Foundation program

AI Productivity Training for Employees

Practise AI-assisted writing, meetings, reporting and research while measuring review effort and protecting work quality.

Discuss this training

The practical answer

What does this program cover?

AI productivity training helps employees apply AI to repeatable work such as preparing drafts, organizing notes and comparing information. NMR Infotech scopes exercises around real task patterns and teaches participants to account for checking and correction time when assessing usefulness.

Audience

Who is this training for?

Employees and managers handling recurring knowledge work. The program can bring multiple departments together for a shared foundation, followed by role-specific practice.

Adaptable curriculum

What will participants learn?

Module 1

Map recurring work

Identify the input, output, reviewer and frequency of a task. Prioritize a clear, bounded workflow over an entire job description.

Module 2

Prepare better drafts

Turn an approved brief into a first draft with explicit facts and constraints. Review tone, completeness and unsupported claims before use.

Module 3

Organize meetings and updates

Extract actions and status from permitted notes without inventing commitments. Preserve unresolved questions and missing information.

Module 4

Research with evidence

Ask for sources, open them and check what they support. Separate finding useful references from making an accountable decision.

Module 5

Measure the whole task

Compare manual and assisted completion against the same quality standard. Include preparation, review, corrections and tool overhead.

Hands-on examples

What will the team practise?

Create a reviewed weekly update

Use synthetic project notes with an access blocker and an absent update. Produce a useful report, verify every material statement and record the corrections needed.

Compare two ways to complete a task

Use equivalent permitted inputs for a manual and an AI-assisted attempt. Record total time and quality issues; discuss what the small test can and cannot establish.

These are proposed learning exercises using synthetic or permitted inputs, not client case studies or claims of measured outcomes.

Learning checks

What should participants be able to demonstrate?

Identify a practical AI-assisted workflow within an existing role.
Prepare useful drafts without treating generated content as verified fact.
Record total task effort, including review and rework.
Explain which findings justify more testing and which suggest changing the task.

Plan the session

How is the program tailored?

Share the participants’ roles, experience, approved tools and two or three recurring tasks. We can then discuss a suitable briefing, workshop or longer learning path, with delivery online, on-site or hybrid subject to agreed scope and arrangements.

The proposed curriculum is a starting point. Duration, prerequisites, software access, materials, follow-up support and fees are agreed in the engagement brief. Participants should have access to the selected tool; any licensing or administrator requirements need confirmation before the session.

Questions about this program

Does productivity training guarantee a percentage time saving?

No. The effect depends on the task, starting process, tool access, review requirements and adoption. Training can help a team design a meaningful comparison; any claimed improvement needs measured evidence.

Can we use our own documents in an exercise?

Yes, where the organization has explicitly approved both the material and the tool used to process it. Public or synthetic examples provide an alternative when that approval is not available.

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