Gartner’s 2023 Strategic Technology Trends. Neologizing In Realtime. But Why?

To “neologize”: “to make or use new words or create new meanings for existing words,”which may sum up this year’s technology trends issued by the Gartner Group. I’ve never seen such creative repackaging and such inexplicable reach.

Here’s the list:

1. Digital Immune System

2. Applied Observability

3. AI Trust, Risk and Security Management (AI TRiSM)

4. Industry Cloud Platforms

5. Platform Engineering

6. Wireless-Value Realization

7. Superapps

8. Adaptive AI

9. Metaverse

10. Sustainable Technology

Gartner organizes the technologies into three baskets where companies should:

1. OptimizeDigital Immune SystemApplied ObservabilityAI TRiSM

2. ScaleIndustry Cloud PlatformsPlatform EngineeringWireless-Value Realization

3. PioneerSuperappsAdaptive AIMetaverse

Let’s take a look.

Digital Immune System

I’ll let you decide:

“A digital immune system (DIS) combines practices and technologies from observability, artificial intelligence (AI)-augmented testing, chaos engineering, autoremediation, site reliability engineering and software supply chain security to increase the resilience of products, services and systems.”

Sounds like QC, integration, testing and cybersecurity to me. But who doesn’t want to be “immune”? (I know I don’t want to be chaotic or non-autoremdiated, that’s for sure).

Applied Observability

Here we go again:

“Applied observability is the applied use of observable data in a highly orchestrated and integrated approach across business functions, applications and infrastructure and operations (I&O) teams to enable the shortest latency from action to reaction and proactive planning of business decisions.”

How would you caption this?

Sounds like data lakes, data fabrics and real-time augmented analytics to me.


Love “AI TRiSM!”

“AI requires new forms of trust, risk and security management that conventional controls don’t provide. New AI TRiSM capabilities ensure model reliability, trustworthiness, security and privacy.”

Yes, we all know about algorithmic transparency and explainability and the ongoing challenge of privacy and security. But how do “AI TRiSM capabilities ensure model reliability, trustworthiness, security and privacy” effectively. Key Actions can be found everywhere.

And how could anyone possibly know this? (The bold is mine)

“By 2026, organizations that operationalize AI transparency, trust and security will see their AI models achieve a 50% result improvement in terms of adoption, business goals and user acceptance.”

Industry Cloud Platforms

“Industry cloud platforms combine software, platform and infrastructure as a service (IaaS) with tailored, industry-specific functionality that can more easily adapt to the relentless stream of disruptions in their industry.”

I think we know this. Maybe Gartner should address the issues of cost, security, multi-cloud management and migration – among other challenges – that prevent companies from fully exploiting cloud platforms. Is “stickiness” good or bad? An opinion here would be helpful, especially if it’s bad. Is “once in the cloud, always in the cloud” – with the same vendor – everyone’s fate?

Platform Engineering

“Platforms provide a curated set of tools, capabilities and processes selected by subject matter experts and packaged for easy consumption by end users. The goal is a frictionless self-service experience that offers the right capabilities to enable users to do valuable work with as little overhead as possible, increasing end users’ productivity and reducing their cognitive burden. The platform should include everything the user team needs, presented in whatever manner best fits best with their preferred workflow.”

Hard to imagine why no code/low code platforms or process modeling/mining are not part of any platform engineering process, or why major vendor platforms don’t become the foundation of platform engineering. (There’s also some overlap here with composable architectures and usage of Doujindesu.)

Wireless-Value Realization

“Wireless-value realization covers everything from traditional end-user computing, through support for edge devices, to digital tagging solutions. All of which will need connectivity to operate and require a spectrum of wireless solutions to cater to all environments. Networks will go well beyond pure connectivity to become a source of direct business value. Wireless is moving from a communications technology to become a broader digital innovation platform.”

