Want maximum value from FinOps in the cloud? – Capgemini
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Choose a partner with intimate knowledge of your industry and first-hand experience of defining its future.
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Discover our portfolio – constantly evolving to keep pace with the ever-changing needs of our clients.
Explore our brands
Explore our technology partners
Become part of a diverse collective of free-thinkers, entrepreneurs and experts – and help us to make a difference.
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See our latest news, and stories from across the business, and explore our archives.
We are a global leader in partnering with companies to transform and manage their business by harnessing the power of technology.
Cloud
Management team
Artificial intelligence
Across the financial services industry, the benefits of cloud adoption have been huge and are incontrovertible – including speed, agility, and scalability. But as usage has increased, so too have issues related to understanding and managing costs. In response, adoption of cloud FinOps is essential for organizations that want to maximize the value of their cloud investments, achieve financial accountability, align technology with business goals, and drive operational efficiency. It’s not just about cost savings – it’s about making informed decisions that lead to better business outcomes and sustained growth in the cloud.
Given recent and rapid advancements in artificial intelligence powered technologies, the addition of Gen AI technology to cloud FinOps programs can significantly improve FinOps practices – including more intelligent forecasting, resource optimization, anomaly detection, and enhanced decision-making.
FinOps in the cloud is still a relatively new practice area, and with the promise of Gen AI being even newer and less mature in many areas, where does an organization begin to explore the possibilities? Six use cases are quickly described where Gen AI might have the most immediate impact on cloud FinOps within your organization. As in all applications of Gen AI, data quality, explainability, and continuous learning will be essential to ensuring optimal implementation and understanding of return on investment.
Intelligent forecasting. Gen AI models can be used to analyze historical cloud usage, patterns, market trends, and business projections.
Anomaly detection. AI algorithms have the ability to help detect unusual spikes and unexpected changes in spend; they can also identify potential overspending, billing errors, and even potential corrective actions.
Automated cost optimization. Gen AI can provide intelligent recommendations; identify waste and underutilization; implement reserved instances or saving plans, or even architectural changes.
Workload placement and pricing model optimization. Gen AI can aid in the analysis of multiple cloud program attributes including pricing models, usage patterns, market benchmarks, most favorable cloud provider pricing, workload performance, and the strategic placement of workload.
Spend attribution and reporting. Large language model driven Gen AI can analyze unstructured data such as invoices and billing reports, categorize spend cost allocations, generate highly customized reports, and contribute to better visibility and accountability.
Communication and collaboration. Chatbot functionality powered by Gen AI can help FinOps teams, engineers, and finance departments communicate more effectively about cloud costs. Chatbots can provide real-time cost insights, answer questions, and help track optimization efforts.
Gen AI in action for Intelligent forecasting
To generate more accurate and flexible financial forecasts, taking cloud cost dynamics into account using Gen AI
Out-of-the-box Gen AI models specifically tailored for use in FinOps are not readily available today. However, a quick synopsis of how a financial services enterprise might leverage existing models and resources to kickstart efforts with Gen AI in FinOps follows.
GPT-3 (and variants)
CODEX ( or similar)
Anomaly detection models
Time-series forecasting models
Classification models
AWS, Azure, GCP
Of course, financial services institutions today are operating at differing maturity levels when it comes to both FinOps and Gen AI; therefore, every organization will have to shape its own approach to exploring and employing Gen AI based on current needs and objectives. A carefully constructed strategic roadmap is essential to success: consider the following pillars and supporting tenets for successfully implementing Gen AI for FinOps within your enterprise.
Build a strong foundation
Identify high-impact use cases
Execute iteratively
Insure continuous leadership and oversight
Maintain a keen focus on data
The Gen AI in FinOps journey described above should yield significant return on investment – but that is not to say that the effort will always be easy. Certainly, there are challenges to be addressed as a business moves ahead:
Generative AI has rapidly emerged as an important business technology and a transformative force across many industries, and Gen AI has the potential to significantly augment cloud FinOps processes. It also offers the possibility of more proactive, predictive, and prescriptive cost management. And as Gen AI technology and fluency continues to mature, we expect even more sophisticated and impactful applications to come within this domain.
Now is the time to embrace Gen AI as a key enabler of cloud FinOps at your organization. We hope you find this paper of interest and that it sparks dialogue across your teams. Capgemini’s Gen AI and FinOps experts would welcome opportunity for a conversation: please don’t hesitate to be in touch.
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This article was autogenerated from a news feed from CDO TIMES selected high quality news and research sources. There was no editorial review conducted beyond that by CDO TIMES staff. Need help with any of the topics in our articles? Schedule your free CDO TIMES Tech Navigator call today to stay ahead of the curve and gain insider advantages to propel your business!
Choose a partner with intimate knowledge of your industry and first-hand experience of defining its future.
Discover our portfolio – constantly evolving to keep pace with the ever-changing needs of our clients.
Become part of a diverse collective of free-thinkers, entrepreneurs and experts – and help us to make a difference.
See our latest news, and stories from across the business, and explore our archives.
