eWeek: Tech Predictions for 2023: AI, Cloud, Edge, Cybersecurity, and More

On January 2, NetSPI VP of Research Nick Landers was featured in the eWeek article called Tech Predictions for 2023: AI, Cloud, Edge, Cybersecurity, and More. Read the preview below or view it online.


So you think you can predict the course of technology in the year ahead?

Really? I have my doubts. In the many years I’ve covered enterprise tech, I’ve never looked ahead and seen such a rapidly shifting landscape. As the pace of innovation leaps ahead, the leading sub-sectors of IT have become increasingly complex:

  • Artificial intelligence: The stunning debut of ChatGPT in November put us on notice: AI is growing exponentially, offering a toolset (for free!) that would’ve been sci-fi not that long ago.
  • Cloud has become the foundation of tech, but never has a foundation continued to evolve so fundamentally. Cloud is now very much multi-cloud. So customers benefit from the vast potential of combining the top hyperscalers – which is equaled only by the frustrating management and cost concerns.
  • Edge computing exploded in 2022; I can hardly count the executives I’ve spoken with recently who see it as a new leading focus. The Internet of Thing’s immersive computing environment is creating a data-rich infrastructure that supports commerce and collaboration and, eventually, the metaverse.

Data analytics – the engine that drives decision making – has forked into an array of mushrooming sub-sectors, from predictive analytics to data visualization to real time data mining. No longer a separate discipline, analytics is being built into ever more applications as a core element. I hope you like the mining of metrics for insight, because it’s becoming omnipresent.

Tech Predictions 2023 and Beyond

Fortunately, my reluctance to predict the course of tech is not shared by executives across the enterprise IT industry. The thought leaders below offer their forecast for the sectors that will shape the enterprise in 2023 and beyond.


Nick Landers, VP of Research, NetSPI

An emphasis on machine learning security, threats, and vulnerabilities

Machine learning is already deployed in numerous technologies, especially those concerned with security — for example email filters, security information and event management (SIEM) dashboards, and endpoint detection and response (EDR) products.

If you thought you could delay ML security conversations, think again. There is a growing group of security researchers focused on Adversarial ML, which includes both attacks on models themselves (inversion, extraction, cloning, etc) and the use of ML in network attacks and social engineering. In the upcoming year, we’ll see a growing list of vulnerabilities being published for ML-integrated systems.

You can read the full article on eWeek!

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