How Skillsoft CPO Ciara Harrington Gets Employees Excited About AI and Upskilling
Ciara Harrington always wanted to lead. She grew up with a briefcase in hand, found her way into HR through compensation and benefits, and sharpened her change skills in consulting before returning to corporate life. Today, as Skillsoft's chief people officer, she's focused on one thing HR cares about: building skills that stick.
Her stance on AI is refreshingly clear: it's a tool, not a threat. The work doesn't disappear - it shifts. Admin tasks move to machines, and people get more time for coaching, leadership, and engagement.
AI at Work: Replace Fear With Usefulness
"AI is a tool to help us, as humans, do our jobs better," Harrington says. The risk isn't that AI removes every job; it's that people who refuse to learn it sideline themselves, like refusing to use a computer years ago.
The message to employees: learn it, use it, and keep the human responsibility. If AI drafts the email, it still goes out under your name. You own the outcome.
How HR Can Get People to Lean In
- Set the narrative: AI clears repetitive work so people can focus on coaching, problem solving, and engagement. Say it plainly and repeat it.
- Start with visible wins: Pilot AI for meeting notes, email drafts, job descriptions, and training outlines. Track time saved and share the numbers.
- Be open about your strategy: Explain where AI will be used, where it won't, and how decisions are made. Hold Q&A sessions and office hours.
- Clarify accountability: The human reviews and approves everything. Make review steps explicit and non-negotiable.
- Build role-based learning paths: Create short, focused tracks for recruiters, HRBPs, L&D, and analytics teams. Require a minimum number of hours each quarter.
- Model the behavior: Leaders should show their workflows, not just talk about them. Share templates and prompts.
- Reward adoption: Recognize teams for time saved, quality improvements, and better employee experience - not just usage.
Accountability Checklist for Any AI Output
- Fact-check claims and figures against trusted sources.
- Remove confidential or personal data that slipped in.
- Adjust tone to match brand and audience.
- Scan for bias, fairness, and compliance risks.
- Add context, examples, and decisions the model can't know.
- Final human sign-off. Your name, your responsibility.
Design an Upskilling Program People Actually Use
- Core literacy (2-3 hours): What AI is, where it helps, where it fails, and common pitfalls. For governance context, see the NIST AI Risk Management Framework.
- Role-specific workflows (3-6 hours): Recruiter sourcing and screening, HRBP coaching aids, L&D content drafting, and people analytics support.
- Responsible use: Bias checks, data privacy, and documentation. EEOC guidance on AI in employment is a helpful reference: EEOC on AI.
- Show your work: Require before/after examples and time-saved estimates. Make it a portfolio, not a quiz.
A Simple 45-Day Rollout
- Days 1-15: Communicate the why. Deliver AI 101. Launch two pilots (e.g., meeting summaries and job descriptions).
- Days 16-30: Train managers to coach with AI. Standardize your accountability checklist. Collect early metrics.
- Days 31-45: Publish playbooks. Recognize wins. Expand pilots to two more workflows per team.
Culture Matters More Than Tools
Harrington's point lands: tools only help if people trust the purpose and feel ownership of the output. Be honest about where AI fits, teach people to use it well, and keep accountability human. That's how you get adoption without losing judgment.
Ciara Harrington, in Brief
- Early interest: Data-driven HR through compensation and benefits.
- Consulting chapter: Built problem-solving and change skills through complex client work.
- Now: Leading people strategy at Skillsoft, with a practical stance on AI, learning, and accountability.
Next Steps for HR
- Pick two admin-heavy workflows and replace them with AI-assisted steps this month.
- Stand up a role-based training path and mandate a small, consistent time commitment each quarter.
- Publish your AI usage policy in plain language, including review rules and data practices.
Need structured learning paths by job type? Explore curated options here: AI courses by job.
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