A great example of an organization that has worked to achieve cloud maturity is Deutsche Bank. By 2026, they have furthered their journey by leveraging cloud maturity to deploy secure, private AI models that assist in risk management and customer service. To do this, the organization invested first in their technologists, providing them with the resources and training they needed to become cloud fluent and build new solutions in the cloud from the ground up.
Editor’s Note (January 2026): This piece has been updated to reflect the latest technological trends, including 2026 global spending forecasts and the critical “AI skills gap” currently impacting the global economy.
By Drew Firment, VP, Partnerships at Pluralsight
When taken seriously, cloud maturity becomes a distinct competitive advantage for organizations. It strengthens business infrastructure at scale, allowing organizations to shift focus away from hardware management and towards delivering AI-powered experiences for their customers. However, when cloud maturity is deprioritized or neglected, security issues, budget inefficiencies, and under-skilled tech workers abound.
Cloud Computing is the Present, and the Foundation for AI
Organizations who achieve a high level of cloud maturity have much to gain over organizations that stop at cloud adoption. Recent McKinsey analysis suggests that by 2030, the business value derived from cloud-supported innovation and product development could exceed trillion globally. Cloud maturity directly contributes to an organization’s bottom line.
The potential rewards for getting cloud strategy right are too high for leaders to ignore. It’s not enough to simply migrate existing features or data into the cloud—tech leaders must reshape their business practices to get the most out of their cloud investment.
Investing in cloud computing can also save an organization manpower by decoupling the cloud software—computing, storage, and network resources from hardware. However, in 2026, the focus has evolved toward Platform Engineering. This allows technologists to focus on building value through “golden paths” rather than managing the underlying plumbing of the cloud.
What is Cloud Maturity?
These cloud adoption stats are staggering. However, despite widespread cloud adoption, organizations are still struggling to ensure that their teams are fully cloud literate. The Pluralsight 2026 Tech Forecast reveals a sobering reality: while AI investment remains a cornerstone of digital transformation, 95% of organizations have struggled to find ROI due to a massive gap in hands-on expertise.
This stat alone shows that simply adopting cloud technologies is not enough to enable your organization to make the most out of its cloud investments. Businesses must begin searching for ways to move from cloud adoption to cloud maturity—a holistic approach that enables tech teams to become cloud experts while executing on organizational cloud goals. Here’s how to start the process.
- Level 1: No Cloud—These are the organizations that use solely on-prem solutions and have not adopted cloud technologies.
- Level 2: Ad Hoc Cloud—These organizations may be dabbling in cloud solutions, but have made no meaningful shift towards cloud adoption or governance.
- Level 3: Cloud Default—These businesses have clear cloud governance and a documented approach for cloud operations and automated guardrails that are always or almost always followed.
- Level 4: Cloud Native—These businesses proactively deploy and manage cloud infrastructure utilizing Platform Engineering principles that enable improvements in capabilities across the organization.
- Level 5: Cloud Intelligent—These organizations use autonomous cloud governance, AI-driven cost optimization (FinOps), and self-healing infrastructure to enable rapid scalability of security and core AI-driven business capabilities.
As I’ve alluded to several times already, a focus on cloud maturity is crucial for organizations who have adopted cloud technologies, but have not yet optimized them. Cloud maturity refers to the extent to which cloud governance and development is optimized within an organization, allowing for scalability and alignment with business objectives.
This misalignment between organizational cloud maturity and tech worker cloud skill levels is especially concerning because human error and the “AI Skills Gap” continue to dominate as the leading causes of cloud security failures. IDC research estimates that these talent shortages could cost the global economy up to .5 trillion by the end of 2026 through product delays and impaired competitiveness.
There are a variety of reasons that cloud computing has been steadily gaining popularity over on-prem solutions. Some of the most obvious advantages of the cloud are flexibility, scalability, and improved speed to market. In 2026, the primary driver has shifted: the cloud is now the mandatory engine for Artificial Intelligence. As noted in Gartner’s 2026 AI Spending Forecast, worldwide spending on AI infrastructure and services is set to reach .52 trillion, as technology providers continue to build out AI foundations.
Making Cloud Maturity your Competitive Advantage
Despite the fact that so few technologists feel well-versed in cloud technologies, internal upskilling ranked relatively low on the list of actions taken towards cloud maturity in the study. The 2026 Tech Skills Report found that while executives rank cloud as the top area of growth, many organizations still lack the hands-on labs necessary to close the gap.
As we move through 2026, less than half of organizations rated themselves as having a high level of cloud maturity. Now that we have an understanding of what cloud maturity is, how does an organization go-about increasing their cloud maturity? According to our research, the top ways that organizations are increasing their cloud maturity is through integrating FinOps into the development lifecycle, adopting serverless architectures for AI workloads, and enabling hybrid-sovereign cloud environments to meet 2026 data privacy regulations.
Though most organizations have adopted cloud in some way, very few organizations are actually optimizing their cloud spend. The State of FinOps 2025/2026 report found that managing AI/ML spend and achieving unit economics have become the highest-rising priorities for practitioners, with over 63% of organizations now actively managing AI-related cloud costs. While many factors contribute to cloud overspend, I believe that one of the key drivers is a lack of cloud maturity. For some organizations, simply implementing a cloud solution into the business structure may seem sufficient. To achieve true cloud transformation, though, tech leaders need to optimize cloud fluency across all levels of the organization.
Cloud maturity is not something an organization gains overnight. Rather, cloud maturity must involve a strategic effort from all levels of the business to optimize cloud spend, mitigate cloud-related risks, and upskill workers in cloud technologies. In 2026, maturity is the difference between an “AI-Experimenter” and an “AI-Leader.”
In 2026, cloud maturity can be categorized in five different levels:
For the past several years, most organizations have made it their priority to shift much of their applications and data from on-premises to the cloud. In fact, the Gartner Worldwide IT Spending Forecast projects that cloud-related software and data center systems will drive a nearly 10% hike in total IT expenditure this year. Furthermore, with 94% of enterprises now utilizing cloud services, the “migration” phase of the last decade has become a historical milestone rather than a current goal.