We are a global leader in partnering with companies to transform and manage their business by harnessing the power of technology.
Explore our latest thought leadership, ideas, and insights on the issues that are shaping the future of business and society.
#1 in the world six consecutive times
Choose a partner with intimate knowledge of your industry and first-hand experience of defining its future.
Explore our brands
Explore our technology partners
Discover our portfolio – constantly evolving to keep pace with the ever-changing needs of our clients.
Explore our brands
Explore our technology partners
Become part of a diverse collective of free-thinkers, entrepreneurs and experts – and help us to make a difference.
Explore careers with our brands
See our latest news, and stories from across the business, and explore our archives.
We are a global leader in partnering with companies to transform and manage their business by harnessing the power of technology.
Cloud
Management team
Artificial intelligence
Across the financial services industry, the benefits of cloud adoption have been huge and are incontrovertible – including speed, agility, and scalability. But as usage has increased, so too have issues related to understanding and managing costs. In response, adoption of cloud FinOps is essential for organizations that want to maximize the value of their cloud investments, achieve financial accountability, align technology with business goals, and drive operational efficiency. It’s not just about cost savings – it’s about making informed decisions that lead to better business outcomes and sustained growth in the cloud.
Given recent and rapid advancements in artificial intelligence powered technologies, the addition of Gen AI technology to cloud FinOps programs can significantly improve FinOps practices – including more intelligent forecasting, resource optimization, anomaly detection, and enhanced decision-making.
FinOps in the cloud is still a relatively new practice area, and with the promise of Gen AI being even newer and less mature in many areas, where does an organization begin to explore the possibilities? Six use cases are quickly described where Gen AI might have the most immediate impact on cloud FinOps within your organization. As in all applications of Gen AI, data quality, explainability, and continuous learning will be essential to ensuring optimal implementation and understanding of return on investment.
Intelligent forecasting. Gen AI models can be used to analyze historical cloud usage, patterns, market trends, and business projections.
Anomaly detection. AI algorithms have the ability to help detect unusual spikes and unexpected changes in spend; they can also identify potential overspending, billing errors, and even potential corrective actions.
Automated cost optimization. Gen AI can provide intelligent recommendations; identify waste and underutilization; implement reserved instances or saving plans, or even architectural changes.
Workload placement and pricing model optimization. Gen AI can aid in the analysis of multiple cloud program attributes including pricing models, usage patterns, market benchmarks, most favorable cloud provider pricing, workload performance, and the strategic placement of workload.
Spend attribution and reporting. Large language model driven Gen AI can analyze unstructured data such as invoices and billing reports, categorize spend cost allocations, generate highly customized reports, and contribute to better visibility and accountability.
Communication and collaboration. Chatbot functionality powered by Gen AI can help FinOps teams, engineers, and finance departments communicate more effectively about cloud costs. Chatbots can provide real-time cost insights, answer questions, and help track optimization efforts.
Gen AI in action for Intelligent forecasting
To generate more accurate and flexible financial forecasts, taking cloud cost dynamics into account using Gen AI
Out-of-the-box Gen AI models specifically tailored for use in FinOps are not readily available today. However, a quick synopsis of how a financial services enterprise might leverage existing models and resources to kickstart efforts with Gen AI in FinOps follows.
GPT-3 (and variants)
CODEX ( or similar)
Anomaly detection models
Time-series forecasting models
Classification models
AWS, Azure, GCP
Of course, financial services institutions today are operating at differing maturity levels when it comes to both FinOps and Gen AI; therefore, every organization will have to shape its own approach to exploring and employing Gen AI based on current needs and objectives. A carefully constructed strategic roadmap is essential to success: consider the following pillars and supporting tenets for successfully implementing Gen AI for FinOps within your enterprise.
Build a strong foundation
Identify high-impact use cases
Execute iteratively
Insure continuous leadership and oversight
Maintain a keen focus on data
The Gen AI in FinOps journey described above should yield significant return on investment – but that is not to say that the effort will always be easy. Certainly, there are challenges to be addressed as a business moves ahead:
Generative AI has rapidly emerged as an important business technology and a transformative force across many industries, and Gen AI has the potential to significantly augment cloud FinOps processes. It also offers the possibility of more proactive, predictive, and prescriptive cost management. And as Gen AI technology and fluency continues to mature, we expect even more sophisticated and impactful applications to come within this domain.
Now is the time to embrace Gen AI as a key enabler of cloud FinOps at your organization. We hope you find this paper of interest and that it sparks dialogue across your teams. Capgemini’s Gen AI and FinOps experts would welcome opportunity for a conversation: please don’t hesitate to be in touch.
We are sorry, the form submission failed. Please try again.
We are sorry, the form submission failed. Please try again.
Our brands:
source
This article was autogenerated from a news feed from CDO TIMES selected high quality news and research sources. There was no editorial review conducted beyond that by CDO TIMES staff. Need help with any of the topics in our articles? Schedule your free CDO TIMES Tech Navigator call today to stay ahead of the curve and gain insider advantages to propel your business!
