Cloud and AI

The next stage of cloud computing will redefine the way it works in the world, and AI will play a big role in how it delivers on its promises.

What does the future of cloud computing look like in the next 3-5 years? It's gotten even more interesting since the pandemic. Since 2020, cloud computing has taken a tremendous leap forward, with many businesses fulfilling their ten year road maps in ten months -- or, for some, even in ten weeks -- because of the massive growth in demand for digital information and e-commerce.

The meaning of cloud computing is changing

The idea of scalable, meterable, centrally manageable, on-demand computing infrastructure works. It fits the business models of a wide range of operations, from startup operations to vast enterprises. Today, it's better to define cloud computing based on these characteristics than it is to continue to define it as computing infrastructure managed by someone else in an outsourced data center. 

As we move forward over the next few years, edge computing will become even more prevalent. Edge devices will become more powerful, but also far more demanding, requiring large amounts of data to be processed in real-time, yet also shared organization-wide for analysis and insight.

Expect edge devices to be more connected, and to be left unattended more often. As they increase in power and intelligence (with AI and ML playing a big part here), they'll be able to perform more functions in areas of reduced or intermittent connectivity, and in areas of extreme weather or environmental conditions.

This is where 5G (and eventually 6G) come into play. 5G handles intermittent connections better, and has the ability to switch frequency and "beamform" to reach areas traditional cellular connectivity hasn't been able to reach. 5G is also putting far more intelligence into the field, which will substantially reduce latency, allowing edge devices to communicate with "the mother ship" far more quickly and with far greater responsiveness.

The growth of AI in cloud management

Increased reliance on complex cloud environments will increase the management challenges. Here, AI can help in at least four ways:

  • Automate routine tasks: There are a huge number of basic IT management tasks, like resource allocation and scaling, that could be managed by an AI. Any place where there could be a script, there could be an AI. Expect that the AI will get to the point that it takes less work to set up than a script.
  • Analyse data: Whether it's customer usage patterns, sentiment analysis, workload impacts on resources, or many other areas of observation, AI can provide insights into network operations and customer behavior that can improve reliability and highlight opportunities.
  • Improve user experience: Expect AI to provide front-end and even second tier customer support via chat and email. On one hand, it puts users into the hands of machines, but it also frees up human technicians to help with the more challenging customer problems.
  • New services and business models: As we've seen with ChatGPT, more and more cloud services are finding a way to add an AI component as a value add. Expect this trend to increase with more and more ways that AI can streamline and assist the humans who are doing the work and using the services.

Then, of course, there's security. With a security skills shortage and ever-increasing cybersecurity threats, preventing and mitigating attacks needs to be a top corporate priority – but it's also a greater and greater challenge.

As we look forward 3-5 years, the watchword is "more." More connections, more power, more AI, more security challenges, more nodes, more devices, more locations, more options, more money, more efficiency, more bang-for-the-buck, more vendors – more, more, more. And, of course, more complex challenges in managing it all. Hunter & Chase has experts certified and experienced in the field with their finger on the industry pulse, we can help organisations find the right talent and prepare for the opportunities that lay ahead.


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