The HR Revolution: What You Need to Know about HCM in 2025

With Mars landings all the rage, it might be apt to say that HCM is being terraformed before our very eyes.  

With shifts in the extensive systems that underly HR, organizations are racing to modernize infrastructure. They are doing so while grappling with emerging artificial intelligence capabilities. It would be an understatement to say that the task at hand is proving difficult to carry out.  

With events like HR Tech 2025 taking place, we thought it a great time to reflect on the opportunities and challenges defining this critical evolution in human resources.

What is the state of HCM today?

Global HCM Market

The HCM market has reached remarkable scale, with +$35 billion in annual recurring revenue, growing at 13% annually. North America continues to dominate with 61% of global revenue, while EMEA accounts for 24% of the market. This growth reflects not just general market expansion, but fundamental shifts in how organizations approach workforce management and employee experience.  

The competitive landscape reveals concentrated market power among established players. At the same time, there is a stark differentiation emerging between traditional enterprise solutions, and innovators pushing the bounds of what’s possible.

Top 5 HCM Market Share Leaders

Who is leading, and why?

Workday is maintaining its global leadership position at 15.7% market share, followed closely by UKG (11.7%) and SAP (11.6%). Oracle holds 8.2% of the market, while Cornerstone OnDemand, despite impressive growth, remains at approximately one-quarter of Workday's scale. This concentration among the top five vendors demonstrates the market's preference for proven, comprehensive platforms, capable of handling complex requirements.  

Challenges Faced

Cloud Migration

Despite talk of widespread cloud adoption, the reality is more nuanced. Cloud solutions account for 76% of total HCM revenue, yet many organizations continue struggling with legacy system transitions. It is all but certain that companies will continue to turn to testing and implementation partners to guide workflows and bridge the gap, as enterprises face mounting pressure to seamlessly modernize their operations.

The barriers to cloud migration extend beyond technical considerations. Organizations are most concerned with:

• Data quality and migration risks
• Complex global compliance requirements
• Integration challenges  

Such concerns with cloud migration are not unfounded, but it’s also universally clear that sticking with the status quo is unwise. The conundrum is that the very issues that propel enterprises to modernize, are the same ones that make modernization difficult. For example, legacy systems often contain years of accumulated technical debt, outdated code dependencies, and undocumented customizations. These issues hamper and complicate modernization.

Uncertain ROI for AI

While GenAI and Agentic AI dominate vendor messaging, real-world impact remains limited.

Recent research made waves, revealing that 95% of generative AI pilots fail to deliver meaningful ROI. What is less widely understood, though, is why. It turns out that the primary barriers to AI success aren't technological, but organizational. These can include:

• Brittle workflows
• Lack of contextual learning
• Misalignment with day-to-day operations

Companies investing billions in AI tools often discover that individual productivity gains don't always translate to measurable business impact. Agentic AI may show more promise, but organizational and culture shifts are still necessary to unlock its potential.

How Companies are Rising Above Challenges

For HR technology, cultural shifts are massively important in addressing challenges with implementation. Second, though, is testing. The difficulty is: the need for testing increases exponentially when organizations transition between two fundamentally different system architectures. In our experience, organizations do not plan for broad enough testing coverage to truly validate and assure their HCM transformation.

What does bad testing look like?

Poor testing protocols often involve:

• Inexact or inaccurate definition of requirements  
• Inadequate validation processes  
• Low feature adoption, from lackluster change management

What does great testing look like?

Organizations implementing new HCM systems must validate complex business processes while ensuring AI-enhanced features function reliably. To do this, organizations must re-think testing.

A better approach includes:

• An appropriately-wide scope of validation: HR organizations must test widely during fundamental transformations
• Rigorous focus and testing of AI features: we find enterprises reach success when they can demonstrate ROI on AI capabilities to leadership
• Feature adoption: organizations increasingly recognize the value of expanding beyond technical validation to include user experience verification and adoption readiness
• Agentic is the word: agentic AI offers more robust testing frameworks that can validate decision-making, orchestrate testing workflows, and manage API/integration dependencies across multiple systems

Looking Forward in HCM

The HCM market's evolution requires leadership at the intersection of enterprise software testing, cloud migration support, and AI validation. Companies are struggling with legacy modernization and AI-enhanced applications, and they need specialized testing expertise to help wade through the waters of transformation in HCM.

As HR technology itself continues evolving toward more autonomous, intelligent systems, the need for sophisticated testing approaches has never been so great. In this liminal period, we must validate both traditional business logic and emergent AI systems. Companies that can thread this needle with more fined-tuned, AI-ready culture, and the testing solutions to back it up, will lay the groundwork for sleeker, more functional, more innovative HCM operations.