By Matt Wong, VP Delivery & Operations, CloudSphere
For most businesses, the operation and maintenance of cloud computing environments is the responsibility of the Chief Information Officer (CIOs) and IT team. As 94% of enterprises use some form of cloud service, it’s not surprising that many in the industry are feeling the weight of this task.
Additionally, as reported by Gartner, approximately 80% of businesses are predicted to migrate towards cloud hosting by 2025. This means that the complexities of managing cloud computing environments only promise to increase for CIOs and other IT professionals.
However, with the transition towards the cloud also comes the ever-evolving technology of generative artificial intelligence (AI).
In this article, we’ll cover the main challenges that CIOs and IT professionals are facing in cloud computing, as well as how generative AI may be the answer to many of these operational obstacles.
The Complexities of Cloud Computing for CIOs and IT Professionals
Although cloud computing offers tech teams many benefits, they are complicated environments that need to be constantly monitored and maintained. Due to the technological nature of the cloud, CIOs and professionals in the IT sector are often the ones who become responsible for these environments.
Despite their expertise in this space, however, many IT professionals find effectively maintaining these environments to be quite challenging. Why? There are actually a few reasons.
Below are the top four obstacles that I’ve identified.
Top 4 Challenges CIOs Face with Cloud Computing
- Evolving Technology: The rapid pace of technological advancement is one major obstacle for those managing cloud environments. The world of IT never stands still, and trying to keep up can often feel almost futile.
- Advancing Standards: Best practices in the industry are also constantly shifting. What was industry standard yesterday may not hold true today, particularly regarding IT services and security.
- Constant Maintenance: Tasked with managing ongoing upgrades, updates, and new product rollouts, IT professionals are in a perpetual state of maintaining the environment.
- Climbing Costs: With the above variables in play, keeping on budget can sometimes feel like an impossible task.
The Benefits of Applying Generative AI in Cloud Computing
Within the tech space, there’s recently been an impressive surge in generative AI tools, significantly affecting the market and creating considerable investment activity. This trend is impacting a variety of industries—from technology to business applications, and beyond.
However, we have merely scratched the surface of what generative AI has to offer. This tool is still in the early stages and it’s likely that there are many exciting developments ahead. Specifically, there may be developments that will help those responsible for managing cloud computing environments.
According to Havard Business Review, generative AI is already helping automate routine tasks, freeing up IT professionals to focus on more strategic issues.
Envisioning the Future with Generative AI
As generative AI continues to evolve, the majority of organizations will likely go one of two ways: adopt the technological shift or reject it and risk becoming obsolete. Some businesses may even create promising new business use-cases for generative AI. While some of these may not work out, others will thrive and inevitably disrupt existing business practices.
There’s also Large Language Models (LLMs) to consider, which is a key element in generative AI. Investment in LLMs currently lies primarily with big corporations that have sufficient cash flow. While some companies have the resources to invest, develop, train and create LLMs, the rest of the industry will be users and customers of these systems. The owners and creators of LLMs will certainly pass down the costs to the users and applications of their systems. So, how the industry decides to integrate and use LLMs will be critical.
Conclusion
It’s undeniable that the rapidly expanding field of the cloud, as well as generative AI, has introduced new challenges for CIOs and IT professionals. However, these same tools also promise to offer possible solutions to long-standing IT management issues, including updates, upgrades, service and incident management, and security.
In the coming years, tech professionals will hopefully be able to leverage both cloud computing and AI advancements to outpace their current challenges with these environments. With this in mind, how the industry efficiently integrates and uses LLMs will be critical.
How CloudSphere Can Help You on Your Journey
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About Matt Wong
As VP of Delivery & Operations, Matt is responsible for ensuring the success of Cloudsphere’s Delivery Partners. He is one of the early contributors to cloud applications and services, beginning with his notable work for technology giants such as Apple, Hewlett-Packard and Xerox, and has built and led large product development teams as VP of Engineering at Panasonic Cloud Entertainment and VP of Engineering at Canal+ Technologies.
Matt holds a Masters of Science in Mechanical Engineering at California State University, San Jose; a Management Certificate (MDE) in Business Management/ Entrepreneurship at the University of California, Los Angeles, Anderson School of Business; a Bachelor’s of Science in Mechanical Engineering at the University of California, Berkeley, and a Bachelor’s of Science Equivalency/Computer Science at California State University, Chico (program via Hewlett Packard).
Connect with Matt on LinkedIn.
