Managing the evolution of the cloud in the age of gen AI

Generative AI (gen AI) is revolutionizing cloud computing. Leading organizations worldwide are looking at ways to integrate gen AI into their cloud computing strategies to boost scalability, flexibility, productivity, and data analytics capabilities – all while cutting costs and time to market.

At Genpact, we look closely at every capability to see if there's an opportunity to improve the customer experience and business outcomes through applied AI. Our cloud capability is no different. Be it cloud migration, modernization, or operations, every aspect of the cloud journey can benefit from generative AI.

Let's consider a use case: a global company is struggling with high IT costs, a legacy code base, a lack of required talent, and a lack of agility. While moving to the cloud seems to be a good destination for this company, reaching it could be a challenge, especially with the talent crunch that has left IT systems with little to no documentation, zero test cases, and outdated versions of supporting systems. While the company could get more manpower to analyze the line by line, it would be time-consuming and costly.

This is where the company can bring in generative AI to help it perform code analysis, write test cases, and create documentation as well as convert its old versions of code to new compatible versions. This will enable faster cloud migration and help realize the benefits of cloud migration sooner than later. Additionally, it can implement robust security measures, train its staff, and regularly monitor its cloud spending using financial operations (FinOps). The possible impact: the company is able to innovate faster, improve customer satisfaction, and increase its market share.

Here are a couple of additional ways in which this company can use gen AI to manage the evolution of the cloud:

• Automated cloud migration planning: Generative AI can analyze an organization's existing IT infrastructure and workloads to create an optimized cloud migration plan. By evaluating workload patterns, security needs, and cost considerations, AI can recommend the most suitable cloud service providers and configurations. This can help ensure a smooth and efficient migration process
• Cost management and optimization: Generative AI can assist in managing and optimizing cloud costs by analyzing usage patterns and identifying cost-saving opportunities. For example, AI can recommend rightsizing of resources, identify underutilized instances, and suggest more cost-effective storage solutions. This helps organizations reduce their cloud expenditure while maintaining performance and scalability

However, gen AI is not a silver bullet for all your cloud computing woes. Here are some tips to avoid common pitfalls:

1. Don't rush the migration process: While the use of gen AI can accelerate migration to the cloud, take the time to plan and execute the migration carefully to avoid disruptions and ensure a smooth transition
2. Invest in security: Using gen AI can expose you to data breaches, which can have devastating legal and reputational consequences. Invest in robust security measures to protect your data
3. Monitor costs: With the hype around gen AI, companies risk overinvesting in applications without considering the ROI. In addition to regularly monitoring and optimizing your cloud spending to avoid cost overruns, keep an eye on your gen AI spend as well
4. Train your staff: Even as you invest in gen AI applications, ensure your team has the necessary skills to manage and leverage the technology effectively

In conclusion, using gen AI strategically to improve cloud operations is crucial as the cloud evolves. To get the most out of your gen AI applications for the cloud, focus on using gen AI responsibly and after a careful evaluation of whether the solution is the right fit for your unique needs.