The IT workforce stories enterprise IT leaders actually read.
Volume 341, Issue 4 · 9 articles from 5 issues
Post-launch HCM support needs clear ownership, issue tracking, training and vendor planning to sustain adoption.
An HCM implementation continues well beyond go-live, requiring HR and IT teams to field employee questions, resolve defects, manage permissions and support integrations.
Real-world adoption often reveals gaps in self-service tools, approvals and workflows that testing did not surface.
Priorities include defining system ownership, ensuring adequate resources and documentation, establishing issue tracking, maintaining audit compliance, budgeting for vendor support, aligning with HR business cycles, providing ongoing training, allocating dedicated post-go-live support and assigning clear module and process ownership.
Seven change-management essentials for driving adoption of new HR software beyond go-live.
The article argues HR software adoption challenges extend well past go-live and require change management across seven areas.
These are detailed planning covering communication, training, and post-launch ownership; visible leadership support that connects rollout to business outcomes; audience-specific communication for employees, managers, and technical teams; documented approval workflows to avoid delays; comprehensive role-based training; change champions among respected employees; and clear policy communication before system use.
The piece stresses treating change management as an ongoing adoption program rather than a one-time launch event.
AI-driven data center expansion is creating urgent demand for power, liquid cooling and infrastructure skills.
Organizations face critical talent shortages in data center roles as AI infrastructure demands expertise beyond traditional IT operations.
Business risks include delayed AI deployments, increased cybersecurity vulnerability and rising labor costs.
Leading organizations adopt multi-pronged strategies that combine automation, workforce development through training and apprenticeships, and partnerships with managed service providers. The goal is building resilient teams rather than competing for a small pool of already-scarce specialists.
Organizations that encourage employees to ask the questions AI can’t answer will thrive, writes SurveyMonkey’s CPO.
SurveyMonkey's Chief People Officer Becky Cantieri argues that organizations are inadvertently discouraging early-career employees from asking questions by creating cultures that reward confidence over curiosity.
Research shows nearly half of Gen Z workers feel pressure to already know answers, and many withhold questions from fear of seeming unprepared. As AI makes instant answers accessible, companies risk losing the collaborative learning and dialogue essential for developing leaders.
Cantieri emphasizes that admirable leaders ask questions regularly and create safe spaces for discussion, recognizing that asking tough questions and admitting uncertainty drives better decisions.
With AI engineering demand growing 69% annually, companies turn to vetted talent marketplaces like Fiverr Pro, Andela, and Upwork.
The article addresses a worsening shortage of AI engineers in a market where AI-skilled roles expand far faster than general employment.
Traditional recruiting has proven too slow for organizations racing to move AI projects from experimentation into production.
It reviews five leading hiring platforms serving different needs, from Fiverr Pro's pre-vetted specialists for rapid deployment to Andela's focus on long-term distributed teams.
Key selection criteria include vetting rigor, onboarding speed, security compliance, and whether the engagement model supports project-based or permanent work.
The conclusion is that no single platform fits every scenario, though Fiverr Pro stands out for enterprises needing pre-screened engineers quickly.
Tech job postings grew for a sixth straight month as software development roles recover, driven largely by AI implementation needs.
Technology employment is growing again as employers increase investment in digital transformation and AI capabilities. CompTIA's Tech Jobs Report notes hiring ramping up across non-tech sectors including finance, manufacturing, and defense.
Software development roles remain below pre-pandemic levels, but postings are up 15% since February 2025.
Notably, 71% of new positions target senior-level talent with AI expertise, raising concerns about entry-level opportunities.
IT leaders must navigate how automation is reshaping career progression and ensure junior developers are not left behind during the recovery.
A learning management system can centralize training, support compliance, improve access, provide learning data and help HR scale employee upskilling and reskilling programs.
A learning management system helps organizations manage training for compliance, onboarding, and career development by serving as a central repository for diverse learning content.
LMS platforms improve convenience through web and mobile access, offer strategic insights via reporting and analytics capabilities, and support upskilling and reskilling initiatives through microlearning and blended formats.
The systems provide assessment tools and feedback mechanisms while scaling efficiently as organizations grow. HR leaders maximize LMS value by connecting training data to business priorities and ensuring employees can find relevant content easily.
A Stanford study cited by Computerworld finds AI has cut entry-level hiring for workers aged 22-25 by 19%.
Computerworld covers a Stanford University study using anonymized ADP payroll data comparing employment in AI-exposed versus less-exposed occupations. Among workers aged 22-25, employment in AI-exposed jobs is now 19% lower than in low-exposure roles, up from a 13% gap the prior year.
The effect concentrates on reduced hiring of young, entry-level workers rather than layoffs of experienced staff, and is sharpest where AI can fully replace specific tasks rather than merely supplement human work, while employment among older, more experienced workers shows minimal disruption.
With AI and cybersecurity talent scarce, CIOs are advised to build internal talent pipelines rather than compete for scarce external hires.
Grant Gross reports that AI, cybersecurity, and data science top CIO.com's State of the CIO survey list of hardest-to-fill roles, with poor hiring risking technical debt, delayed transformation, and staff burnout.
Experts recommend building AI capability internally since 'the market for pure AI specialists is volatile and expensive,' broadening geographic hiring and prioritizing demonstrated skills over credentials, and building talent communities ahead of need since 'by the time an AI engineer... hits the open market, every company is competing for the same person.'