In the face of ongoing economic uncertainty, managing cloud costs has become a paramount concern for organizations in 2023.
Although investment in cloud computing has continued its upward trajectory, tech leaders are now proactively seeking avenues to reign in expenses. To achieve this, numerous CIOs are forming internal teams and embracing innovative tools that enable cost control, fostering a proactive approach to financial management in the realm of cloud computing.
As organizations and business leaders continue to think through ways they can reduce cloud spend, many are turning to tools like predictive analytics and artificial intelligence to empower their organizations to enhance monitoring and control of cloud spending.
To understand more about the challenges and optimal responses, Digital Journal caught up with Eric Madariaga, a senior executive at CData, a real-time data connectivity company. Madariaga has a unique point of view on how AI, in particular, can help manage cloud spending.
Digital Journal: What types of AI-based technology can help manage cloud spending?
Eric Madariaga: The AI-based technologies that manage cloud spending are doing so in many of the same ways that IT teams are using manually today. Teams have to monitor costs, usage, and resource allocation in order to effectively manage their cloud spending. By adopting AI and ML technologies to understand cost optimization and usage analytics, teams can analyze historical data and the AI can make recommendations on where to optimize spending and allocate budget. A well-trained AI bot can even make predictions on when usage will increase or decrease based on certain factors, and allocate resources based on those predictions to minimize expensive uptimes and ultimately reduce cloud spending. Effective AI-based technologies will help organizations optimize their cloud spending by providing insights and recommendations that are difficult to achieve through historically manual processes.
DJ: Why is this something organizations should be looking into?
Madariaga: The cloud isn’t going anywhere, and teams are beginning to understand the need to pause and investigate the best ways to manage cloud spending. As SaaS technologies have become more prevalent in recent years, many organizations have embraced the usage of multiple applications to solve or streamline many different business challenges. This has led to overspending on numerous tools across every department – a trend that cannot continue without checks and balances. Why do we need this tool? Is it providing value that our other tools are not? Do we know if other departments or business units are already using a similar tool we can adopt? Etc.
Beyond app sprawl, the cloud is also creating data proliferation – high volumes of data are streaming into organizations, and the cost involved with storing, organizing, securing, and sharing that data is increasing commensurately.
By incorporating AI into their cloud management strategy, organizations open the doors for optimized costs and efficiency. Predictive analytics will enable organizations to understand where their budget is going and how that will look in the future should they continue down their current path.
DJ: Who are the key stakeholders in developing a strategy for implementing AI to manage cloud spending and control costs?
Madariaga: The key stakeholders when it comes to implementing AI to manage cloud spending and control costs are primarily IT management and finance. IT teams are responsible for implementing and maintaining the AI-based technologies and helping to find meaning from the results of those tools. Finance is involved as the final stop when it comes to paying for cloud resources, controlling what portion of the organization’s budget goes into both the cloud resources and the AI technology used to help manage the cloud.
Secondary stakeholders include engineers who may be tasked with building and/or training an AI and cloud architects who are responsible for the cloud architecture and associated costs. It’s important for an organization to include all these stakeholders in the planning process to ensure that the implementation of AI-based technologies meets the needs of the organization and aligns with its goals and objectives.
DJ: How must the market for AI-based cloud spending management and analytics further develop?
Madariaga: Like any AI-based technology, AI-based cloud spending management and analytics tools will see increased adoption, enhanced capabilities, integration with other technologies, and expansion of the market and competition.
Increased adoption will give these AI technologies larger datasets to work with and learn from. Enhanced capabilities are almost a given expectation for any technology, as organizations want to see their technologies grow with them, meeting their new needs and initiatives like they did when originally adopted. AI-based technologies will need to integrate with other technologies, like cloud security solutions, to ensure a comprehensive view of the organization’s cloud environment.
In order to succeed, AI-based cloud management solutions need to expand to serve smaller organizations by increasing affordability and accessibility. One thing to keep an eye out for is a likely increase in competition among vendors. This competition may lead to more innovation and advancement in the technologies, which helps these technologies meet the needs of more organizations.
DJ: Why is it important for organizations to start considering the use of AI tech for cloud spending management NOW?
Madariaga: Cloud computing and storage are not likely to go away any time soon. The faster organizations can get a handle on their cloud spending, the more money they will save in the long run. AI-based technologies will serve to accelerate better cloud management, which will free up resources and allow organizations to focus on their core business needs, investing in those teams and departments that ensure continued success for the organization.
