Data Skills Gap Leaves Millions Without Workplace Training
New research by RRC has found that nine in ten workers, equivalent to around 30.9 million people, want to improve their data skills, but that almost half are given little or no dedicated time during the working day to do so. This leaves more than 15 million workers wanting to upskill in relation to their data skills, but unable to access the training they need.
In Brief
Millions of UK workers want to improve their data skills, but many are not being given dedicated time during working hours to access the training they need. Separately, employers are seeing a rise in AI-assisted grievances, creating new challenges for managers who need to identify the substance of complaints and investigate them fairly.
Key Points
- RRC research found that nine in ten workers want to improve their data skills, equivalent to around 30.9 million people.
- Almost half of workers are given little or no dedicated time during the working day for data skills training.
- Data literacy is now expected across many roles, including HR, finance, operations, health and safety, management and administration.
- Poor data literacy can affect reporting, decision-making, record-keeping and the value employers receive from digital systems, reporting tools and AI.
- Employers should treat data skills training as part of workforce development, with role-specific training built into working time.
- Separately, WorkNest research found that 70% of employers had seen an increase in suspected AI-assisted grievances, but only 12% were confident managers could handle complex grievances involving AI-generated content.
Data Skills Are Now a Baseline Workplace Requirement
Data literacy is no longer only relevant to analysts, IT teams or specialist technical roles. Employers increasingly expect workers across HR, finance, operations, health and safety, management and administration to understand, interpret and act on workplace data.
Separate research conducted by YouGov found that 88% of business leaders now regard basic data literacy as essential to day-to-day work, placing it alongside traditional workplace skills such as written communication and project management.
The Cost of Poor Data Literacy
Poor data literacy creates everyday business problems. Reports take longer to prepare, managers may struggle to interpret figures accurately, records can become inconsistent and decisions may be based on incomplete or misunderstood information.
For employers, this matters because workplace technology is only as effective as the people using it. Many organisations are investing in digital systems, reporting tools and AI, but those investments will not deliver their full value if employees lack the confidence or training to understand the data those systems produce.
The issue is therefore not simply a skills gap. It is a productivity and workforce planning issue. Where data skills are now expected across roles, employers need to give employees proper time and support to develop them during the working day.
Closing the Data Skills Gap
Accordingly, the problem is not a lack of appetite for training. Many employees recognise that data skills are becoming more important, but are not being given the time, structure or practical support needed to develop them.
Employers should therefore treat data literacy as part of workforce development, rather than as an optional extra. Training is likely to be most effective where it is role-specific, built into working time and linked to real workplace tasks, rather than delivered as generic learning that employees are expected to complete on top of their normal workload.
For employers, the message is clear. If data skills are now a basic workplace requirement, employees need a realistic opportunity to build them. That means making time for training, supporting managers to reinforce good practice and setting clear expectations about how data should be used in day-to-day work.
AI-Assisted Grievances Create New Challenge for Employers
A WorkNest survey of more than 900 HR professionals and business leaders found that 70% had seen an increase in suspected AI-assisted grievances, with more than a third describing the rise as significant. Yet only 12% of employers said they were confident that their managers could handle complex grievances involving AI-generated content.
The difficulty is not that AI-assisted grievances should be treated as less genuine. Employees may use AI to organise their thoughts, explain events more clearly or understand the grievance process. However, AI can also produce complaints that are lengthy, legalistic and difficult to follow. They may contain inaccurate legal references, broad allegations or procedural language that obscures the real issue.
For employers, the correct approach is to focus on the substance of the complaint rather than the way it has been drafted. Where a grievance is unclear, an initial clarification meeting can help identify the specific allegations, relevant dates, people involved, evidence relied upon and outcome sought.
The rise in AI-assisted grievances reinforces the need for manager training. Managers should know how to investigate fairly, assess evidence, keep accurate records and recognise when HR or legal support is needed. The fundamentals remain unchanged: listen carefully, clarify the issues, investigate properly and respond to the complaint actually being raised.
What Employers Need to Know
Employers need to give employees realistic opportunities to build data skills. They also need to ensure managers are equipped to deal with AI-assisted grievances fairly and effectively.
- Do not assume employees will develop data skills in their own time; build training into working hours where data literacy is now part of the role.
- Make data training practical, role-specific and linked to real workplace tasks rather than relying on generic online learning.
- Review whether employees using digital systems, reporting tools or AI have the confidence and training needed to interpret the data those systems produce.
- Train managers to handle AI-assisted grievances by clarifying the issues, identifying the evidence, keeping accurate records and focusing on the substance of the complaint.
