Unisys New is an Enterprise / IT company.
Unisys New actively redefines its internal operations through a comprehensive digital transformation. This involves embedding artificial intelligence across critical service delivery workflows and modernizing its core cloud and infrastructure platforms. The company specifically transforms its application development processes and strengthens its internal cybersecurity posture.
This significant shift creates dependencies on robust data pipelines, secure cloud environments, and reliable AI models, introducing specific operational risks. Breakdowns can occur in data integrity, system integration, and automated decision-making processes. This page analyzes Unisys New's key digital transformation initiatives, identifies where execution becomes difficult, and highlights opportunities for sellers.
Unisys New Snapshot
Headquarters: Blue Bell, Pennsylvania, U.S.
Number of employees: 10,000+ employees
Public or private: Public
Business model: B2B
Website: http://www.unisys.com
Unisys New ICP and Buying Roles
Unisys New sells to large enterprises managing complex IT environments. They target organizations requiring secure, integrated solutions across diverse technology landscapes.
Who drives buying decisions
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Chief Information Officer (CIO) → Oversees overall IT strategy and technology investments.
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Chief Technology Officer (CTO) → Leads technology vision and directs product development.
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Chief Information Security Officer (CISO) → Manages cybersecurity risks and enforces security policies.
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Head of Digital Workplace Services → Drives initiatives for employee productivity and IT support.
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Head of Cloud Operations → Manages cloud infrastructure, migration, and cost optimization.
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Head of Application Development → Directs software engineering and application modernization efforts.
Key Digital Transformation Initiatives at Unisys New (At a Glance)
- Automating field service management with AI-powered routing and scheduling systems.
- Integrating generative AI into software development for code generation and testing.
- Migrating internal infrastructure and client workloads to hybrid cloud environments.
- Enhancing internal cybersecurity with zero-trust and quantum-resilient models.
- Developing internal data platforms for operational analytics using machine learning.
Where Unisys New’s Digital Transformation Creates Sales Opportunities
| Vendor Type | Where to Sell (DT Initiative + Challenge) | Buyer / Owner | Solution Approach |
|---|---|---|---|
| Field Service Automation Platforms | AI-driven field service automation: automated ticket routing creates incorrect technician assignments. | Head of Digital Workplace Services, Head of Field Operations | Validate AI assignment logic against service level agreement requirements. |
| AI-driven field service automation: appointment scheduling conflicts with technician availability. | Head of Digital Workplace Services, Operations Manager | Standardize scheduling rules across multiple technician calendars. | |
| AI-driven field service automation: service ticket data misses critical customer context. | Head of Field Operations, VP Customer Experience | Capture complete customer context from disparate systems for service tickets. | |
| AI Development & Governance Platforms | Internal AI application development: AI-generated code does not meet internal quality standards. | VP of Application Development, Head of Software Engineering | Validate AI-generated code for syntax errors and architectural compliance. |
| Internal AI application development: AI model outputs produce biased results during testing. | CTO, Head of AI/ML Engineering | Detect bias in AI model predictions before deployment into production. | |
| Internal AI application development: generative AI lacks proper version control within development pipelines. | Head of Software Engineering, Director of DevOps | Route AI model versions through automated change management workflows. | |
| Hybrid Cloud Management Platforms | Cloud and infrastructure modernization: application performance degrades after cloud migration. | Head of Cloud Operations, Director of Infrastructure | Monitor application performance metrics across hybrid cloud environments. |
| Cloud and infrastructure modernization: data transfer failures occur during cloud database migration. | Head of Cloud Operations, Director of Database Administration | Validate data integrity between source and target databases during migration. | |
| Cloud and infrastructure modernization: hybrid cloud costs exceed allocated budget thresholds. | SVP and GM, Cloud, Applications & Infrastructure Solutions, Head of FinOps | Detect cost anomalies and enforce spending limits across multi-cloud resources. | |
| Cybersecurity Orchestration Platforms | Advanced cybersecurity operations: reactive security tools delay incident response workflows. | CISO, Head of Security Operations | Route security alerts to the appropriate incident response teams automatically. |
| Advanced cybersecurity operations: security policy enforcement varies across cloud and on-premises environments. | CISO, Director of Compliance | Standardize security policies across all internal infrastructure components. | |
| Advanced cybersecurity operations: threat detection systems produce too many false positives. | Head of Security Operations, Security Analyst | Filter security alerts to prioritize actual threats requiring investigation. | |
| Data Quality & Governance Platforms | Internal data analytics platform: operational data contains inconsistent or missing values. | Head of Data & Analytics, Chief Data Officer | Validate incoming data streams for completeness and accuracy before ingestion. |
| Internal data analytics platform: data silos prevent unified reporting across business units. | Head of Data & Analytics, Director of Enterprise Architecture | Standardize data models across disparate internal data sources for consolidation. | |
| Internal data analytics platform: analytics outputs fail to integrate with business intelligence dashboards. | Head of Data & Analytics, Business Intelligence Lead | Route processed data into visualization tools without manual intervention. |
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What makes this Unisys New’s digital transformation unique
Unisys New’s transformation heavily prioritizes integrated AI across its service delivery and internal development functions. This approach places significant dependency on precise AI model performance and robust data quality to prevent operational disruptions. The company’s focus on embedding security directly into its internal solutions, rather than as an afterthought, creates a distinct emphasis on zero-trust architectures and quantum-resilient models. This combined strategy for AI, cloud, and security integration presents a more complex operational landscape compared to companies with isolated transformation efforts.
