HANCOM Sets 2026 as Year One for Embedded AI - What HR Needs to Know
HANCOM announced it will make 2026 the first year of companywide AI embedding and will overhaul how work gets done across the business. This isn't a pilot. It's a full reset of processes with AI agents built into daily operations.
For HR leaders, the signal is clear: AI moves from tool to workflow. Policy, culture, and capability must keep pace.
What's changing inside HANCOM
The company is rolling out constant AI agent use across development, planning, marketing, HR, and finance. Each frontline department partnered with a dedicated team to select role-specific solutions and has moved into live operations.
- The finance and accounting team uses AI for tax law reviews and cash flow forecasting.
- The planning and marketing team applies generative AI for market research and content creation.
- The HR team introduces AI for organizational culture diagnostics based on data analysis.
HANCOM's approach is "inside-out." Employees use and verify tools first, then the company offers validated solutions to customers. Internal guidelines cover security and protection, including verification of data processing agreements (DPA).
Chief Executive Kim Yeon-su said, "This initiative is not a simple tool rollout but an AI-based transition process that reorganizes how we work overall," adding, "As AI use expands, we plan to adjust the corporate culture as well so that employees can focus on creative, essential value creation instead of repetitive tasks."
Why HR should care
HR sits at the center of this shift. You're responsible for the talent model, culture, governance, and change management that make AI stick.
- Work design: Redefine roles around AI agents. Clarify what the agent does, what the human owns, and how decisions are made.
- Policy and risk: Update AI use policies, DPAs, data retention, model access, and review cadences.
- Culture: Move teams away from repetitive busywork and toward creativity, judgment, and relationships.
- Skills: Roll out targeted training for prompts, QA, data literacy, and agent supervision.
- Measurement: Track time saved, cycle times, quality, compliance issues, and employee sentiment.
How to operationalize AI agents in HR
Think in three tracks: policy, workflow, capability. Keep the loop tight between HR, legal, IT, and frontline leaders.
- Identify high-volume, rules-based tasks first: job description creation, sourcing, resume screening, interview scheduling, ticket triage, pulse surveys, policy FAQs.
- Select agents with risk tiers and human-in-the-loop checkpoints. Log prompts, outputs, and overrides.
- Pilot with clear KPIs: time-to-fill, response time to employee tickets, quality of candidate shortlists, accuracy on policy answers, sentiment coverage from culture diagnostics.
- Set data contracts with IT and vendors: DPAs verified, data minimization, retention rules, role-based access, red-teaming, and bias checks.
- Upskill managers and ICs with short, recurring sessions. Provide prompt templates and review checklists.
Governance and security
HANCOM built internal safeguards around data processing and protection. If you're formalizing your own framework, start with DPAs and clear accountability between controller and processor. See practical guidance from the UK ICO on data processing contracts.
ICO: Data processing contracts
For risk posture and evaluation practices, the NIST AI Risk Management Framework offers a useful structure for mapping, measuring, and improving AI use.
NIST AI Risk Management Framework
What this signals for HR leaders
AI shifts HR from policy gatekeeper to product owner of AI-enabled work. Your edge will come from redesigning processes, building skills, and maintaining trust through transparent guardrails.
If your team needs practical upskilling by role, explore curated options here: AI courses by job.
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