AI, data fabrics and the distributed enterprise

Gartner has released its strategic technology trends for 2022, which includes the growth of the distributed enterprise, connected by data fabrics that integrate data across cloud and non-cloud platforms, and AI that can generate brand-new content and objects.

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It’s that time of year again, when—along with fall foliage and pumpkin spice lattes—Gartner comes out with its annual strategic technology trends for the year ahead. And in 2022, it’s all about growth, digitalization and efficiency.

The forecast, announced during the virtual Gartner IT Symposium/Xpo Americas this week, outlines 12 tech trends related to the growth of the distributed enterprise (which is, in fact, one of the trends).

While ‘distributed enterprise’ sounds a lot like ‘hybrid workplace,’ it’s really about evolving the traditional office-centric model into a geographically dispersed one.

The distributed enterprise

Knowledge workers may already be accustomed to working anytime, anywhere, but the distributed enterprise will extend into other industries that have traditionally embraced an office-centric model.

“For every organization, from retail to education, their delivery model has to be reconfigured to embrace distributed services. The world didn’t think they’d be trying on clothes in a digital dressing room two years ago,” said David Groombridge, research vice-president at Gartner, in a press release.

There’s good reason to consider this. According to Gartner, 75 per cent of organizations that exploit the benefits of a distributed enterprise will realize revenue growth 25 per cent faster than their competitors—and they’ll realize these benefits by 2023.

But that, in turn, will place more demands on the network. We’ve already experienced this during the pandemic, as organizations turned to WFH. This next iteration means that organizations will need to evolve and perhaps re-architect the network.

Data fabrics

When it comes to re-architecting the network, we’ll see an increased use of data fabrics, according to Gartner, which integrate and connect data across both cloud and non-cloud platforms (which could also help to release valuable data trapped in silos).

Gartner defines data fabrics as a “flexible, resilient integration of data across platforms and business users.” This creates a scalable and simplified architecture that can “dynamically improve data usage with its inbuilt analytics, cutting data management efforts by up to 70% and accelerating time to value.”

And though this requires redesigning network topology, access to more integrated data could help fuel some of the other trends in Gartner’s tech predictions for 2022, such as AI—or, rather, generative AI.

Generative AI

distributed enterprise

Generative AI is a machine learning methodology that ‘learns’ about content and objects and then generates brand-new content and objects. By 2025, Gartner expects generative AI to account for 10 per cent of all data produced (currently, it’s less than one per cent).

According to Gartner, it can be used in myriad ways, “such as creating software code, facilitating drug development and targeted marketing, but also misused for scams, fraud, political disinformation, forged identities and more.”

AI engineering, another tech trend on Gartner’s list, is also key. After all, a lot of organizations are wasting time and money on AI projects that don’t go anywhere or don’t generate any value even if they are put into production.

“By 2025, the 10% of enterprises that establish AI engineering best practices will generate at least three times more value from their AI efforts than the 90% of enterprises that do not,” said Groombridge.

Read more:

Allstream Q&A: The future of hybrid work
Reshaping the network for a post-COVID world
Tips for a successful transition to hybrid work

Cloud, security and automation

A few other noteworthy trends include:

  • Cloud-Native Platforms: Organizations will need to move away from ‘lift and shift’ cloud migrations toward CNPs that provide elastic IT-related capabilities as a service, “delivering faster time to value and reduced costs.”
  • Cybersecurity Mesh: A cybersecurity mesh architecture (CSMA) will help to reduce the financial impact of security incidents through integrated tools, common APIs and centralized management that secures all assets, regardless of location.
  • Hyperautomation: By rapidly identifying, vetting and automating multiple processes, hyperautomation—which uses machine learning and automation tools—allows organizations to speed business processes and decision making.

Whether you call it ‘hybrid work’ or ‘distributed enterprise’ doesn’t matter. What matters is that your network needs to be able to handle the added demands for the future of work.

Images: gremlin/iStock; in-future/iStock

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