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Cloud Predictions 2024: The Future of AI, Hyperscalers, and Cloud Data Warehouses

As we look ahead to the future of how companies migrate to the cloud, many trends and projections are set to redefine this rapidly evolving domain. In this article, I will look at three trends in particular and how organizations can prepare to stay ahead of these trends that will shape their move to the cloud in the years to come.

1. The reliance on AI analytics and generative AI will continue to grow.

The integration of AI analytics and generative AI is projected to persist at an accelerated pace. This growth is driven by the increasing volumes of data, the advancement of AI and cognitive technologies, and the demand for intelligent business processes. For example, AI is making a significant impact in various industries:

• In healthcare, AI is being used to predict patient outcomes and personalize treatment plans.

• In finance, it plays a crucial role in fraud detection and risk management.

• As regulatory bodies strengthen their requirements in the financial services industry, the cloud and use of AI will play a critical role in satisfying these requirements.

 These few examples illustrate the wide-ranging impact and potential of AI, and this will have a massive impact on migrating cloud data, allowing companies to streamline processes and become more efficient.

This rapid proliferation and adoption will prompt organizations to continually optimize their workforce. To prepare for these transformations, businesses should start by identifying key areas that would benefit from AI, such as repetitive and tedious tasks. This will free up time for employees to focus on higher-value tasks.

Businesses should also invest in educating their workforce about AI, emphasizing that it is not a threat but a tool that will enhance their productivity. Upgrading the infrastructure to meet the data demands of AI applications is another crucial step, as is setting out a clear AI strategy, including a rollout plan for key stakeholders.

2. Hyperscalers will embed more AI into their offerings.

As the trend above continues, cloud hyperscalers are significantly monetizing their AI investments. For example, here are some of the ways that the major players are investing in AI:

• Microsoft leverages AI to enhance the capabilities of its cloud services.

Snowflake employs AI to optimize data processing and analytics.

Databricks utilizes AI to streamline data management and foster insights, catering to businesses' growing analytical needs.

• Google provides AI-driven real-time analytics to support businesses in converting data into valuable insights.

To prepare for the continued investment in AI by cloud hyperscalers, businesses—particularly those focused on cloud migration—might encounter challenges, such as data security, compliance risks, uncertain costs of cloud migration and AI transparency.

These challenges, however, can be effectively managed and even turned into opportunities for growth and innovation. For example, investing in robust security measures can help businesses protect their data and comply with relevant regulations. Before adopting AI solutions from cloud hyperscalers, businesses should ask about security measures, AI transparency, potential costs involved and the availability and integration of automation tools.

In addition to these strategies, businesses can also invest in automation tooling. Automation tools can streamline various processes, reduce manual errors and increase efficiency. For instance, automation can help in managing and organizing data, a crucial aspect of AI readiness. It can also assist in monitoring cloud costs and usage, helping businesses stay within their budget. Furthermore, automation tools can be used to regularly check compliance and security measures, ensuring that businesses meet the necessary standards.

3. Hyperscalers will invest heavily in their cloud data warehouses.

The increasing demand for cloud services and the migration of more companies to the cloud are also driving cloud hyperscalers to invest heavily in their cloud data warehouses. The same industry leaders mentioned above, for instance, are making significant investments to offer unique features and capabilities, such as:

• Microsoft provides a centralized repository for structured and semi-structured data, ideal for reporting and analysis.

• Snowflake offers security, governance and data protection.

Databricks simplifies data management and supports a hybrid data lakehouse approach.

Google BigQuery offers an architecture for real-time analytics.

This trend is driven by the need for businesses to leverage the benefits of cloud technology, such as scalability, flexibility and cost-effectiveness. However, this move also presents challenges, such as data security and privacy concerns, integration issues and the need for technical expertise.

When adopting these solutions, businesses will need to work closely with hyperscalers to ensure the safety of their data and ask in what ways each vendor can streamline the process and meet regulatory requirements.

Conclusion

The future of cloud technology is set to be shaped by the continued adoption and advancement of AI, the monetization of AI investments by hyperscalers and the ongoing investment in cloud data warehouses. These trends underscore the increasing importance of AI in the cloud space and the significant role it will play in shaping the future of business operations.

Businesses, particularly those focused on cloud migration, should consider several steps to stay ahead of these trends:

1. Identify their specific business needs and assess their AI and cloud readiness, ensuring they have a well-organized data-collection process.

2. Budget for AI and data warehousing, considering costs such as data acquisition, model development, infrastructure, talent and compliance. Aligning initiatives with business goals and tracking financial returns is crucial.

3. Invest in training their teams on AI-related skills, promoting hands-on experience with AI systems.

4. They should strive for transparency and trust, disclosing their criteria for AI transparency to customers and end users.

In short, to prepare now for these developments, businesses should be working with their teams to understand if they have the proper skill sets and working with vendors to determine if they have a full understanding of what it will take to keep their data secure and to meet regulatory compliance in this new cloud future.

Next Pathway is the Automated Cloud Migration company. Powered by the SHIFT Cloud, Next Pathway automates the end-to-end challenges companies experience when migrating applications to the cloud. For more information, please visit nextpathway.com.

Read the full article on Forbes here: Cloud Predictions 2024 - The Future of AI, Hyperscalers, and Cloud Data Warehouses

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