The adoption of cloud services is nearly ubiquitous as organizations, regardless of their size, rely on the cloud for its scalability, flexibility and cost-efficiency. That said, to make the most of their cloud investments and achieve a positive ROI, companies must focus on efficient resource management. This necessitates gaining comprehensive visibility into how cloud services are utilized within their operations.
To optimize cloud ROI, companies need to align their cloud resources with their specific business needs. Over-provisioning or under-provisioning resources can result in unnecessary costs or performance issues. Therefore, ensuring that cloud resources are optimally matched to the actual demands of the business is imperative.
Additionally, reducing unnecessary spending is a core element of cloud ROI. This involves identifying and eliminating inefficiencies, such as running idle virtual machines or leaving unused data storage, to maximize the cost-effectiveness and benefits of cloud services.
One way to achieve this is through a FinOps model using AI-powered software. By implementing FinOps practices, organizations can identify and reduce unnecessary cloud spending, align costs with business needs and achieve a more favorable ROI from their cloud services.
However, according to a recent study by Foundry and commissioned by Tangoe, enterprises activating a FinOps model using AI-powered software are 53% more likely to report an overall cost savings of greater than 20%. In contrast, companies who do not use AI average less than 10% in cost savings.
Incorporating AI-enabled tools into FinOps offers several notable advantages for companies. One of the primary benefits is the ease of program management, as highlighted by 50% of the surveyed organizations. AI can automate many aspects of financial operations, such as cost tracking, resource allocation and expense forecasting.
By leveraging AI, companies streamline these processes, making them more efficient and less labor-intensive. This not only reduces the administrative burden on finance and IT teams but also allows for real-time monitoring and adjustments, ensuring that cloud resources are optimally matched with business needs.
There are additional challenges that organizations face, too. More than half of the surveyed companies pointed to the difficulty of building the right processes and human support systems for FinOps. Integrating AI tools into existing workflows and ensuring they align with the organization's unique financial practices can be a complex endeavor. Moreover, change management is often necessary to ensure that employees are comfortable with these new technologies and are able to use them effectively.
Establishing the right processes and support systems is critical for the successful implementation of AI in FinOps, as it can help companies harness the full potential of these tools while mitigating the challenges associated with adoption and integration.
This then raises the question of how businesses can take advantage of AI in FinOps.
Tangoe's AI-powered Tangoe One Cloud solution, for example, empowers companies to implement effective FinOps strategies, offering a comprehensive cloud expense management solution covering IaaS, SaaS (News - Alert) and UCaaS. It provides benefits such as enhanced visibility into cloud expenses through extensive API integrations, AI-powered FinOps tools that expedite financial management workflows and the flexibility to reduce cloud infrastructure costs across major providers while customizing services to align with the needs of both IT and finance teams.
Tangoe's solution also extends cost optimization to mobile devices and telecom services when organizations are ready to apply FinOps principles beyond their cloud infrastructure.
“Business leaders need real-time dashboards that connect IT operations, finance and cloud financial management data in one platform, taking advantage of AI to deliver actionable insights,” said Parker.
Edited by Alex Passett