Scaling AI in HR

The HR team of The Heico Companies, a diversified industrial holding company with over 80 companies across five continents, struggled to extract data from siloed systems, leading to ineffective dashboards and delayed decisions. The lack of real-time reporting and integration made it difficult to generate predictive workforce or career insights. As a result, HR staff were bogged down doing manual data preparation rather than strategic work.

Interest in artificial intelligence was high, but The Heico Companies faced structural challenges that limited progress. Leaders needed clarity on where AI could create value, how to measure success, and how to scale solutions across 80 operating companies and approximately 10,000 employees without introducing unnecessary risk.

To avoid costly implementation missteps, The Heico Companies enrolled its team in SHRM’s AI Enablement for HR program to assess AI readiness, align stakeholders, prioritize high-impact use cases, and translate AI interest into measurable business outcomes.

In just eight weeks, The Heico Companies moved from exploratory conversations about AI to practical application within HR workflows.

The organization reduced manual data entry and preparation work, freeing up HR teams to focus on higher-value activities. More importantly, leaders observed a significant shift in mindset: Employees no longer viewed AI as mysterious or threatening.

Participants emerged as internal AI champions, increasingly sought out by colleagues for guidance. Post-program assessments reflected this cultural and capability shift, with self-reported increases of 20% to 40% in preparedness, confidence, and perceived process efficiency.

Rather than engaging in isolated experimentation, The Heico Companies established a shared understanding of where AI fits into HR workflows, how it supports managers, and how future use cases can be scaled responsibly across the enterprise.     

Before deploying tools, The Heico Companies needed to assess whether its people and processes were ready to support them. An initial assessment revealed a critical gap: Employee enthusiasm for AI was high, but the organization lacked shared clarity around workflows, governance, and execution.

The risk was clear: Moving fast on technology without aligning on process and decision-making structures would dilute impact and stall adoption. 

By establishing a shared baseline, leadership identified strengths, exposure points, and priority areas for support. This created the foundation for responsible, scalable AI adoption.

Interest in AI was strong, but alignment was not. Teams initially prioritized different areas, including recruitment and core HR automation. The discussion risked becoming tool-driven rather than value-driven.

The shift came by reframing the conversation around three questions:

1. Where will AI drive measurable impact?
2. What is feasible within current constraints?
3. Where can we scale responsibly? 

Performance management emerged as the highest-impact opportunity. Managers were burdened by time-intensive processes and struggled with inconsistent goal setting. The Heico Companies repositioned AI as a manager enablement layer, supporting:

• Stronger SMART (Specific, Measurable, Achievable, Relevant, Time-bound) goal development.
• More structured performance conversations.
• Reduced administrative lift. 

Once priorities were clear, the question shifted from what to pursue to how to execute without introducing risk.

The Heico Companies used backward planning and the PACE (Primary, Alternate, Contingency, Emergency) communications methodology to pressure-test implementation before launch. This approach enabled it to:

• Anticipate constraints and failure points.
• Define alternate paths before pilots began.
• Move from pilot to production with greater confidence.      

Execution was tied to defined success measures, including:

• Alignment on priority use cases.
• Stakeholder engagement and adoption readiness.
• Increased team confidence and capability.
• Clear governance and defined next steps. 

The result was disciplined progress. AI initiatives were structured, measurable, and scalable, not isolated experiments. 

The Heico Companies’ structured approach turned AI from exploration into execution. By aligning governance, priorities, and capability upfront, the organization minimized risk, accelerated adoption, and positioned HR to deliver measurable efficiency gains and stronger performance outcomes at scale.