Company: UIS
Filing Date: 2025-02-21
Form Type: 10-K
Source: 0000746838-25-000008
Chunk: 1

Company: UNISYS CORP
Filing Date: 2025-02-21
Form: 10-K
Item: Item 1
Chunk 1
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Multi-Cloud

Enterprises are increasingly adopting a multi-cloud strategy often leveraging a combination of public, private and SaaS clouds based on business and security needs, type of applications and cost considerations. Multi-cloud offers speed, flexibility and new technology adoption but introduces governance, workforce, financial and operational complexities. Navigating these challenges requires strong cloud governance, upskilled talent and dynamic cost controls. As artificial intelligence and digital initiatives continue to advance, businesses must focus on enabling rapid adoption of multi-cloud as a foundation to achieve these goals. Doing so requires deep expertise to manage and operate at scale, including expertise in more traditional IT infrastructure (e.g., data centers, servers and networking hardware).

Government and Enterprise Digitization 

Citizens increasingly expect a digital experience when engaging government services such as voter registration, tax filing and application processes for licenses, permits, visas or passports. Governments and law enforcement agencies are also seeking to automate processes, leverage data to make better decisions and improve transparency and data sharing. Similarly, customers, employees, suppliers and partners expect a digital experience when interacting with enterprises. Enterprise IT organizations must evaluate a myriad of technologies, software platforms and tools to manage and optimize their technology infrastructure and multi-cloud environments that support mission-critical workloads to meet these expectations.

5

Proliferation of Data

Data has always been a critical enabler of informed decision-making for enterprises. Today, vast amounts of data are being transferred and processed to generate actionable insights, often from disparate sources or stored within disparate environments. The explosive growth in data volume and variety, coupled with the compliance and regulatory environment and ethical and privacy standards, are driving enterprises to set up or modernize their data ecosystems. As a result, advanced paradigms for data engineering, data infrastructure, data lakes and data products combined with streaming and batch data capabilities are being used. Predictive analytics and traditional AI enable better informed decision-making and generative AI leverages previously unwieldy unstructured and semi-structured data, forcing complex enterprises to enhance their data strategies.

Artificial Intelligence

AI and automation continue to be interwoven to drive value. Organizations are leveraging AI to automate IT operations spanning security, development and networking to continually monitor, identify and proactively respond to performance issues.  Organizations are also using AI to automate repetitive tasks, facilitate enterprise access to knowledge and reduce operational costs. Customer and employee experience is being transformed through generative AI agents and chatbots, providing personalized and responsive interactions. Research and development costs and development timelines are being reduced through code generation technologies leveraging Large Language