A Look at Gartner’s Top Strategic Technology Trends for 2021

Gartner released its top strategic technology trends for 2021 last month providing organizations across the IT board with an idea of how to successfully approach the new year. Though some trends in the ongoing development of decentralization and AI may not seem like news, the exceptional impacts of COVID-19 in the 2020 tech and business world have added a unique touch. This week, we review these leading trends so that you can Live Easy, into the new year.

What we know

Election hype is wearing down and we are now left with six weeks going into this year’s holiday season. With a pandemic still lurking and the uncertainty of economic shifts to come, Gartner has summed up the following nine tech trends for 2021:

1. Internet of behaviors (IoB)
2. Total experience
3. Privacy-enhancing computation
4. Distributed cloud
5. Anywhere operations
6. Cybersecurity mesh
7. Intelligent composable business
8. AI engineering
9. Hyperautomation

Thanks to COVID-19, SMEs are already more than familiar with improving total experience for better business outcome (from customers and users to employees), and maintaining anywhere operations so business can be accessed, delivered, and enabled at any location. Business intelligence (BI), or as Gartner calls it this year – intelligent composable business – has also been at the top of CIO priority lists for some time, and it seems that repeating well-known tech trends this year has left some enthusiasts less than satisfied.

Villanova business tech professor Steve Andriole describes Gartner’s 2021 top strategic trends as easy, weird, and incomplete. In this light, those well-known cloud, AI, cybersecurity, and BI trends are considered easy, while efforts to revamp old tech by renaming them the Internet of Behaviors and privacy-enhancement computation are depicted as weird. Andriole then goes on to list important tech such as 3D manufacturing, low code-no/code programming, and ethical AI which didn’t make the list this year – tech to consider going into 2021.

Despite these critiques, however, it’s worth the time to review these top trending techs and just how organizations can put them together for a successful new year. It’s not necessarily about the individual technologies, but their seamless collaboration for better business operations and continuity.

Privacy in IoB and digital surveillance

The IoB, or as Adriole points out as simple – digital surveillance – essentially gathers and analyzes data to change behaviors, and we’ve seen it dominate via COVID-19 safety measures. Employees returning to work after mass closures became subject to IoB tech including sensors or RFID tags used to monitor hand hygiene and computer vision for mask compliance with speakers to warn of violations. The objective was, and still is, to influence how people behave at work.

We see this technology spreading across industries. Telematics in commercial vehicles monitor driving behaviors to improve driver performance, health insurance companies monitor wearables to track physical activity and adjust premiums, and auto insurance companies track driving habits to do the same. Data is collected from various sources including, as Gartner lays out, commercial customer data, citizen data from government agencies, social media, facial recognition, and location tracking. The applications seem endless, though ethical and privacy concerns remain at the forefront.

In 2012, University of Helsinki retired Psychology Professor Gote Nyman developed the concept that behavior can be data mined. In other words, the intentions of the human background can be used to determine what is about to happen in the connected world. With the continued development of the internet of things (IoT) and digital surveillance, however, this notion has brought about questions concerning cybersecurity and the ability of cybercriminals to access sensitive data that reveals consumer behavior patterns. Furthermore, as researcher and technology author Chrissy Kidd explains in BMC blogs, “The IoB approach, interconnecting our data without decision-making, demands change of our cultural and legal norms, which were established before the Internet and Big Data Ages.”

The IoB is changing how organizations interact with people, making business operations and consumer activities more efficient and convenient. However, as the percentage of the global population subject to IoB programs grows, businesses should keep in mind the varying privacy laws from one region to the next associated with this trend, and how they will affect the adoption of such programs.

Distributed cloud and cybersecurity mesh

We never pass up the opportunity to talk about the cloud, and as Gartner highlights, “distributed cloud is the future of cloud.” In our article on how decentralized storage networks are transforming the cloud, we look at what it means to decentralize cloud storage. While we use the terms decentralized and distributed interchangeably for this topic, there is a difference – decentralized cloud storage is really a subset of distributed cloud storage.  So, what’s the difference?

