Cloud modernization and the promise of AI: A strategic imperative for 2024
diciembre 21, 2023 / Peter Altabef
Short on time? Read the key takeaways:
- The integration of AI across industries underscores the need for organizations to accelerate their data maturity and modernize cloud capabilities to stay competitively relevant.
- To balance potential budget constraints with AI integration, businesses should consider a range of cost-effective solutions to optimize resource management within cloud environments.
- Enhanced interoperability of existing and new AI technologies in cloud environments is key to efficiently handling AI-driven workloads, preventing data silos, and getting the most valuable insights from data analytics.
- Cloud modernization investments should prioritize frugal architecture principles, optimizing IT systems to maximize value when developing innovative AI-driven solutions.
In 2023, the technological landscape bore witness to an extraordinary narrative - the promise of profound disruption through generative artificial intelligence (AI). The seismic impact of this innovative technology has rippled across such diverse sectors as healthcare, finance, logistics, and manufacturing, and will only continue to expand.
As organizations rushed to meet the escalating demand for AI (which includes but is broader than generative AI) from internal stakeholders and external market pressures, data maturity emerged as an operational cornerstone from which to propel businesses into an AI-driven future or concede any competitive standing.
Subsequently, the question heard throughout corporate corridors is this – can organizations genuinely unlock the transformative potential of AI without embarking on or continuing the essential path of data modernization?
Balancing AI ambitions with budget realities
Throughout 2023, businesses began to invest substantially in AI capabilities as the reality of its revolutionary and transformative possibilities became evident.
However, the surge in awareness has not always corresponded with increased cloud, data, and development budgets. Many organizations struggled with integrating AI or bringing generative AI-enabled products and services to market while managing the unplanned budgetary expenditures that came with meeting the new demand. For some organizations, these unplanned expenditures necessitated quickly upgrading cloud capabilities for their private, public, or hybrid cloud environments.
To meet the strategic imperative of AI integration, cost optimization measures for cloud solutions, such as reserved instances, spot instances and serverless cloud computing, will help organizations make the most of their 2024 budgets. Doing so will also help them manage expenditures while minimizing budget overruns effectively.
Scaling cloud environments for AI integration
AI tools, each an amalgamation of technologies with unique frameworks, have introduced new complexities for the interoperability of existing cloud environments. Therefore, before organizations can even consider AI integration, they must first refine their data integration strategies to prioritize system interoperability.
Cloud environments rely on automation and orchestration tools to streamline processes and manage resources efficiently. Interoperability is vital for these tools to communicate and coordinate tasks effectively across applications, services, and infrastructure components.
AI-intensive workloads necessitate dynamic resource scaling to accommodate fluctuating demands. Here, too, interoperability is vital to ensuring that cloud infrastructure can effectively scale up or down as needed to support AI workloads without service disruptions. This affords organizations with modernized cloud infrastructures a distinct competitive advantage.
Big data accessibility and cloud modernization
Without interoperability, data can also become siloed within specific cloud services or applications, making it challenging to gain a holistic view of an organization's data. Modernized cloud environments streamline data accessibility and support the requisite computing power for big data analytics, especially those driven by AI and quantum computing.
Inadequate data visibility, whether through data silos, fragmentation or even redundancy, can hinder accurate data modeling. This, in turn, can adversely impact an organization’s ability to derive the most value from its data assets. Inefficient data analytics also prolongs “time-to-insight,” which prevents organizations from making timely decisions based on data-driven insights.
While organizations will benefit from AI’s ability to analyze large structured and unstructured data sets, to achieve the most value, they should invest in the dynamic scalability of modern cloud environments to accommodate the substantial volumes of data generated by AI-enabled solutions. The alternative is to risk costly performance bottlenecks and increased processing times for analytics workloads.
The business case for cloud modernization
For organizations to harness the full potential of AI’s transformational capabilities, cloud modernization will be a strategic necessity. As businesses enhance their data maturity through cloud modernization, they will keep pace with industry standards and increase the valuation of their cloud-based data assets. This will temper cloud computing constraints such as data silos and support the agile development of innovative AI-driven products and services in 2024.
Organizations fortified with improved data maturity will also best navigate the as-yet-unknown challenges and opportunities AI presents. That said, any investment in cloud modernization must be rooted in solid data governance principles and guided by the discipline of a “frugal architect” to optimize enterprise IT environments for AI integration.
Although pursuing data maturity through cloud modernization will inevitably present some challenges along the way, the rewards — heightened performance, cost optimization, competitive advantage, and boundless innovation — will justify the investment.
Unisys offers multi-cloud management, cloud observability, cloud migration and modernization, and financial analysis and optimization. For more details, learn more about Cloud Management solutions and watch this video showcasing how the cloud can unleash innovation, securely.
Download from Barriers to Breakthroughs: Unisys Cloud Insights Report 2023 to learn how data maturity and cloud modernization can help you benefit from increased agility and cost savings.
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