The rapid evolution of HR technology is being shaped by the growing demand for strategic workforce alignment and AI-powered advancements. Justin Angsuwat, Chief People Officer at Culture Amp, highlights that HR leaders must leverage strong workplace and HR data foundations to navigate this transformation effectively.
With AI’s impact accelerating, the next 12-18 months will be critical for HR teams to optimize data strategies and unlock the full potential of agentic AI—a shift that McKinsey and Deloitte predict will redefine HR’s role within organizations.
The Urgency for HR Data Maturity
AI adoption in HR is moving beyond process automation into personalized workforce insights and predictive analytics. However, many organizations remain in the early stages of AI maturity, limiting their ability to extract meaningful insights from HR data.
“The power of the HR team is no longer going to be finding data. It’s about finding insights and knowing what to do with them.”
– Justin Angsuwat, Chief People Officer, Culture Amp
Deloitte forecasts that one-fourth of companies using Generative AI will launch agentic AI pilots this year, with 50% adoption by 2027. Organizations that fail to prepare their data ecosystems today risk being left behind.
Building an AI-Ready HR Data Infrastructure
A structured, AI-ready data framework is essential for unlocking AI’s potential. Angsuwat recommends that HR leaders focus on:
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Consistent Data Structuring: Standardized definitions for key HR metrics (e.g., headcount, full-time equivalents, active employees).
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Data Portability: Seamless integration across platforms and HR systems.
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Bias-Free Data Collection: Ensuring fair and ethical AI-driven decision-making.
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Real-Time Data Accessibility: Enabling instant workforce insights and actionable intelligence.
Organizations should avoid investing in AI tools before building a strong data foundation, as premature adoption can lead to organizational friction and wasted resources.
The Four Stages of HR Data Maturity
According to McKinsey research, only 1% of organizations consider themselves fully mature in AI implementation. Angsuwat outlines four key HR data maturity levels:
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Descriptive: Understanding the current workforce landscape.
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Diagnostic: Identifying why certain patterns emerge.
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Predictive: Forecasting future workforce trends and risks.
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Prescriptive: Recommending AI-driven strategic interventions.
Most HR teams remain at the descriptive or diagnostic stage, but progressing towards predictive and prescriptive analytics will unlock AI’s full potential in workforce planning, talent management, and employee experience.
AI’s Role in HR: Beyond Automation to Business Growth
While early AI adoption in HR has focused on automating repetitive tasks, the real impact lies in:
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Predictive Workforce Analytics: Anticipating hiring needs, attrition risks, and skill gaps.
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Personalized Employee Experiences: AI-driven coaching, training, and career development.
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Strategic Decision-Making: Leveraging AI insights to drive business performance.
AI adoption isn’t just about efficiency gains—it’s about revenue growth. Nearly 90% of business leaders expect AI to drive financial gains within three years, but only those that fully transform their HR data capabilities will see lasting success.
HR Leaders Must Act Now
The next 12-18 months present a critical window for HR teams to refine their data strategies and prepare for AI-driven transformation. Organizations that invest in data readiness today will secure a competitive advantage in workforce planning, employee engagement, and business growth.
“People leaders will demand that HR is data-informed. Gut feelings will no longer work in HR.”
– Justin Angsuwat
The future of HR is data-driven and AI-powered. The question is: Will your organization be ready?
Source – HR Executive
