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The role of AI in workforce cost forecasting and the financial leadership shift toward horizontal planning

November 12, 2026
Sara Maginn Pacella

Workforce cost forecasting is evolving. What was once a top-down, siloed exercise from the financial arm of an organization’s executive is transforming into a more collaborative and dynamic human-centred competitive advantage, in part, and somewhat ironically, thanks to AI financial forecasting.

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The basics of workforce planning

 

Workforce planning is the practice of ensuring organizations have hired the right people with the right skills to meet current and future strategic goals. This includes planning for workforce retirement, attrition or other factors that impact a company’s turnover. Many in the field tout best practices for workforce planning that involve looking 18 months to five years into the future; however, this doesn’t always happen in practice. A recent Korn Ferry survey reveals “35 per cent of Chief Human Resources Officers say future workforce needs are being overlooked as short-term pressures dominate—making strategic workforce planning more critical than ever.”

What are the benefits of AI-powered workforce planning?

Software for AI workforce planning can improve workforce cost forecasting by providing the following:

  • Accurate company rosters
  • Deeper understanding and analysis of workforce data, leading to data-driven decision-making
  • Predictive forecasting using historical data
  • Improved, competitive alignment of salary and compensation within the industry
  • Reduction of redundancies and staffing costs
  • Improved productivity
  • Employee skill-mapping

Using AI workforce prediction for generational trends

One example of the effective use of AI tools for workforce forecasting is its ability to provide predictive analysis of delayed retirement. For three decades, delayed retirement has become a critical issue for those dealing with succession planning, business cost forecasting and workforce strategy. Katie Horne, a savings export at Flagstone, told Pension Age Magazine, that “A workforce that retires later than planned is a workforce that costs more than planned. Finance teams that aren’t already modelling this risk may find themselves caught out.” Flagstone adds, “The businesses that will navigate this best are the ones that treat retirement planning as a financial risk to manage now, not a people issue to deal with later.”

AI platforms can use predictive attrition and headcount modelling to accurately forecast retirement-related workforce changes, spot talent gaps and help preserve institutional knowledge. HRTech SaaS recently provided a list of the 10 best AI people analytics platforms for workforce planning in 2026, including Culture Amp, Lattice, One Model, Visier and more.

The shift to horizontal workforce planning

Disconnects between senior management and their teams can create gaps in talent strategies. Human capital management leaders understand that horizontal workforce planning, rather than the traditional top-down model, supports a collaborative, cross-functional approach to talent management. Research conducted by the American Productivity and Quality Center suggests a lag in the application of horizontal planning, finding “49 per cent of strategic workforce plans are either designed to be top-down or are not integrated across divisions and regions within the enterprise.” The implementation of horizontal workforce planning aims to address this.

Horizontal workforce planning in practice

Deloitte provides the example of Network Rail (an organization well known for its active use of AI analytics) using horizontal workforce planning to address talent gaps amid high turnover among train signalers and a 12-month lead time for recruiting, hiring and training new staff. They addressed this issue by using multiple qualitative and quantitative data sources, including input from managers and train signalers. It then created “a cross-disciplinary team—one with representatives from HR, operations, finance, training and local and national trade unions—to develop a workforce planning approach that better anticipated talent requirements.” This resulted in a 50 per cent reduction in the time required to recruit, hire and train new signalers. Network Rail expects that this new process will also reduce the need to pay signalers “premium hour” rates to cover staff shortages, leading to projected savings of £1.2 million (roughly C$2.27 million) over three years.

How does AI fit in with horizontal planning practices?

McKinsey & Company notes that top performers and forward-thinking organizations understand the importance of talent management and regard talent management with the same attention as their financial capital. AI-powered workforce planning software can compile data to ensure collaborators in the process speak the same language, enabling them to make data-driven decisions. It can also engage in scenario planning to guarantee recommendations that best reflect organizational strategies.

Organizations that effectively combine AI capabilities with cross-functional collaboration can expect to see a competitive advantage within their industry and beyond.

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