Sapience Named Workforce Intelligence Company of the Year 2026

Overview

Enterprises today are navigating profound shifts. Hybrid and remote work, rapid digitalization, and rising regulatory demands have redefined how organizations operate.

Leadership teams are under pressure to scale generative and agentic AI responsibly—ensuring compliance and measurable value—yet many remain uncertain about where to start, which use cases to prioritize, and how to ensure safety.

According to Everest Group’s 2025 survey, 86% of enterprises admit they are unprepared to manage the risks required to capture AI’s higher-order rewards.

Meanwhile, rising labor costs and the need to align workforce productivity with business priorities add further strain.

Traditional approaches—such as financial reports, surveys, or manager feedback—capture outcomes but fail to reveal the underlying drivers of productivity, capacity, and risk.

Leaders need a workforce intelligence layer that offers a continuous, fact-based view of:

• How work happens
• Where inefficiencies occur
• How resources can be aligned more effectively

This is not about monitoring individuals—it’s about surfacing organizational patterns such as:

• Workload distribution
• Employee well-being
• Supplier accountability
• Technology adoption

Modern platforms capture these signals across:

• Networks
• Virtual Desktop Infrastructure (VDI) environments
• Devices

This ensures insights are consistent and scalable across the enterprise.

By focusing on systemic signals, workforce intelligence helps leaders:

• Optimize labor spend
• Strengthen workforce sustainability
• Govern AI adoption responsibly
• Maintain transparency and trust

In a recent discussion, the President of Xerox IT Solutions shared how Sapience:

• Increased workforce utilization from 68% to 93%
• Reduced unused software licenses by 60–80%
• Saved approximately $360 per license annually

What This Viewpoint Covers

This Viewpoint examines how workforce intelligence is evolving in response to enterprise needs and provides a framework to turn analytics into measurable outcomes.

Key topics include:

• The shifting work and organizational performance landscape
• What types of workforce data matter most and why
• How workforce intelligence enables use cases and business outcomes
• Stakeholder perspectives and cross-enterprise value creation
• Evidence from enterprise adoption and lessons learned
• A strategic roadmap to move from visibility to value

Business and technology leaders can use this to:

• Align workforce intelligence with organizational goals
• Guide digital and workforce investments
• Build a foundation for scalable, AI-enabled growth

External Forces & Internal Realities

External Forces

• Skill Gaps
  A persistent gap between workforce skills and business needs, with rising demand for digital, analytical, and leadership capabilities
• Economic Uncertainty
  Cost pressures, inflation, and frequent priority shifts requiring agile resource allocation
• AI & Technology Disruption
  Enterprises struggle to identify use cases, ensure safe adoption, and scale AI effectively

Internal Realities

• Hybrid & Fragmented Workforce Models
  Distributed teams across geographies create coordination and visibility challenges
• Regulatory Compliance
  Expanding requirements around labor laws, data privacy, and workforce policies
• Contingent Workforce Visibility
  Limited insight into external labor costs, productivity, and integration
• Workforce Expectations
  Increased demand for flexibility, transparency, well-being, and purpose-driven work
• Collaboration Overload
  Excessive meetings and messaging reduce focus and productivity

Key Insight

Everest Group research shows that 47% of enterprises want to upskill talent with generative AI capabilities but lack visibility into where to focus.

Enterprise Systems vs Workforce Intelligence

Traditional Systems

• Human Capital Management (HCM): Employee data, payroll, benefits
• Customer Relationship Management (CRM): Customer interactions and sales
• Supply Chain Management (SCM): Procurement and logistics
• IT Service Management (ITSM): IT services and infrastructure
  
  

Workforce Intelligence (WFI)
Optimizes:

• Resource productivity
• Cost savings
• Workforce capacity

The WIDE Framework

W — Work Patterns
Data on how work is executed across roles, teams, and departments
Reveals inefficiencies, overload, and bottlenecks

I — Interaction with Digital & AI Tools
Insights into how employees use enterprise applications and AI
Helps determine ROI and ensure safe adoption

D — Deliverables / Outcomes
Connects daily work to business outcomes
Tracks performance, quality, timelines, and cost efficiency

E — Enterprise Workforce
Visibility into internal and external talent
Improves planning, retention, and workforce sustainability

Why This Data Matters

“This is the fastest ROI platform I have seen in 30 years.”
— Munu Gandhi, President, Xerox IT Solutions

• A mortgage firm achieved $16.7M in productivity gains in 4 months
• Reduced non-productive work by 2 hours per employee per day

Real-World Use Cases

“We target three key use cases:

1. Spot innovation through technology usage
2. Identify burnout risk early
3. Reallocate capacity without targeting individuals”
   — CTO, U.S. Finance Firm

Stakeholder Perspectives

CHRO
Nearly 30% of employees lack digital proficiency for AI workflows

Business Unit Head
Need to retrain 200 employees and reallocate 50 to higher-value work

CIO / CTO
Only 60% of AI applications are fully used—potential $1M savings

CFO
$5M investment offset within 12–18 months through gains and savings

Procurement Head
External providers can deliver faster adoption at 20% lower cost

Enterprise Impact Examples

• Fortune 500 company recovered $12M in outsourcing costs
• Increased productivity by 1.5 hours per employee daily
• Large U.S. bank uses workforce intelligence for:
  • Contractor reconciliation
  • C-suite reporting
  • Enterprise-wide operational decisions

The A³ Framework (Align, Analyze, Act, Accelerate)

Align

• Integrate data from collaboration tools (Teams, Microsoft 365, Google Workspace)
• Connect enterprise systems (ERP, HRIS, payroll, VMS)
• Define shared metrics across HR, IT, finance, and procurement

Analyze

• Use the WIDE framework
• Prioritize insights tied to business outcomes:
  • Burnout prevention
  • License optimization
  • Provider accountability
• Ensure data is secure, explainable, and accessible

Act

• Embed insights into workflows:
  • Budget approvals
  • Workforce planning
  • Supplier negotiations
  • AI deployment
• Create dashboards for all levels of the organization

Accelerate

• Deploy across networks, VDI, and devices
• Establish cross-functional governance
• Reinforce privacy-first design and AI guardrails