A company can invest in security software, document its policies, and establish reporting procedures while leaving an important source of exposure largely unaddressed: how employees understand the technology they use every day.
Consider an employee sharing a project folder with an external partner. The platform is approved, the employee has legitimate access, and the task serves a business purpose. However, selecting an unrestricted sharing option instead of named recipients may expose information beyond the intended audience.
The weakness sits in the gap between having control and knowing how to use it.
For risk leaders, that gap deserves attention. Digital literacy influences how people manage information, interpret system prompts, use artificial intelligence, and respond when technology behaves unexpectedly. It should therefore be treated as an operational capability within enterprise risk management.
Everyday Technology Decisions Create Business Exposure
Employees make small technology decisions throughout the working day. They approve application permissions, download attachments, connect services, share documents, and decide whether an unusual notification requires action.
Individually, these choices can appear insignificant. Their consequences depend on the information, access, and business processes involved.
Imagine a sales team adopting a browser extension to accelerate prospect research. Before approving it, the organisation needs to understand what the extension can access, whether it receives customer information, and who will monitor its continued use.
The relevant risk question extends beyond whether the tool performs its advertised function. It also concerns the permissions and dependencies introduced into the business.
A digitally informed employee is better equipped to recognise when a routine action needs further review. That judgement gives formal approval processes a stronger foundation.
Translate Policies Into Recognisable Decisions
Policies establish expectations, but employees still need to apply those expectations inside software interfaces.
An instruction to “protect confidential information” leaves several practical questions unanswered. Can a document be shared through a public link? Is a personal account acceptable for transferring a large file? May customer information be pasted into an AI assistant?
Training becomes more useful when it explains the decision at the point where an employee encounters it.
For example, a document-sharing exercise can ask employees to select an appropriate access setting for three situations: an internal project, a client review, and a public announcement. The discussion can then cover who should have access, whether editing is necessary, and when access should expire.
This approach also reveals usability problems. If employees repeatedly misunderstand a setting, the organisation may need clearer instructions, safer defaults, or a simpler workflow.
Support Learning With Accessible Technical Resources
People do not always need a lengthy training course. Sometimes they need a clear explanation of a browser setting, an application feature, or an unfamiliar software function.
For general technology learning, resources such as OTechWorld publish practical tutorials and guides covering browsers, Windows, applications, and other everyday digital tools. Such material can supplement internal learning by helping employees become more familiar with the interfaces they use.
Organisations should connect that general understanding to their own requirements. A public tutorial may explain how a feature works, while internal guidance specifies whether it is approved, which information it may handle, and when assistance is required.
A useful internal knowledge base can combine short approved instructions with carefully selected supporting resources. Each entry should answer a specific workplace question and identify the team responsible for keeping the guidance current.
Extend Digital Literacy to AI-Assisted Work
AI changes what employees need to evaluate. A conventional application may display an obvious error message. An AI assistant may instead return a fluent, confident response containing incorrect information.
NIST’s Generative AI Profile identifies risks including confidently false output, data privacy exposure, and overreliance on AI systems. These issues make employee judgement an essential consideration when introducing AI into business processes.
Practical AI literacy should help employees distinguish between generating a draft and verifying a result.
Consider a customer service employee using AI to prepare a reply. The output may be well written while misstating a refund condition or promising an unavailable service. The employee needs to check the response against approved information before sending it.
Training should establish clear boundaries around:
- The information employees may enter into approved AI tools.
- The outputs that require verification against original sources.
- The actions that require human approval.
- The process for reporting unexpected or misleading results.
Those boundaries should reflect the task. Brainstorming an internal meeting title requires a different level of oversight from producing a customer-facing explanation of contractual terms.
Tailor Training to Roles and Responsibilities
A single awareness presentation cannot address every technology decision across an organisation.
Finance teams encounter payment instructions and account changes. Human resources teams handle sensitive employee records. Marketing teams manage publishing permissions and external applications. System administrators control access that may affect multiple departments.
Build learning around realistic situations within each role.
For a finance team, a scenario could involve a supplier requesting a change to payment details through a familiar email thread. The exercise should test whether employees follow the established verification process.
For a marketing team, the scenario might involve granting an external agency access to a social media account. Employees should understand the appropriate permission level, the approval route, and how access will be removed when the engagement ends.
The purpose is to practise the decisions people actually make.
Measure Whether Employees Can Apply What They Learn
Training completion confirms attendance. It provides limited evidence that employees can recognise and manage a risky situation.
Risk teams can develop more useful measures by examining specific tasks. Can employees choose the appropriate sharing setting? Can they identify where to report an unexpected access request? Can they verify an AI-generated claim using an approved source?
Interpret the results carefully. An increase in reported mistakes may indicate stronger reporting confidence rather than declining performance.
Combine assessment results with employee feedback and operational observations. If a task repeatedly causes confusion, investigate the interface and workflow as well as the training.
These findings should lead to a concrete response, such as revising instructions, changing a default setting, or simplifying an approval process.
Give Digital Capability a Clear Owner
Digital literacy requires coordination across risk management, IT, human resources, and operational teams.
Risk leaders can identify the decisions with the greatest business consequences. IT can explain system behaviour and configure safeguards. Learning teams can turn those requirements into accessible exercises. Department managers can reinforce them through daily work.
NIST’s Cybersecurity Framework 2.0 offers a useful organisational reference through its Govern, Identify, Protect, Detect, Respond, and Recover functions. Employee learning can be connected to the relevant responsibilities within that structure.
Start with one important workflow. Identify the decisions employees must make, observe where uncertainty arises, and provide targeted support. Review the guidance when the underlying application or process changes.
That gives digital literacy a practical place in enterprise risk management: a maintained capability, with accountable owners and evidence that people can apply it.