Resource Hub
The LDI Resource Hub
The LDI Resource Hub
What is Artificial Intelligence?
AI is sophisticated technology that involves a wide variety of technological advancements focused on a vareity of tasks.
Learn MoreWhy is AI Literacy Important?
AI literacy builds confidence, ethics, and effectiveness in digital environments.
Learn MoreWhat Views Exist on the AI Spectrum?
Views range from fear and skepticism to innovation and trust.
Learn MoreWhy Do Organizations So Often Fail to Upskill Employees?
Reasons Why Organizations Fail to Train
Learn MoreWhy A New Workforce Readiness Model is Neceaary
A new workforce readiness model for the age of AI is essential because blending technical and human capabilities is the new frontier of work.
Learn MoreWhy a New Workforce Readiness Model for the Age of AI Is a Necessity
1. Automation Is Reshaping Every Role
Response: AI and automation now affect nearly every occupation, demanding continual reskilling across technical, analytical, and interpersonal domains. Traditional education pipelines cannot adapt fast enough to the pace of change.
Source: World Economic Forum, The Future of Jobs Report 2025 — View report
2. Skills Half-Lives Are Shrinking Rapidly
Response: The average “half-life” of job skills has fallen below five years, meaning today’s competencies lose market value faster than ever—requiring models built for lifelong, modular learning.
Source: Deloitte Insights, 2025 Global Human Capital Trends — View report
3. Employers Face Historic Talent Gaps
Response: Nearly 60% of employers report difficulty finding workers with the right mix of digital and human skills, signaling the need for readiness frameworks that connect education and employment more fluidly.
Source: ManpowerGroup, Talent Shortage Survey 2025 — View survey
4. Human Skills Remain the Competitive Edge
Response: As AI automates routine work, critical thinking, collaboration, and ethical decision-making define the new baseline of employability—requiring models that blend technology with humanity.
Source: McKinsey & Company, Defining the Skills Citizens Will Need in the Future World of Work — View article
5. Equity Gaps Are Widening
Response: Without intentional upskilling frameworks, AI adoption risks deepening inequality among workers lacking digital access, training, or credentials recognized by employers.
Source: Brookings Institution, Building a More Inclusive Future of Work — View analysis
6. Employers Need Agility, Not Static Credentials
Response: Static degree models no longer meet evolving skill needs. Readiness frameworks must emphasize agility, adaptability, and just-in-time credentialing aligned to emerging technologies.
Source: IBM Institute for Business Value, AI and the Workforce of the Future — View report
7. Policy and Industry Standards Are Converging
Response: New U.S. and international workforce initiatives tie funding to measurable readiness and skills outcomes—necessitating updated frameworks that align learning design with economic mobility goals.
Source: U.S. Department of Labor, AI and the Workforce Initiative (2025) — View site
8. Continuous Learning Is Becoming a Workplace Standard
Response: Organizations that embed lifelong learning outperform peers in innovation, retention, and adaptability—making structured readiness models a strategic imperative, not an HR perk.
Source: LinkedIn Learning, Workplace Learning Report 2025 — View report
9. Responsible AI Adoption Requires New Ethics Skills
Response: As AI decisions affect hiring, finance, and education, professionals need literacy in ethics, bias, and governance—areas absent in most legacy workforce models.
Source: UNESCO, Recommendation on the Ethics of Artificial Intelligence — View recommendation
10. Readiness Models Anchor Regional Competitiveness
Response: States and universities adopting new readiness frameworks strengthen local economies, attract employers, and future-proof their labor force against automation shocks.
Source: National Governors Association, State Roadmap for the Future of Work and AI — View roadmap