Editorial
In “Designed for Digital,” authors Jeanne W. Ross, Cynthia M. Beath and Martin Mocker highlight how digital technologies — analytics, IoT and cloud computing — are driving ubiquitous data, limitless connectivity and vast processing power, fueling today’s AI solutions.
At Dresner Advisory Services, our research underscores that reliability, access and availability rank as the top priorities for organizations leveraging cloud solutions to deliver on the AI future. Closely following in importance are scalability and ease of use, with factors like administration and implementation time rounding out critical considerations.
In a recent Rackspace survey of over 1,400 IT decision-makers, a significant shift in cloud strategies was clear. Organizations are increasingly moving away from single-cloud approaches, favoring flexible hybrid cloud environments that better align with dynamic business requirements. Notably, 90% of respondents plan to make substantial changes to their cloud strategies within the next two years, signaling a continued drive toward business agility and faster innovation around AI and generative AI solutions.
Hybrid Cloud as a Way Forward
The Rackspace survey found that 48% of IT decision-makers view hybrid cloud deployment as the way forward for their operations over the next 12-24 months.
This is no surprise, as there is a growing emphasis on flexibility, adaptability and resilience as organizations navigate evolving technological demands, particularly around AI integration. AI-driven capabilities, such as enhanced operational efficiency and advanced data analysis, are reshaping priorities and driving go-forward cloud strategy.
At the same time, as the full costs of cloud computing become clearer, two-thirds of respondents report that their organizations have considered repatriating at least some workloads from public clouds to private clouds or on-premises infrastructure. This trend highlights a reevaluation of cloud strategies as businesses seek optimal cost structures and operational efficiency. At Dresner, we’re also seeing movement between cloud database vendors for the same reasons.
Related Article: Managing Cloud Spend in the GenAI Age
What’s Driving These Cloud Strategy Changes?
The Rackspace survey further identified the primary drivers for these changes to cloud strategy.
- 50% of respondents cited data security and compliance requirements as leading factors
- 48% pointed to the need for better integration with existing systems
- 44% named the pursuit of cost savings
Together, these findings paint a picture of an IT landscape where hybrid solutions and strategic repatriation are shaping the next phase of cloud adoption.
At Dresner, we've observed that cloud-based solution providers often lack the level of control and security provided by on-premises systems — an important concern for organizations managing sensitive data or operating in regulated industries. Despite these challenges, the flexibility and scalability of cloud business intelligence (BI) solutions remain powerful advantages. They enable businesses to adapt swiftly to changing market conditions and scale operations without the need for significant upfront infrastructure investment.
What Are Vanguard Organizations Doing?
The Rackspace Survey highlighted the strategies of "cloud leaders," organizations that align their cloud platform choices with overarching business goals. These leaders are at the forefront of AI adoption, with 37% using AI-driven cloud optimization to refine their cloud strategies, achieving greater operational efficiency and accelerated innovation. IT leaders are increasingly embracing workload-by-workload analysis to determine the optimal hosting environment for their workloads.
“As AI continues to drive rapid advancements, IT leaders are reevaluating their approach to workload management. Instead of updating existing infrastructure, they are designing entirely new cloud strategies to meet evolving demands,” said Srini Koushik, president of AI, technology and sustainability at Rackspace Technology. This shift underscores the importance of aligning AI and cloud strategies, with 84% of respondents taking steps to integrate the two.
The business outcomes driving this integration are clear: 49% of survey participants aim to enhance operational efficiency, while 45% leverage AI to improve data analytics insights.
At Dresner, our research supports this trend, finding that cloud BI is at near-record levels of importance, with 66% of organizations rating it as critical or particularly important — a figure that rises to 80% for enterprises with over 10,000 employees. Furthermore, 75% of organizations already have at least 40% of their BI and analytics solutions in the cloud. This growing reliance on cloud-based tools reflects a shift toward prioritizing scalability, flexibility and seamless integration of advanced technologies like AI to enhance business operations.
Despite the opportunities, talent and resource shortages remain significant challenges, potentially limiting the ability of organizations to fully realize their AI and cloud goals. This scarcity of expertise is further pushing organizations to adopt cloud solutions to support their AI initiatives.
However, data security and compliance are top priorities, with 96% of surveyed organizations establishing robust procedures and policies to safeguard data privacy in cloud environments. These efforts reflect a broader need to balance innovation with accountability in an era of rapid technological transformation.
Related Article: What Biden’s New AI Policies Mean for Tech and Innovation
Flexibility and Innovation Will Define Cloud Success
The findings of the Rackspace’s survey paint a clear picture of a rapidly evolving cloud landscape, where AI and hybrid strategies are at the forefront. Organizations are rethinking their cloud approaches, driven by the dual imperatives of flexibility and innovation.
AI is no longer a future ambition but a present-day driver, pushing IT leaders to refine cloud strategies and integrate advanced capabilities that enhance operational efficiency and data insights.
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However, this transformation is not without its challenges. Talent shortages, rising costs and the complexities of balancing security and compliance with scalability underscore the need for thoughtful cloud planning. The rise of hybrid cloud environments and workload-specific hosting decisions reflect a maturing approach to cloud adoption, where adaptability and strategic alignment are key.
As businesses continue to navigate this dynamic landscape, the leaders will be those who embrace AI as a central pillar of their cloud strategies, prioritize security and compliance and leverage hybrid solutions to achieve resilience and efficiency. This ongoing shift signals a future where cloud strategies are not static but evolve to meet the complex demands of a data-driven, AI-enabled world.
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