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4 Strategies to Optimize Cloud Investments and Maximize Value

Mayank Bhargava
VP Consulting Services and Cloud Modernization Practice Leader
CGI

As companies scale their cloud strategies, IT and finance leaders are looking to maximize both operation efficiency and return on investment. On their digital transformation journey, companies are migrating more workloads to the cloud, which can incur higher costs during the process due to the higher volume of cloud resources needed. However, it is also an opportunity to create more agile, resilient systems that will lower costs in the long term while increasing its business value.

Additionally, many organizations are increasing the number of advanced cloud-based services. This includes the addition of artificial intelligence, machine learning, data analytics, and similar technologies that demand more resources and have higher associated costs.

Still, when managed effectively, cloud and even multi-cloud strategies can offer significant savings compared to on-premise. However, organizations must be mindful of the challenges that can arise when embracing cloud and multi-cloud strategies, as unexpected costs can balloon quickly.

Organizations can employ several strategies to mitigate rising cloud costs. Implementing a robust cloud governance framework that includes ongoing cost optimization practices is key. Here are four critical components of a cloud governance framework that can help keep cloud costs under control.

1. Right-sizing resources

The first step is to right-size resources by matching the type and size of instances to the needs of the workload. In this process, tech leaders will examine the performance of the company's cloud instances, as well as analyze its cloud usage patterns and needs. By accumulating this data, the organization can determine if unused or underutilized services can be eliminated.

In addition to pure cost cutting, the right-sizing process enables businesses to fully understand their cloud environment and usage. This is especially true with regular analysis, allowing the organization to evolve with shifting priorities.

2. Utilize automation and real-time insights

Traditional methods of deploying cloud workloads require manual processes. This exhausts an IT team's time and creates opportunities for errors. Introducing automation increases the speed, security, and cost-efficiency of various tasks, including autoscaling. This occurs when a tool monitors and adjusts cloud usage to automatically remove or increase compute resources as needed.

Additionally, organizations can take a proactive approach by using cloud management services with real-time insights into usage, costs, and performance. These tools analyze vast amounts of data from cloud operations to provide insights into performance, cost trends, and resource utilization. Predictive analytics can forecast future cloud needs, enabling proactive capacity planning and budgeting. Detailed reporting features allow organizations to track key metrics and KPIs, providing a clear understanding of their cloud environment's health and performance in real-time.

3. Move to a serverless architecture

Moving to a serverless architecture also reduces costs by eliminating the need to manage and pay for always-on servers. In a serverless environment, you only pay for the exact compute resources used during the execution of your code. This approach is particularly beneficial for applications with variable workloads, as it automatically scales based on demand, ensuring that you only incur costs for what you use.

4. Create a cloud cost-aware culture

Finally, the role of culture cannot be underestimated. It is crucial to foster a culture of cloud cost awareness. From the top down, teams should be encouraged to continuously monitor and analyze their own cloud usage patterns. This way, those most familiar with a project's needs and processes can determine what can be streamlined with minimal ripple effects.

Companies that ingrain this into their organization may also consider creating a Cloud Cost Optimization Officer role if they don't already have one. This individual would lead efforts related to analyzing and strategizing cloud usage. Because they would have an overarching view of all cloud usage throughout the company, they would be able to spot opportunities for optimization that others may not have visibility into.

Looking ahead

These are all strategies IT leaders can and should implement today. It is also vital to keep an eye on the future to avoid falling behind. Cloud costs will continue to rise, particularly as cloud adoption deepens and businesses leverage more advanced and specialist cloud services. That doesn't necessarily mean that the cloud will become less cost-effective.

As cloud technologies become more widespread and mature, more cost-management tools and strategies will emerge, offering even more opportunities for organizations to optimize their spending more effectively. For example, artificial intelligence can play a crucial role in analyzing, forecasting, and scaling cloud usage. This can enable greater fine-tuning in automation and, ultimately, lowered costs.

Lastly, the pricing structures offered by various providers will continue to shift based on customers' priorities. There is already a trend toward increasingly granular pricing models. As providers cater to their clients' industry-specific needs and sustainability goals, new and increasingly competitive pricing models may emerge for enterprises to take advantage of and further reduce their cloud spend.

