MGNT7840 · People Management

Evidence-Based AI Skills Training

Enhancing job satisfaction among administrative staff in manufacturing

Class Share 01 / 05
The problem · Why now

Technology is moving faster than training.

General, one-off and tool-focused training can feel like extra work—not real support.

01

Replacement anxiety

“Will AI make my experience less valuable?”

02

Familiar ways of working

Established routines can make new tools feel unnecessary.

03

No time to learn

Busy administrative work turns training into another demand.

Digital transformation is also a people-management issue. 02 / 05
Our analytical logic

Training design should improve the work experience.

INPUT

Employee-centred training

Relevant, paced and supportive

PSYCHOLOGY

Confidence & autonomy

Employees feel capable and in control

WORK

Less repetition & stress

AI supports real tasks and reduces burden

OUTCOME

Job satisfaction

A better daily experience—not only more output

Manufacturing administrative staff are the main group; experienced employees are a priority subgroup.

Productivity alone is not the outcome. 03 / 05
Our recommendation

A three-stage path from awareness to continuous improvement.

01

Build awareness

Understand

Explain AI trends, its supportive role and essential skills. Reduce uncertainty before complex tool training begins.

02

Run job-based pilots

Apply

Connect AI to specific administrative tasks. Let employees experience real time savings and practical value.

03

Track and adapt

Improve

Use employee questions, feedback and work outcomes to continuously refine future training.

Awareness → Application → Adjustment 04 / 05
Evidence · Challenge · Key message

Evidence before assumptions.

Course theoryMotivation, job satisfaction and stress
Academic studiesEmployee learning and technology use
Industry evidenceManufacturing and training trends
Pilot feedbackEmployee voice and work outcomes
Technology and people management should progress together. 05 / 05