and the way they interact with machines. IoB brings data from both digital and physical world to influence actions and human behavior through feedback.

When employees at an industrial site returned to the workplace after it was closed during the COVID-19 pandemic, they noticed a few differences. Sensors or RFID tags were used to determine whether employees were washing their hands regularly. Computer vision determined if employees were complying with mask protocol and speakers were used to warn people of protocol violations. This behavioral data was collected and analyzed by the organizations to influence how people behaved at work.

Gartner offers another example of how software can monitor the habits of drivers and how this data can be used to increase safety, productivity and optimize daily travel.

However, some of the complicating factors related to IoB have to be considered, including the social and ethical implications. Nobody wants to be watched and his behavior used by other people to achieve their goals.   

Total experience with the business

The overall experience combines user and employee experience to impact and transform business results. The goal of the technology is to improve the overall experience of employees, customers and suppliers and to take advantage of the destructive aspects of the current pandemic.

Gartner gives an example of a telecommunication company that is changing, in order to improve both satisfaction and safety. The report notes: “First, they arranged a meeting through an existing application. When customers arrived at their scheduled time and approached 20 meters from the store, they received two messages. First one on how to go through the check-in process. The second how long it will take to reach the store safely and keep social distance”.

The company put more digital desks in the store and allowed workers to share their own tablets on customers' devices, without having to contact them physically. As a result, the customer experience for clients and employees has improved and they have interacted safely as well.

Privacy-enhancing computation


A privacy-enhancing technologies (PET) are technologies that embody fundamental data protection principles by minimizing personal data use, maximizing data security and empowering individuals. PETs allow online users to protect the privacy of their personally identifiable information (PII) provided to and handled by services or applications.

The privacy calculation focuses on three technologies that protect the data as it is used. The first one offers a trusted environment, in which it is possible to process or evaluate confidential data. In a decentralized way, the second conducts processing and analytics. Prior to retrieval or analytics, the third encrypts data and algorithms.

Gartner pays attention that this trend allows organizations to "collaborate on research securely in regions and with competitors without sacrificing confidentiality." This approach has been developed specifically for the growing need to share data, while maintaining confidentiality or security.

Distributed cloud

Distributed cloud refers to cloud services spread in different physical locations, while operation, management and development remain the responsibility of a common public provider.

The system allows many clients to have access and supports operations (create, delete, modify, read, write) on that data. Each file may be partitioned into several parts called chunks. Each chunk may be stored on different remote machines, facilitating the parallel execution of applications.

The physical convergence of the services in a distributed cloud reduces latency as well as data costs. Which helps to ensure compliance with the law, that data must remain in a specific geographical region.  

Anywhere operations


This model had been highlighted by the crisis and will remain after the end of the pandemic. Given the fact that more and more businesses seem to be done remotely, the model makes it easier to work everywhere.

For example, bank accounts could be managed by mobile devices - from transferring funds to opening accounts. This does not mean that there is no room for physical space, but it needs to be digitally enhanced. Imagine visiting a physical store without contact.

Cybersecurity mesh

The threat of unauthorized access is expanding with the remote office solutions. Company information is now more distributed than ever and home office created new playground for hackers. The cybersecurity network offers new opportunities for counteraction with this new threat.

In order to use the COVID-19 pandemic for their phishing attacks, criminals continue to improve their technology and tactics. Their attacks often occur at the same time with significant events. Such are peaks of new cases or the disclosure of a new vaccine.  

As Brian Burke, research vice president at Gartner, said, “We’ve passed a tipping point - most organizational cyberassets are now outside the traditional physical and logical security perimeters.”

The cybersecurity mesh is a distributed architectural approach for scalable, flexible and reliable control. There are already many assets outside the traditional security perimeter. Essentially, the cybersecurity network enables the defense perimeter to be established around the identity of an individual or item. It allows for a more modular, responsive approach to security by centralizing security policies.

Intelligent composable business

An intelligent composable business is one that can adapt and fundamentally rearrange itself based on a current situation. Intelligent composable business turns decision-making into a stronger, more versatile approach by accessing and reacting to data. Redesigned digital work models, autonomous operations and new goods, services and platforms would allow intelligent composable business to exist.

The smart business can be adapted and fundamentally rearranged according to the current situation. As organizations accelerate digital business strategy to drive faster digital transformation, they need to be flexible and make quick decisions by analyzing currently available data.

To do this successfully, organizations must provide better access to information, and have the ability to respond quickly to the consequences of that information. This will also include increasing autonomy across the company, allowing part of the business to respond quickly instead of waiting for the result of inefficient processes.

AI engineering


In the last four years, the market for "Artificial Intelligence Specialists" has risen 74 percent, according to LinkedIn's 2020 Emerging Jobs Survey. With more companies than ever (even those outside of the tech) relying on AI tasks as part of their daily business, demand for practitioners with this expertise will only grow.

An artificial intelligence engineer is a person who works to create models that power AI-based applications with conventional machine learning techniques, including natural language processing and neural networks.

Getting the most out of artificial intelligence (AI) investment requires a solid AI engineering strategy for scaling, better performance and reliability. Many companies had problems with artificial intelligence projects due to poor management, scalability and maintenance.

Gartner notes: “Due to the managerial aspect of the engineering art of artificial intelligence, a responsible AI is emerging that deals with issues of trust, transparency, ethics, fairness, comprehensibility and compliance.”


Hyperautomation, which was the number one trend listed in Gartner's 2020 projections, notes that anything that can be automated must be automated. Without hyperautomation, businesses with inherited processes that are not standardized, due to an inefficient approach, will suffer from expensive and comprehensive problems.

Many organizations use not optimized technologies, not sufficiently understood by employees. At the same time, accelerating digital business requires efficiency, speed and democratic processes. Organizations that do not focus on efficiency and flexibility, will have huge losses in the years to come.

Related topics: Business Gartner’s top 10 strategic Technology trends for 2020

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