Artificial Intelligence (AI) now plays a key role in workforce planning, raising the question of how the technology will impact recruitment. From predictive hiring tools and automated interviews to streamlined CV screening algorithms, the technology can reduce admin and speed up the hiring process. However, the conversation goes much deeper than simply admin hours saved. What can AI tell a business about the skills it will need in the future to be resilient and how can that translate into robust training and recruitment plans?
Workplace planning is centred on aligning people with business objectives and strategy. While this has typically relied on existing data, manager intuition and labour forecasts, which tend to lag, AI is changing the process. It enables real-time analysis of talent supply and demand, internal workforce capabilities and external labour market trends. By modelling future scenarios, it gives organisations a gauge of which roles are likely to expand or shrink, which skills will become scarce and where training investments will deliver the greatest return.
Skills based hiring
Conversations around recruitment have largely shifted from ‘jobs’ to ‘skills’. AI has accelerated this shift by scouring for and extracting skills from documents – ranging from job descriptions and CVs to references and performance reviews.
This is hugely advantageous for HR leaders, giving them a birds-eye view of organisational capability in real time, including the transferable skills that match people to designated tasks and projects. Similarly, AI can translate products, programmes and regulatory change into the skills that will likely be required. And finally, it can assist to tailor training and development to close skills gaps more efficiently and effectively than external hiring.
Predictive scenario planning
AI uses predictive analytics and simulation, which models scenarios that will help businesses plan for upcoming workforce needs.
Machine learning can forecast attrition and internal mobility by role, location and skills cluster based on market trends, salary competitiveness and engagement levels.
Similarly, simulations can allow HR teams to test scenarios. For example, how would the introduction of a new piece of regulation increase compliance workload and what would the implications be on talent, cost and time.
It can also enable companies to optimise their hiring process and instruct whether they should hire, upskill or hire secondments or contractors to be the most efficient. To do this, it will compare cost, time-to-productivity ration, quality and risk across each different option, allowing HR teams to present the strongest business case.
For instance, a local council adopting low-code automation could leverage AI to pinpoint employees with related skill sets. Rather than relying solely on hiring new developers, HR can combine targeted training for current staff with a small group of contractors for more intricate integrations. This approach reduces costs while enhancing internal knowledge retention.
Providing access to fair opportunity
Often, employers fail to consider the full potential of their existing workforce, prioritising prior experience, which leads to internal candidates missing out on the best opportunities. AI can bridge this gap, recommending candidates based on their existing skills rather than job history, and suggesting stretch projects which would develop their skills. Additionally, AI can act as a career coach by suggesting roles employees could work towards with targeted learning – increasing internal mobility and talent retention.
In the retail industry, for example, AI could be used to discover store managers with data skills, who could second to a forecasting or analysis role during peak periods. In this case, employers are remaining efficient by reducing external hiring and improving future management.
Another example comes from the legal sector, where a firm could implement AI-powered contract analysis and compliance automation. AI could anticipate demand for technology-focused paralegals and compliance analysts, while also recommending reskilling pathways that help existing employees transition into legal technology roles. This approach reduces workforce risk and minimises the need for costly external recruitment.
How businesses can act now
Employees should be working in tandem with AI, rather than resisting against it. To allow them to strike this balance, organisations need to be both proactive and strategic, beginning with investing in skills mapping and analytics, auditing internal skill inventories, identifying gaps and forecasting future needs. This means that workforce planning will be driven by data, rather than intuition.
Alongside the implementation of AI for recruitment purposes, the role it can play in supporting the employees’ continuous learning should be prioritised. AI-powered platforms can deliver tailored training plans, which makes upskilling and reskilling an integrated part of career development rather than an additional benefit. Employers should also consider redesigning job roles around uniquely human strengths, so that AI integration is focussed on augmenting people, rather than replacing them. This will increase the value of the roles that rely on intrinsically human skills – judgement, creativity and emotional intelligence.
Ethical considerations also need to be made when it comes to AI-driven hiring and workforce decisions. Putting in place guidelines and policies that ensure transparency, bias and human accountability is key. Organisations can strengthen their resilience by promoting internal mobility, leveraging predictive AI insights to redeploying employees into emerging roles. This will both reduce turnover and improve retention. Finally, by working collaboratively with training providers, educational institutions and industry groups, organisations can help shape curricula and align talent pipelines with the skills that are required.
AI has the potential to reinvent workforce planning, shifting it from an infrequent, static process into an adaptive, continuously evolving model. By leveraging AI, organisations can accelerate skills development, make smarter talent deployment decisions, and enable fairer, more inclusive career pathways across the enterprise.
