Workforce intelligence: How HR and IT can turn fragmented data into faster, smarter decisions

Your people are building the plane while flying it: Mercer reported that 81% of executives admit leaders in their organizations are struggling to simultaneously run and transform the business at the same time.

This isn’t a single team’s challenge. It’s a response to near-constant change, viewed through different lenses. IT views change in terms of new technology, artificial intelligence (AI), and shifting infrastructure needs. HR sees it through people: what roles are changing, which skills are becoming scarce, and who may be at risk of falling behind or leaving. Both perspectives are valuable, but when they’re misaligned, they hinder proactive planning and adaptive response.

A 2026 Cornerstone and Vanson Bourne study of 2,000 decision-makers and employees found that 93% of IT and HR leaders agree their departments could be better aligned on workforce needs. Yet only 48% say they work closely together with shared goals.

Employees feel the consequences. According to the study, only 17% feel fully prepared for how their role will change over the next year or two, and 60% describe their organization’s approach to skills development as reactive. Instead of preparing for change before it arrives, many people are trying to build new capabilities while in the thick of disruption.

HR and IT need a shared, current view of workforce capabilities, changing business needs, and emerging risks to get on the same page. Workforce intelligence provides that shared reality, connecting fragmented workforce data to help teams move from separate interpretations of change to coordinated action.

What is workforce intelligence, and what does it achieve?

A workforce intelligence platform combines data analytics and AI to turn workforce and labor-market data into clear signals that help you make confident decisions about hiring, development, and workforce planning.

Unlike traditional workforce analytics, which show current headcount and historical metrics, workforce intelligence adds live data and predictive insights, so you can act on opportunities or address problems before they grow. That forward-looking view is crucial, yet often overlooked. McKinsey's HR Monitor 2026 found only 11% of organizations take a long-term view of workforce planning.

Workforce intelligence brings together three connected layers:

• A governed workforce data foundation: HR, learning, performance, recruiting, and work data from across your tech stack are standardized and connected into one platform, so job titles, roles, and skills are consistent and normalized.

• Contextual skills and labor market intelligence: AI combines internal skills signals, such as training, performance, project history, and career movement, with external data on skill demand, availability, and compensation. This helps workforce intelligence understand skills in the context of specific roles, tasks, and business needs.

• Predictive insights and recommended actions: Pattern-recognition models identify emerging skills gaps, retention risks, capacity constraints, and internal talent development opportunities. They can then suggest practical next steps, such as targeted learning paths, redeployment, external hiring, or succession planning.

Together, these layers turn a static dashboard someone checks once a quarter into meaningful intelligence that answers the questions keeping leaders up at night: Could we staff an AI-driven transformation with people we already have? Who might be ready to move into a critical opening with the right training? Where is a capacity risk about to become a business problem?

For your people, it means clearer visibility into the skills their roles will require, the internal opportunities they may be ready to pursue, and the development paths that can help them get there.

Cornerstone Workforce AI™ was built for this, combining the Cornerstone People Graph™ and Skills Engine to create a living model of how people, skills, roles, and work connect across the organization. Instead of simply recording that someone has a skill, it looks at how they’ve used it, where it applies, and whether demand for it is rising or falling, giving organizations the insights they need to make smarter decisions.

Leading bank identifies critical skills and avoids $3 million in costs

A leading European bank used Cornerstone to assess anti-financial crime capabilities across 850 people, 19 teams, and 80 roles. By comparing internal skills with external labor market benchmarks, the bank identified strengths and gaps by business unit, team, and role, then assigned targeted learning to build the capabilities it needed most.

Using AI, the bank avoided more than $3 million in manual analysis and consulting costs, reduced the risk of fines that could exceed $50 million, and established continuous benchmarking to keep critical skills aligned with changing industry demands.

What disconnected workforce data is costing you

It sounds straightforward: workforce intelligence combines information about your people, development initiatives, and future needs, to help you make better decisions.

But in reality, many organizations are limited by a big data problem. Data lives across HR systems, learning platforms, recruiting tools, performance records, project systems, spreadsheets, and in the everyday tools where workers collaborate and track progress, like Jira, Teams, and Salesforce. Most workforce solutions still miss these real work signals entirely, relying on traditional talent profiles instead of the tools where people are actually doing the work. Without a workforce intelligence platform to bring it all together, the process of checking, updating, and analyzing data across systems is a major pain point.

The same Cornerstone and Vanson Bourne report found that 85% of organizations rely on three or more methods to access workforce data. Picture it: by the time you request or pull data from three different systems, reconcile inconsistencies, and build a usable report, that picture is long outdated.

AI only exacerbates this problem. Adding AI on top of fragmented or inaccurate data enables organizations to make assumptions, mistakes, and misguided decisions faster and at scale. AI can only produce reliable insights when it can access current information, see how roles and skills relate to one another, and understand a common language across systems.