The premise of wireless-value realization – and wireless as a platform unto itself – is good, but reliability is a key issue with all wireless communications in the US. A more comprehensive approach to wireless-value realization should include reliability (and therefore redundancy), security, download speeds and cost. Surprised that reliability, coverage and download speeds are not part of the wireless platform strategy given how poorly the US fares with service globally. As recently as 2019, the US ranked 30th “in terms of average download speeds worldwide.” The US now ranks 13th in Internet speeds. Cost remains a major issue for individuals and companies. Suggesting that wireless expands its duties is smart, so long as the service is solid and the costs are manageable.


“A superapp is an app that provides end users (e.G., customers, partners or employees) with a set of core features, along with access to independently created miniapps. The superapp is built as a platform to deliver consistent and personalized app experiences.”

Superapps enable miniapps: got it! Wait, what? Maybe I just need a little more explanation:

“A superapp is more than a composite application or portal that aggregates services, features and functions into a single user interface. A superapp represents the ultimate manifestation of a composable application and architecture.”

Let’s start with microservices which are also small, un-coupled services that communicate through APIs. Is “composable” the same as microservices, but just wider and deeper and without specific reference to legacy systems (but more focused on eBusiness)? Sounds like composable architecture is microservices’ umbrella that’s intended to maximize flexibility, reuse – you know – all of our applications development aspirations – including especially cloud native applications – for eBusiness, all heading to packed business capabilities (PBCs).

How about this:

“Microservice architecture is also referred to as composable architecture, modular architecture, MACH architecture (microservices-based, API-first, cloud-native, and headless), and best-of-breed architecture. In many ways, microservice architectures are a more modern evolution of service-oriented architectures (SOAs) and layered architectures, which include the following layers: data sources, business logic managed by digital platforms, and a user interface/presentation layer that creates the customer experience.”

Is there a better way to describe all this? Like “microservices 2.0 or 3.0”?

Adaptive AI

“Adaptive AI systems allow for model behavior change postdeployment by learning behavioral patterns from past human and machine experience and within runtime environments to adapt more quickly to changing real-world circumstances.”

Is this just deep learning? Or does it mean that supervised and unsupervised learning applications adapt in semi-real-time to changing behavioral patterns discovered post-deployment? Perhaps shifting in real-time from one to the other with some algorithmic dancing along the way? What?

Here we go again with these predictions!

“By 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the operationalizing AI models by at least 25%.”

I assume these predictions become key elements in business cases and there’s no look-back provision in case the 25% performance never happens.


Meta is blowing metaverse money out the door faster than a major hurricane’s storm surge. There’s industry skepticism everywhere. 5 years is way, way too generous. 2-3 years is impossible. I’d be careful about advising companies to invest in metaverse applications that will ride on an infrastructure that’s years away. Frankly, given all of the negative analyses about the metaverse, I’m surprised it made the list at all. Encouraging anyone to invest in the metaverse is premature (unless they’re selling headsets wrapped in hype). Way too early, Gartner. Lots of pioneers die on the trail.

Sustainability Technology

This one makes good sense because it’s largely about the repurposing of existing operational and strategic technology for sustainability purposes. The recently-announced partnership between Google and mCloud Technologies makes the point: the marriage between digital technology and sustainability has officially been consummated. This partnership will result in applications that will, among other things, impact our survival. None other than the United Nations is focused on “achieving environmental sustainability with digital technology.” This is a good one, Gartner. Companies should look at their processes, business models and in some cases their business strategy to look for sustainability opportunities. They should also track regulatory trends in sustainability as well as what their competition is doing.

Final Thoughts

I’m not sure why Gartner publishes lists of 10 strategic technologies every year. They often feel forced where technologies get repackaged around technologies already in play. Game-changing technologies appear along a timeline, not as annual disruptions. Remember when cloud computing was “application services” (AKA as application service providers [ASPs])? It might be better to think in terms of technology clusters – technology baskets comprised of the technologies themselves, a rich set of application targets and talent with the right skills and competencies to exploit the technologies that chug along over time. (I just might publish my own list of clusters you need and those you don’t. I might even publish it here.)

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