Unisys New’s Digital Transformation: Operational Breakdown
DT Initiative 1: AI-Driven Field Service Automation
What the company is doing
Unisys New expands its partnership with Salesforce to integrate Agentforce 360 into its Digital Workplace Solutions Field Services. This initiative automates the routing of over 1 million service tickets annually. It also auto-schedules 70% of monthly field service appointments without human intervention.
Who owns this
- SVP and GM, Digital Workplace Solutions
- Head of Field Operations
- Operations Manager
Where It Fails
- Automated ticket routing generates incorrect technician assignments.
- AI-powered scheduling conflicts with real-time technician availability.
- Service ticket data misses critical customer context before dispatch.
- Automated updates to field service applications do not propagate to mobile devices.
Talk track
Noticed Unisys New scales AI-driven field service workflows. Been looking at how some teams isolate high-priority tickets for human review instead of routing everything automatically, can share what’s working if useful.
DT Initiative 2: Internal AI Application Development
What the company is doing
Unisys New invests significantly in AI, operating 135 AI projects across the company. Its application development teams utilize generative AI for code generation. This integration aims to increase developer productivity by 50%.
Who owns this
- Chief Technology Officer (CTO)
- VP of Application Development
- Head of AI/ML Engineering
Where It Fails
- AI-generated code introduces security vulnerabilities during development.
- Generative AI models produce code that fails internal compliance checks.
- AI model retraining cycles cause delays in feature release schedules.
- AI-generated documentation does not reflect actual system behavior.
Talk track
Looks like Unisys New integrates generative AI into application development. Been seeing teams validate AI-generated code for security flaws before integration into main branches, happy to share what we’re seeing.
DT Initiative 3: Cloud and Infrastructure Modernization
What the company is doing
Unisys New focuses on evolving its cloud capabilities, including hybrid cloud and cloud optimization. This involves migrating internal systems and client applications to hybrid cloud environments. They specifically roadmap efforts to deploy ClearPath Forward in these new environments.
Who owns this
- SVP and GM, Cloud, Applications & Infrastructure Solutions
- Head of Cloud Operations
- Director of Infrastructure
Where It Fails
- Application dependencies break during migration to hybrid cloud platforms.
- Data transfer processes fail to complete during legacy system cloud transition.
- Security configurations do not align between on-premises and cloud environments.
- Hybrid cloud resource provisioning creates unexpected cost overruns.
Talk track
Saw Unisys New shifts core systems to hybrid cloud environments. Been looking at how some enterprises prevent application performance degradation after cloud migration, can share what’s working if useful.
DT Initiative 4: Advanced Cybersecurity Operations
What the company is doing
Unisys New prioritizes cybersecurity by internally deploying and validating its own cyber solutions. The company continuously updates its Stealth platform to include advanced visualization and dashboard tools. It also implements zero-trust and quantum-resilient security models.
Who owns this
- Chief Information Security Officer (CISO)
- Head of Security Operations
- Director of Compliance
Where It Fails
- Security event correlation fails to detect advanced persistent threats.
- Zero-trust policies block legitimate user access to internal applications.
- Vulnerability scanning tools produce excessive false positive alerts.
- Incident response workflows do not propagate across all security systems.
Talk track
Noticed Unisys New strengthens internal cybersecurity operations. Been seeing teams streamline security event correlation to reduce alert fatigue in their security operations centers, happy to share what we’re seeing.
DT Initiative 5: Internal Data Analytics Platform Development
What the company is doing
Unisys New builds and utilizes internal data analytics platforms to transform raw operational data into actionable insights. This involves employing statistical models, machine learning, and AI technologies. The company aims to overcome challenges like poor data quality and data silos.
Who owns this
- Head of Data & Analytics
- Chief Data Officer
- Business Intelligence Lead
Where It Fails
- Raw operational data contains formatting inconsistencies before analysis.
- Data ingestion pipelines create duplicate records in analytics platforms.
- Machine learning models generate inaccurate predictions for business forecasting.
- Analytics dashboards display stale information due to data refresh failures.
Talk track
Seems like Unisys New develops internal data analytics platforms. Been looking at how some companies enforce data validation rules at ingestion to prevent inconsistent insights, can share what’s working if useful.