The study revealed, when workforce data stays fragmented and inaccessible, the cost your organization pays is often wrong, delayed, or missed decisions:

• 50% of organizations say skills gaps remain unaddressed for too long

• 44% report delays in hiring, redeployment, or restructuring decisions

• 41% miss productivity or efficiency targets

• 41% feel limited to respond when market conditions change

These aren't just reporting problems. They affect real decisions, such as staffing a new initiative, preparing people for a changing role, or catching a capacity risk before it hurts the business.

To help organizations unstick these workforce data problems, a workforce intelligence platform provides one integrated and continuously updated view of workforce capabilities. And investing in the right one can accelerate readiness: according to the recent Cornerstone and Vanson Bourne study, organizations using AI to support workforce planning are twice as likely to say they have the processes, data, and tools needed to make workforce decisions quickly.

But solving the data problem is only one step. To turn workforce intelligence into action, HR and IT need shared priorities, clear ownership, and a common process for making decisions together.

Animates cuts HR administration by 70% and expands skills-based development

Animates Vetcare replaced paper forms, spreadsheets, and disconnected systems with Cornerstone, creating a single source of truth across HR, learning, performance, recruiting, and succession. Using Cornerstone Workforce AI™ and Cornerstone Content, Animates built development pathways to give team members meaningful opportunities to strengthen current skills or grow into new roles, not just check the box on compliance.

Today, 88% of courses completed through The Pawtal are self-registrations, and people leaders report having better visibility and practical tools to coach their teams. Animates also reduced HR administration by 70%, freeing the People team to focus on professional development and retention.

HR and IT alignment drives effective workforce intelligence

Getting HR and IT on the same page may feel like an uphill battle, even when both teams are bought into the idea. Among IT and HR leaders, 94% agree workforce planning needs to become more continuous and adaptive, but 40% cite a lack of joint planning between IT and workforce strategy as one of their biggest challenges, according to the workforce readiness study.

Importantly, IT and HR are not necessarily disagreeing. They’re just solving different parts of the same problem, often on separate tracks. IT tends to prioritize visibility, forecasting, and technology, while HR focuses on developing people and creating clearer workforce processes.

Effective workforce intelligence connects those priorities, so insight and action support the same goals. According to the workforce readiness study, organizations where HR and IT collaborate closely are 67% more likely to feel equipped to make workforce decisions at the speed their industry requires.

A workforce intelligence platform can give both teams access to the same information, but they still need to agree on what signals mean, which decisions they influence, and who is responsible for acting on them.

Building that internal alignment typically looks across four areas.

1. Start with shared business priorities

Alignment begins before HR drafts a workforce plan or IT evaluates a new platform.

HR and IT must first agree on which priorities matter most over the next 12 to 24 months and which workforce decisions they need to make across technology, work design, and people.

For example, an AI initiative isn’t just a question of which technology to buy. HR and IT must also figure out how that initiative changes tasks and roles, how much capacity the organization will need, and whether those needs should be met through development, redeployment, hiring, automation, or a combination.

The result is a collaborative workforce readiness strategy tied to business goals, not separate HR and IT plans that get compared once a year and then operate independently.

To build a shared workforce readiness strategy:

• Discuss corporate goals, common roadblocks, and existing initiatives.

• Identify three to five business priorities that will create the greatest workforce change and have the greatest impact on organizational goals.

• Map the roles, tasks, skills, technology, and capacity each priority will require.

• Agree on what “ready” means for each priority.

2. Build one workforce view to inform people and technology decisions

Both HR and IT need to work from the same trusted data and share a clear understanding of workforce capability and needs. Otherwise, when each team operates from a different version of the workforce, they can make individually reasonable decisions, but still pull the organization in different directions.

This is not an ad hoc exercise of pulling and consolidating reports. The data needs to be integrated, standardized, governed, and directly accessible to both teams whenever they need it, ideally without waiting for someone else to produce a report.

A reliable data foundation turns scattered information into workforce intelligence. Organizations should treat it as a corporate priority and strategic asset that informs both workforce planning and technology decisions. Alignment happens through collaboration, while workforce intelligence provides the starting point for decisions and the evidence to compare options.

Develop a unified workforce view:

• Define the workforce data both teams will use by agreeing on consistent definitions for critical roles, skills, proficiency levels, capacity, and readiness, so HR and IT are not measuring the same workforce in different ways.

• Create one governed source of workforce intelligence by connecting the relevant HR, learning, performance, recruiting, and work systems and assigning owners for data quality, access, and updates.

• Establish standards for data freshness and reliability, so both teams know how recently information was updated and whether it’s reliable enough to support a decision.

• Provide role-appropriate access and reporting views, so HR and IT can answer their own questions without creating competing reports or data sets.

3. Agree how you will act on workforce signals

You don’t need another dashboard. You need an actionable plan for responding to the signals workforce intelligence surfaces.

