Artificial Intelligence (AI) and automation are changing how work is done across industries. From warehouses and manufacturing environments to recruitment, administration and customer service, technology is increasingly becoming part of everyday operations. But investing in new systems does not automatically translate into greater productivity.
The real test is whether employees are prepared to work alongside these technologies. Businesses that introduce AI without developing their people risk creating a gap between what the technology can do and what their workforce is equipped to deliver.
Technology alone cannot deliver productivity
The success of AI depends heavily on workforce readiness. Employees need to understand the systems they are expected to use, how to interpret outputs and when human judgement is still required.
When this preparation is missing, the warning signs can appear quickly. Employees may avoid new systems, develop manual workarounds, make repeated errors or rely heavily on support teams. Instead of improving productivity, technology can create additional complexity.
This is where Temporary Employment Services (TES) providers can support businesses. By considering digital readiness alongside traditional skills and experience, TES providers can source and prepare people who are able to work confidently with new systems from their first day. They can also help clients spot readiness gaps early, back up the skills and standards each role requires, and keep developing workers as roles and operating models change.
Building skills for an AI-enabled workplace
Digital literacy is becoming a basic workplace requirement. Employees increasingly need confidence using digital platforms, data tools and automated workflows, while understanding both the capabilities and limitations of AI.
In some roles, prompt literacy and the ability to verify AI-generated information will also become important. However, training must remain relevant to the actual job.
A warehouse operator using AI-supported scanning or routing technology, for example, does not need to become an AI specialist. They need to understand how to use the device, interpret instructions, identify unusual outputs and know what to do when the system does not behave as expected. This also means training cannot be treated as a once-off exercise. As technology changes, skills development must continue with it.
Keeping people accountable for decisions
Greater automation must also be matched by clear governance. Businesses need to determine where AI can support decision-making and where human approval remains essential.
This becomes particularly important when technology influences recruitment, pay, disciplinary processes, safety, privacy or other decisions that can affect people’s livelihoods.
Employees should know how automated decisions are reached, when an outcome should be questioned and who remains accountable. Phased implementation, clear communication and documented oversight can help businesses identify problems before they become embedded in operations.
Measuring more than technology adoption
The success of AI should not simply be measured by whether employees are using a system. Businesses should consider whether it improves accuracy, productivity, service levels, safety and quality, while also measuring how effectively employees are adapting.
Reskilling should also lead somewhere. Employees who develop stronger digital capabilities should have opportunities to move into positions such as team leaders, system champions, analysts or technology-support roles.
Recruitment strategies will consequently need to evolve. Adaptability, judgement and willingness to learn may become just as important as existing technical experience.
Preparing people for changing work
AI and job creation should not automatically be treated as opposing forces. In many cases, technology will change the nature of a job rather than remove it entirely. The challenge is ensuring that workers can change with it.
This is where TES providers have an important role to play by helping businesses build adaptable talent pipelines and preparing workers before they enter increasingly technology-enabled environments.
Businesses cannot control every way AI will reshape work, but they can control how they prepare their people for that change. Organisations that invest in technology while equally investing in skills, communication and responsible implementation will be better positioned to improve productivity without leaving their workforce behind.
