Enterprise AI Depends on Better Cloud Migrations
It is often assumed that migrating to cloud computing is a purely technical step. But how can it help companies improve their business models, support business transformations and deliver value?
Any migration, including moving to the cloud, should be driven by business value. Typical reasons why organizations adopt the cloud include taking advantage of its ability to scale rapidly and drive efficiency while focusing on core priorities.
Crucially, cloud can be an enabler for innovation. In a recent EY study looking at how rethinking your cloud strategy can help you reshape your business, 35% of executives said cloud-native development will lead to improved innovation and a stronger ability to develop new revenue streams. By lowering the barriers to entry for new apps and automation, employees at different levels can contribute ideas that transform the business model through bottom-up innovation.
Rapid technological advances, including AI and Generative AI, are changing the way businesses operate. The ability to leverage these new technologies is critical to survive and thrive, and leveraging the cloud for these technologies is a necessity.
Cloud Leader for EY Global Delivery Services.
Together with AI, the cloud plays a critical role in enabling better insights and experiences through data and analytics by making it easier to use the latest technologies with elastic scalability.
Additionally, well-designed cloud solutions can provide cost savings compared to traditional on-premises solutions if designed and implemented optimally. Also, moving to an Opex model can help with cash flow and provide flexibility for organizations. Well-designed solutions that are designed to use the right mix of services and geographies can also help reduce a company’s overall carbon footprint, helping to achieve sustainability goals.
Security and data privacy are key requirements for all businesses. While the cloud itself doesn’t necessarily guarantee it, it’s important to understand that hyperscalers have invested billions in best practices including encryption, key vaulting, identity and access management, and threat detection. They also comply with many regulations including GDPR, HIPAA, and PCI-DSS. However, the onus still lies with the organization to implement all the best practices to ensure security.
Historically, business continuity, including disaster recovery, involved setting up alternate data centers with high availability. Today, the cloud makes it easier and less expensive to deploy applications using the “as-a-code” approach.
In the world of digital transformation, the cloud is the foundation. It should not be seen as just an infrastructure component, but as a replacement for all other technologies.
What role does cloud migration play in AI adoption by companies?
By migrating to the cloud, organizations can take advantage of advanced technologies such as artificial intelligence, machine learning, and big data analytics. In the survey, 84% of respondents said AI adoption would not have been possible without cloud migration. Cloud offers the opportunity to reimagine operations, create agile business models, and leverage AI.
However, the adoption of AI services in the cloud requires organizations to use the cloud more broadly and not just rely on the cloud for specific or isolated AI use cases.
For example, a universal approach to data, cloud, and AI can help businesses gain a bird’s-eye view of operations and customer behavior. Access to a larger, more diverse data set allows for more accurate and reliable analytics, which in turn improves AI outcomes. This continuous influx of real-time data into the cloud creates an ideal environment for evolving AI models. These models can adapt and learn as new data flows in, forming the foundation for an agile and intelligent business ecosystem.
We believe the cloud has the potential to democratize access to AI by breaking down silos and technical complexities, creating an accessible and collaborative environment where cross-functional teams can share ideas and innovate together.
How is AI changing cloud migration?
AI is completely transforming the end-to-end cloud migration and modernization lifecycles. Overall, we see that GenAI-infused tools, including the use of AI agents, help significantly improve productivity across the entire migration/modernization lifecycle. GenAI intervention is increasingly important when it comes to optimally executing large-scale migration programs at scale, helping to improve quality, consistency, and risk mitigation. Examples include the use of AI tools to support cloud migration risk and planning, scenario testing, cybersecurity in cloud operations, and costs.
Many companies believe their cloud migrations would have been beneficial, but were not implemented effectively
Businesses may face obstacles or challenges when it comes to cloud migration, particularly in highly regulated industries such as banking, capital markets, wealth and asset management, insurance, healthcare, public sector and government. This includes viewing cloud migration as purely an IT project; 50% of IT leaders surveyed told EY that their cloud strategy was part of their technology transformation efforts, while only 27% said the goal was business transformation.
Lack of management commitment, organizational buy-in, and stakeholder availability are also challenges. Only 16% of the companies we surveyed were considering using cloud to evaluate new business models.
Other challenges include lack of governance, skills and knowledge shortages, lack of organizational readiness, and lack of planning or budgeting.
How can organizations adapt and recalibrate after a suboptimal cloud migration to truly deliver value?
To achieve a successful migration, we advise companies to clearly define their cloud strategy and governance framework from the start. The process should be led by a Cloud Transformation Office in which all relevant stakeholders are represented. They should regularly refresh their business case for the cloud migration as needed and adjust as necessary to ensure that the value gap is minimized.
Secondly, if a value gap does arise, it is crucial that the specific reasons behind it are fully understood. This includes, for example, always revisiting and reflecting on the original business case, addressing cost overruns via FinOps best practices, validating the people strategy, including upskilling and creating new roles, and rethinking the overall IT procurement approach in the cloud world.
We provide an overview of the best cloud optimization services.
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