Let’s say workforce intelligence shows that a critical data skill will be in short supply by next year. HR must now decide whether people with adjacent skills can be developed in time or whether external talent is the faster path. IT, working from that same signal, decides whether automation or new tooling can step in, and both teams must determine what the tradeoffs are for each choice.

Once each team chooses a response, there needs to be an owner, timeline, and clear next step, whether that's HR launching a learning path or opening a stretch assignment, or IT scoping a tooling investment. The process should be deliberate, not a series of off-the-cuff decisions.

A repeatable process helps HR and IT each respond to workforce signals with speed, consistency, and clear accountability in their own lanes. Start with a focused initial use case, such as internal mobility or succession planning. This approach helps HR and IT establish a shared working model that guides HR’s people decisions and IT’s AI and tech recommendations, without trying to transform every workforce process at once.

Test the process:

• Choose a business problem with a clear cost, deadline, executive sponsor, and measurable outcome as the test case.

• Define which signals will trigger a joint review and who must participate in choosing the response.

• Establish a baseline, including how long the decision takes today and the current cost or business result.

• Review the findings together, assign an owner, timeline, and next step.

4. Measure whether workforce intelligence is improving decisions

Too often, organizations measure the activity surrounding workforce readiness, such as platform adoption, training completions, or whether a technology rollout stayed on schedule. Those measures show what work took place, but not whether workforce intelligence helped the organization make faster, better decisions.

Instead, HR and IT should turn that shared definition of readiness into a scorecard that combines employee and business outcomes. This gives both teams shared goals and a structured way to judge investments by their impact on workforce adaptability.

HR and IT should review these measures together regularly and use the results to adjust workforce, development, and technology investments.

A practical scorecard could focus on four areas:

• Track decision speed by measuring how long it takes to go from identifying a capability gap to approving and implementing a response.

• Assess workforce capability by determining whether gaps are closing, more priority roles are being filled internally, and people are reaching proficiency faster.

• Evaluate employee readiness by measuring whether capability and confidence are improving, people understand how their work is changing, and they receive support before change is already underway.

• Measure business impact by determining whether strategic initiatives have the skills and capacity they need and whether productivity, workforce agility, and execution are improving.

Every measure should connect to a decision in the overall plan. If a readiness metric declines, the teams should already know who will review it, what questions to ask, and what action to take next.

Why Cornerstone is the leader in workforce intelligence

Workforce readiness cannot be solved in an annual planning session, because business goals, technology, and skills keep changing. HR and IT need a regular way to assess new signals and adjust their plans together.

Cornerstone Workforce AI™ gives HR and IT one governed, current view of workforce skills, roles, capacity, and future needs without forcing either team to replace the systems they already use. The Cornerstone People Graph™ and Skills Engine connect signals from across your tech stack, and then layer in global labor market intelligence, so you have a comprehensive picture to inform decisions. Meanwhile, an open architecture makes those insights available across existing workflows and tools, like Salesforce or Slack.

What further sets Cornerstone apart is that its insights are actionable. Instead of providing yet another report, Cornerstone connects workforce intelligence directly to learning, development, mobility, succession, and workforce planning. You can close critical gaps sooner, deploy talent more effectively, accelerate proficiency, and make workforce and technology decisions from the same evidence.

Responsible AI is core to the platform. Built-in governance, explainability, auditability, and human oversight help both teams trust the recommendations and retain control over consequential workforce decisions.

Book a demo to see why Cornerstone was named the 2025 HR Tech Award winner for Best Talent Intelligence Solution and how Cornerstone Workforce AI™ empowers your HR and IT teams.

Frequently asked questions about workforce intelligence

How does workforce intelligence differ from traditional people analytics?

People analytics typically looks backward, at historical metrics like turnover and engagement scores. Workforce intelligence adds current, connected data and AI-driven, forward-looking recommendations, so organizations can act before issues grow, rather than reviewing them after the fact.

Does a workforce intelligence tool integrate with my other platforms?

With a workforce intelligence platform, data from your human resources information system (HRIS), learning management system (LMS), applicant tracking system (ATS), and performance tools flow into a single, connected view. With all of that information working together, you can see not just who works where, but what skills your organization has, where gaps are forming, and which teams need support before problems surface.

How long does it take to see results from a workforce intelligence platform?

Results depend on the use case, data quality, integration complexity, and how quickly leaders and managers incorporate the insights into decisions. Starting with one focused use case can make progress easier to measure before expanding.

Can mid-sized organizations benefit, or is this only useful at enterprise scale?

Yes. Mid-sized organizations can start with one defined business problem and connect the data and systems most relevant to that use case. The appropriate scope depends more on workforce priorities and data complexity than organization size alone.

Is workforce intelligence the same as employee monitoring software?

No. Workforce intelligence works at the organizational level, using AI to analyze skills, learning, performance, and career data and surface trends like readiness gaps and succession risk, not to track what any one person is doing minute to minute.