Who Should Target Unisys New Right Now
This account is relevant for:
- AI Development Operations (MLOps) platforms
- Hybrid Cloud Cost Management solutions
- Cybersecurity Orchestration and Automation platforms
- Data Quality and Governance tools
- Field Service Management software with AI integration
- Application Modernization and Migration services
Not a fit for:
- Basic project management tools
- Stand-alone marketing automation platforms
- Generic IT help desk software
- Products designed for small business IT infrastructure
When Unisys New Is Worth Prioritizing
Prioritize if:
- You sell platforms for validating AI-driven field service assignments against performance metrics.
- You sell solutions that detect security vulnerabilities in AI-generated code during development workflows.
- You sell tools for monitoring application performance and cost within hybrid cloud environments.
- You sell security orchestration platforms that automate incident response across disparate security systems.
- You sell data quality solutions that enforce consistent data formatting in analytics ingestion pipelines.
- You sell platforms that standardize data models for unified reporting across fragmented data sources.
Deprioritize if:
- Your solution does not address specific breakdowns within AI-driven service, cloud, security, or data workflows.
- Your product provides only generic analytics or reporting capabilities without specific data validation features.
- Your offering focuses solely on on-premises IT infrastructure without hybrid cloud integration capabilities.
Who Can Sell to Unisys New Right Now
Field Service Optimization Platforms
ServiceMax - This company offers field service management software that optimizes scheduling, dispatch, and mobile operations.
Why they are relevant: AI-driven field service automation at Unisys New experiences conflicts in appointment scheduling. ServiceMax can validate technician availability against automated schedules and ensure consistent service delivery.
IFS - This company provides enterprise software for managing service and asset lifecycles, including field service management.
Why they are relevant: Unisys New's automated ticket routing generates incorrect technician assignments. IFS can apply advanced routing logic to prevent misallocations and improve first-time fix rates.
AI Governance and Validation Platforms
C3 AI - This company delivers an enterprise AI application development platform with data integration and model management capabilities.
Why they are relevant: AI-generated code at Unisys New does not meet internal quality standards. C3 AI can enforce code quality checks and validate AI-generated outputs against predefined metrics.
Databricks - This company offers a data intelligence platform that unifies data, analytics, and AI workloads across the enterprise.
Why they are relevant: Unisys New's generative AI models produce biased results during testing. Databricks can monitor AI model predictions for bias and detect drift in real-time.
Weights & Biases - This company provides a developer platform for machine learning, offering tools for experiment tracking, model optimization, and collaboration.
Why they are relevant: Generative AI at Unisys New lacks proper version control within development pipelines. Weights & Biases can manage AI model versions and route them through automated change management.
Hybrid Cloud Optimization Platforms
CloudHealth by VMware - This company offers a cloud management platform that provides cost optimization, security, and governance for multi-cloud environments.
Why they are relevant: Hybrid cloud costs at Unisys New exceed allocated budget thresholds. CloudHealth can detect cost anomalies and enforce spending limits across diverse cloud resources.
Turbonomic - This company provides an AI-powered platform for application resource management and cloud cost optimization.
Why they are relevant: Application performance at Unisys New degrades after cloud migration. Turbonomic can monitor and dynamically adjust cloud resource allocation to maintain optimal application performance.
Rubrik - This company offers a data security and management platform for hybrid cloud environments, focusing on data resilience and recovery.
Why they are relevant: Data transfer processes at Unisys New fail to complete during legacy system cloud transition. Rubrik can validate data integrity between source and target systems during migration and ensure recovery readiness.
Cybersecurity Automation and Orchestration
Cortex XSOAR by Palo Alto Networks - This company delivers a security orchestration, automation, and response (SOAR) platform.
Why they are relevant: Security event correlation at Unisys New fails to detect advanced persistent threats. Cortex XSOAR can automate the correlation of security events and orchestrate incident response workflows.
CrowdStrike - This company provides cloud-native endpoint protection, threat intelligence, and security operations solutions.
Why they are relevant: Zero-trust policies at Unisys New block legitimate user access to internal applications. CrowdStrike can refine access policies based on continuous authentication and behavioral analysis.
Splunk - This company offers a data platform for security, observability, and IT operations, enabling real-time monitoring and analysis.
Why they are relevant: Vulnerability scanning tools at Unisys New produce excessive false positive alerts. Splunk can filter and prioritize security alerts to reduce noise and focus analyst efforts on actual threats.
Final Take
Unisys New actively scales its integrated AI capabilities and modernizes its core cloud infrastructure. Breakdowns are visible in the precision of AI-driven service automation, the quality assurance of AI-generated code, and the consistent performance of hybrid cloud applications. This account is a strong fit for solutions that precisely validate AI outputs, orchestrate complex cloud migrations, and automate advanced cybersecurity responses.
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