The following illustration from BlockChain Engineer depicts the difference between a centralized, decentralized, and distributed network by indicating how nodes are connected and controlled.

With centralized applications, data is held in a centrally owned database, controlled by a single authority. All nodes within the network are connected to under this authority, requiring significant trust that this centralized entity is operating in the best interest of those connected.

Decentralization, on the other hand, means that no single node or authority has control over the application. Code runs on a peer-to-peer network of nodes, and no node “tells” others what to do. Decentralized cloud storage uses the power of edge computing. Processes and storage are moved to devices (endpoints) across multiple physical locations – the nodes –  at the edge of the network, rather than to a central data center. As a result, each node maintains its own cloud functionality.

Similarly, distributed applications are made up of independent nodes, but each of these individual components is connected, allowing them to communicate and coordinate directly with each other to achieve a common goal. This, like its decentralized subset, allows customers to have cloud computing resources close to the physical location where data and business activities happen, helps in low-latency scenarios, reduces data costs, and helps take into account laws that specify whether data must remain in a specified geographical location. As Gartner research vice president Brian Burke said at its flagship IT Symposium/XPO Americas conference, “distributed cloud can replace private cloud and provides edge cloud and other new use cases for cloud computing.”

In fact, the distributed architectural approach has made its way into network security, described as the cybersecurity mesh and number six in Gartner’s top tech trends. The idea behind the mesh, Burk says, is that anyone can access any digital asset securely independent of where the person or asset is located. Policy enforcement and decision making are decoupled using the cloud delivery model, which allows identity to become the security perimeter. This comes at a time when perimeter protection is becoming less meaningful as access to corporate networks is being achieved across various locations.

Business operations (now anywhere operations) and security perimeters have changed in a culture of social distancing and remote work – which we now know isn’t going anywhere. Part of keeping up now and succeeding into the new year is about adapting a distributed network, cloud, and cybersecurity architecture.

AI engineering and hyperautomation

Research efforts with Carnegie Mellon University’s Software Engineering Institute are leading the creation of an AI engineering discipline that ensures we can understand and repeat successful AI solutions. Though AI has long been among top tech trends, organizations continue to face challenges in the maintenance, scalability, and governance required to gain the full value of AI investments. With AI engineering, AI becomes part of the mainstream DevOps process, as opposed to a set of specialized and isolated projects.

We touched on this concept in our last blog with the integration of AIOps infrastructure, network, and cloud monitoring into DevOps processes as the key to business continuity. In short, finding vulnerabilities or malicious code in software, evaluating software quality, and essentially making inferences about code in situations not yet encountered is all a part of AI engineering solutions which are saving time for software engineers to focus on development and cost reduction – a critical tactic for business continuity in 2021.

With that in mind, however, the idea of ethical AI must be at the forefront of AI developments for organizations of all sizes. As Reid Blackman covers in “A Practical Guide to Building Ethical AI” for Harvard Business Review, companies are creating scalable solutions by leveraging data and AI, but they’re also scaling their reputational, regulatory, and legal risks.

To take into consideration data and AI ethics, the world’s biggest tech companies are rapidly building teams to tackle the ethical issues of widespread data collection, analysis, and use for training of machine learning models; SMEs should take similar precautions to avoid those reputational, regulatory, and legal risks mentioned earlier. Blackman’s guide covers “What Not to Do” and “How to Operationalize Data and AI Ethics”, and is definitely worth the read.

Finally, while simple and slightly repetitive, the idea of hyperautomation – automating anything in an organization that can be automated – isn’t going anywhere. Businesses with legacy business processes that are not streamlined continue to create expensive and extensive challenges, many of which arise from a lack of optimization, connectivity, and seamless collaboration. As Gartner bluntly puts it, “organizations that don’t focus on efficiency, efficacy and business agility will be left behind.”

At LeCiiR, we’re all about offering tailored SME secure, reliable, and innovative IT solutions so that you can Live Easy. For our take on more tech trends going into the new year, or for any other questions, don’t hesitate to contact us and leave your comments.