The IT workforce stories enterprise IT leaders actually read.
Volume 342, Issue 4 · 9 articles from 4 issues
Layoffs create hidden 'capability risk' by wiping out undocumented expertise and institutional knowledge.
Andy Patrizio examines how layoffs create capability risk: the loss of specialized expertise and undocumented tacit knowledge that erodes long-term performance even as it cuts short-term costs.
Unlike immediate savings, capability risk emerges gradually, making it easy for leadership to overlook.
Key exposure areas include specialized technical skills, legacy system maintenance, key-person dependencies, and institutional memory about past design decisions. The article recommends identifying critical capabilities before layoffs, documenting procedures and exceptions, cross-training, succession planning, and building dynamic knowledge repositories to protect against capability erosion.
6 Steps HR Teams Should Follow to Clean Data
Clean HR data is essential for analytics, compliance, and performance management. CHROs can improve data quality through AI analysis, conducting audits, implementing interfaces between systems, and using picklists and default values to reduce entry errors, plus establishing mandatory training for data entry personnel.
The article emphasizes that requiring approval for employee changes and limiting data entry access helps prevent mistakes. Gamification can encourage employee participation in data cleanup initiatives.
78% of HR leaders fear AI automating entry-level work is eroding the pipeline for developing future managers.
A Talogy survey found 78% of senior HR and talent leaders worry that AI automation of entry-level tasks is undermining leadership pipeline development, as fewer early-career roles mean fewer organic learning opportunities.
Nearly a third of employees report they cannot function without AI assistance, and leaders fear workers use AI to mask competency gaps rather than build real skills.
The article urges HR to implement intentional development strategies focused on critical thinking, adaptability, collaboration, and emotional intelligence starting early in careers, rather than only teaching AI tool usage.
AI in HR should automate activity but never accountability, making AI-led HR transformation a CEO-level agenda.
The author argues that HR, not sales or finance, may be the true test of a CEO's AI leadership because it touches hiring, pay, performance and job security directly.
AI can act as a catalyst across recruitment, payroll anomaly detection, compliance and employee support, but it cannot fix broken processes or fragmented data.
Leaders should start with the business problem, build a connected digital HR foundation, then layer AI on top. The future HR function should combine a digital foundation, AI for high-volume work, and a human layer that owns judgement, fairness, exceptions and culture.
CIO Eduard de Vries Sands argues developing leaders is a deliberate discipline built on handing off real work with a safety net.
IT executive Eduard de Vries Sands writes that the systems he built are mostly gone, but the people he developed now run their own functions.
He deliberately leaves "white space," giving capable staff bounded, real decisions while staying close enough to catch failures, and limits how big a mistake can get.
He recounts a vendor-managed migration where he misjudged a manager's readiness, then took the heat and moved go-live a month.
Delegating freed his own capacity for high-value work such as acquisition due diligence, and his proteges have gone on to senior roles elsewhere.
A pay gap is emerging as workers want compensation for AI skills that many employers still treat as a baseline expectation.
Ginger Christ reports on a growing disconnect between employers and employees over pay for AI skills: nearly 25% of companies treat AI fluency as an unpaid baseline expectation, while over half of workers believe they deserve more pay for developing it.
Payscale research warns of a "retention time bomb" as existing employees see new hires earn 20-40% pay premiums for tech skills they lack recognition for.
While 61% of employers rewrote job descriptions for AI, fewer than half adjusted salaries, and over 40% struggle to find workers with needed AI skills.
Despite 58% of companies planning AI pay premiums, misalignment threatens retention.
Most fraudulent employees receive corporate access before organizations detect the fraud.
According to HYPR's hiring fraud report, 98% of fraudulent hires obtain company credentials before detection, exploiting a 90-day gap between hiring and onboarding.
While 98% of HR leaders report experiencing candidate fraud, only 53% of threats are detected by automated tools, with manual discovery catching the remainder.
Organizations average 2.2 disconnected detection checkpoints across fraud incidents, revealing fragmented security practices.
The report identifies ownership gaps between HR and IT as a critical vulnerability window attackers exploit to gain system access.
Organizations should reinvest AI productivity gains into growth rather than cutting staff.
When AI makes teams more productive, using those gains to reduce headcount is strategically shortsighted.
Drawing from manufacturing lean principles, author Niel Nickolaisen argues that freed-up capacity should fund new initiatives such as deeper customer relationships, innovative products, or proactive strategies, rather than cost-cutting.
Success requires making capacity visible, allocating it purposefully before deployment, training teams to identify opportunities, and protecting gains from budget recovery pressure.
HR teams should automate employee data flows across systems instead of manually re-entering data at every step.
The article argues HR departments waste effort manually re-entering employee data into separate systems such as ATS, HRIS, payroll, ERP, and identity management platforms as employees move through hiring, promotions, transfers, and offboarding. This manual approach creates repetitive work, inconsistency, and error risk, and forces HR workload to grow with headcount.
Automating data movement so information is entered once and flows to all dependent systems reduces administrative burden, improves consistency, and frees HR to focus on strategic work while still retaining oversight and decision authority.