Global Skills Supply & Demand: Mapping The Future Of Work With AI

Kirsty Cooke

The global workforce is changing faster than many organizations can track. According to the World Economic Forum, trends in technology, the economy, demographics and the green transition are projected to generate 170-million new jobs by 2030 – while displacing 92-million others. This rapid evolution requires a more sophisticated approach to workforce planning.

Headcount and job titles alone no longer tell the full story. Organizations need to understand the actual tasks people perform, the skills required to complete them, and how these intersect with broader labor market trends.

Workforce Intelligence – powered by ethical AI – provides the visibility to navigate this complexity.

What Do We Mean by Skills Supply & Demand?

Skills supply represents the capabilities available within the workforce, including current skills, certifications and experience, as well as the skills available in the wider talent pool. Skills intelligence has formed the basis of workforce planning for many forward-thinking companies for some years now – but it’s not quite enough on its own.

Skills demand is determined by the work that needs to be done: the tasks that make up each role. Every task requires specific skills, and as tasks evolve, so does the demand for the skills needed to complete them. Task intelligence reveals how work actually flows through an organization: how often it happens, how much effort it takes, where duplications occur, and what’s ripe for automation. It provides the operational context that skills data alone cannot.

By analyzing task demand as well as skills supply, organizations are better placed to anticipate emerging skill gaps, target reskilling and upskilling initiatives, and deploy talent more effectively – shifting workforce planning from reactive to proactive.

The Forces Shaping Global Skills Imbalances

Several trends are reshaping global skills supply and demand. According to the World Economic Forum Future of Jobs Report 2025 there are “five key factors that will drive a net creation of 78 million jobs globally by 2030”: technological changes, the green transition, demographic shifts, geoeconomic fragmentation, and economic uncertainty.

Automation is a key “technological change”. As AI helps us perform more and more routine tasks, many roles are changing rapidly. Accenture estimates that 44-% of U.S. working hours are in scope for automation or augmentation, while 82% of leaders say they’re confident that they’ll use digital labor to expand workforce capacity in the next 12–18 months (Microsoft).

As well as giving us “digital colleagues to manage”, AI is creating new task categories – from prompt engineering to AI governance. There are skills gaps emerging in terms of using AI, but there is also significant demand for inherently human skills such as creativity and problem-solving.

Understanding these changes through a dynamic model of “skills supply and demand” is essential.

Why Traditional Labor Data Isn’t Enough

Labor market reports and static job taxonomies provide historical context, but cannot keep pace with rapidly changing tasks or emerging skills.

Only 38-% of C-suite executives are satisfied with how well people data integrates with business performance (SAP) – highlighting the gap between available data and actionable insight.

AI-driven Workforce Intelligence combines internal HR data, workforce profiles, job descriptions, learning histories and external labor market insights to provide a rich, continuously updated, actionable view of skills supply and demand.

How To Build An AI-Ready Workforce Model

Building an AI-ready workforce model means moving beyond static roles to a dynamic, task- and skills-aware view of your organization – one that connects internal capabilities with external market demand, and guides actionable workforce decisions.

Map existing skills supply: Analyze your current workforce to understand which skills exist, where they are concentrated, and where gaps may appear. AI can harmonize and standardize employee data from a range of HR systems for a clear view of internal capabilities, and even infer skills from unstructured data such as resumes.
Infer tasks and role requirements: Apply AI to job descriptions to determine the tasks performed in each role.
Connect tasks to skills and market demand: Overlay external labor market intelligence to see where skills are abundant, scarce, or emerging globally. AI can continuously reconcile internal capabilities with external demand signals.
Unify workforce and market data: Integrate HR tools, learning systems, and project data with external labor market insights. This consolidated view highlights skill gaps, mobility potential, and reskilling priorities across functions, regions, and markets.
Model scenarios with a digital twin: Create a virtual representation of your workforce, including roles, tasks, skills, and headcount. Use AI to simulate potential changes – such as automation, redeployment, or hiring – to understand their impact on global skills supply and demand.
Identify gaps and prioritize action: Compare internal skills supply to projected task-based demand. Detect critical shortages, surplus capacity, and high-priority reskilling areas. Translate these insights into targeted programs: internal redeployment, upskilling, or strategic hiring.
Forecast future skills needs: Anticipate how trends such as AI adoption, automation, demographic shifts, and industry transformation will impact tasks and required skills. AI-driven forecasting allows organizations to prepare for emerging roles and capabilities.
Operationalize and continuously update: Present insights in dashboards and decision-making tools for HR, finance, and business leaders. Continuously refresh the data, monitor emerging skills, and adjust planning as market conditions and organizational priorities evolve.
Engage employees and foster transparency: Communicate about opportunities, reskilling programs, and AI recommendations. Encourage participation and transparency to build trust, adoption, and a culture that values skills-first thinking.

The Beamery Framework for Skills Supply & Demand

Beamery’s Workforce Intelligence Suite delivers a continuously updated, data-driven view of the workforce ecosystem. It is built on three interdependent pillars:

Skills Intelligence: Maps workforce capabilities and their evolution over time. Integrated with HRIS, learning and performance systems, it highlights where skills exist, where gaps may appear, and what capabilities will be needed in the future.
Task Intelligence: Uses AI to establish the discrete tasks behind every role. By analyzing effort, frequency and importance, organizations can identify which tasks can be automated, redeployed or require new skills.
Talent Market Insights: Combines external labor market data to reveal supply-demand patterns, emerging skills and evolving role requirements, enabling benchmarking, proactive hiring and strategic mobility.

These pillars feed into a digital organizational twin, a virtual model of roles, tasks, skills and headcount. Leaders can simulate “what-if” scenarios, test reskilling strategies, and visualize the impact of automation or shifting demand – all before taking action.

Use Cases and Insights

Predicting Emerging Skill Shortages: A global manufacturer may spot that 80-% of key automation-related tasks are concentrated in just 15-% of roles, enabling targeted reskilling before gaps widen.
Identifying Global Reskilling Priorities: A financial services firm would be able to map thousands of critical tasks to future skill demand, uncovering data literacy and AI governance training as top priorities.
Informing Strategic Workforce Mobility: A technology company could apply task-level visibility to redeploy talent across regions, reducing external hiring by 20-% while increasing productivity.

Organizations leveraging Beamery’s Workforce Intelligence framework see measurable results. A pharmaceutical company found that 30% of its tasks were automatable, while a financial services client discovered significant task duplication across departments. Beamery helps enterprise organizations not just spot opportunities, but implement changes quickly, ensuring employees are placed where their skills can drive the most value.

Traditional Forecasting vs. AI-Driven Workforce Intelligence

Traditional forecasting relies on static roles and historical reports. AI-driven Workforce Intelligence is dynamic, predictive and task-aware, enabling organizations to:

Model how automation will impact specific tasks, roles and teams
Identify emerging or declining skills in close to real time
Simulate workforce scenarios and forecast skill gaps
Plan reskilling, redeployment and hiring proactively
Promote fairness and reduce bias by grounding workforce decisions in data.

The global skills landscape is in constant motion. Organizations that see beyond roles and job titles – understanding the work that actually needs to be done and the skills to do it – are the ones that thrive.

Beamery’s Workforce Intelligence Suite gives HR and talent leaders a complete view of both skills supply and the demand driven by tomorrow’s tasks. The result is smarter, fairer, more agile workforce planning – and a more resilient organization ready for the future of work. Learn more.