Mayank Bhargava is VP Consulting Services and Cloud Modernization Practice Leader at CGI

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4 Strategies to Optimize Cloud Investments and Maximize Value

Mayank Bhargava
VP Consulting Services and Cloud Modernization Practice Leader
CGI

As companies scale their cloud strategies, IT and finance leaders are looking to maximize both operation efficiency and return on investment. On their digital transformation journey, companies are migrating more workloads to the cloud, which can incur higher costs during the process due to the higher volume of cloud resources needed. However, it is also an opportunity to create more agile, resilient systems that will lower costs in the long term while increasing its business value.

Additionally, many organizations are increasing the number of advanced cloud-based services. This includes the addition of artificial intelligence, machine learning, data analytics, and similar technologies that demand more resources and have higher associated costs.

Still, when managed effectively, cloud and even multi-cloud strategies can offer significant savings compared to on-premise. However, organizations must be mindful of the challenges that can arise when embracing cloud and multi-cloud strategies, as unexpected costs can balloon quickly.

Organizations can employ several strategies to mitigate rising cloud costs. Implementing a robust cloud governance framework that includes ongoing cost optimization practices is key. Here are four critical components of a cloud governance framework that can help keep cloud costs under control.

1. Right-sizing resources

The first step is to right-size resources by matching the type and size of instances to the needs of the workload. In this process, tech leaders will examine the performance of the company's cloud instances, as well as analyze its cloud usage patterns and needs. By accumulating this data, the organization can determine if unused or underutilized services can be eliminated.

In addition to pure cost cutting, the right-sizing process enables businesses to fully understand their cloud environment and usage. This is especially true with regular analysis, allowing the organization to evolve with shifting priorities.

2. Utilize automation and real-time insights

Traditional methods of deploying cloud workloads require manual processes. This exhausts an IT team's time and creates opportunities for errors. Introducing automation increases the speed, security, and cost-efficiency of various tasks, including autoscaling. This occurs when a tool monitors and adjusts cloud usage to automatically remove or increase compute resources as needed.

Additionally, organizations can take a proactive approach by using cloud management services with real-time insights into usage, costs, and performance. These tools analyze vast amounts of data from cloud operations to provide insights into performance, cost trends, and resource utilization. Predictive analytics can forecast future cloud needs, enabling proactive capacity planning and budgeting. Detailed reporting features allow organizations to track key metrics and KPIs, providing a clear understanding of their cloud environment's health and performance in real-time.

3. Move to a serverless architecture

Moving to a serverless architecture also reduces costs by eliminating the need to manage and pay for always-on servers. In a serverless environment, you only pay for the exact compute resources used during the execution of your code. This approach is particularly beneficial for applications with variable workloads, as it automatically scales based on demand, ensuring that you only incur costs for what you use.

4. Create a cloud cost-aware culture

Finally, the role of culture cannot be underestimated. It is crucial to foster a culture of cloud cost awareness. From the top down, teams should be encouraged to continuously monitor and analyze their own cloud usage patterns. This way, those most familiar with a project's needs and processes can determine what can be streamlined with minimal ripple effects.

Companies that ingrain this into their organization may also consider creating a Cloud Cost Optimization Officer role if they don't already have one. This individual would lead efforts related to analyzing and strategizing cloud usage. Because they would have an overarching view of all cloud usage throughout the company, they would be able to spot opportunities for optimization that others may not have visibility into.

Looking ahead

These are all strategies IT leaders can and should implement today. It is also vital to keep an eye on the future to avoid falling behind. Cloud costs will continue to rise, particularly as cloud adoption deepens and businesses leverage more advanced and specialist cloud services. That doesn't necessarily mean that the cloud will become less cost-effective.

As cloud technologies become more widespread and mature, more cost-management tools and strategies will emerge, offering even more opportunities for organizations to optimize their spending more effectively. For example, artificial intelligence can play a crucial role in analyzing, forecasting, and scaling cloud usage. This can enable greater fine-tuning in automation and, ultimately, lowered costs.

Lastly, the pricing structures offered by various providers will continue to shift based on customers' priorities. There is already a trend toward increasingly granular pricing models. As providers cater to their clients' industry-specific needs and sustainability goals, new and increasingly competitive pricing models may emerge for enterprises to take advantage of and further reduce their cloud spend.

Mayank Bhargava is VP Consulting Services and Cloud Modernization Practice Leader at CGI

Hot Topics

The Latest

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...