30 Jul AI Transformation Scenario: What an HR Project Could Look Like in Practice
Key Takeaways
- Most companies today don’t plan a target number of vacancies – they react once a workforce gap already exists.
- 59 out of 100 employees would need training by 2030 (WEF Future of Jobs Report, 2025 – Skills outlook) – without a plan, that number stays a statistic instead of an action.
- This is an illustration of an HR Project’s development direction, not a screenshot of a finished feature – the numerical scenario below is hypothetical.
In the previous article, we described how an HR Project would gather context around a change initiative – its goal, timeline, positions, and people. This AI transformation scenario shows what that could look like in a concrete example: a customer service department going through a change driven by AI.
What does a workforce gap look like in this AI transformation scenario?
A workforce gap is the difference between the team a company has today and the team it needs to reach a new goal. Imagine a 10-person customer service department where the transformation goal is a 14-person team with a different competency profile – a gap of 4 people emerges (this is an illustration, not data from a live system). One idea under consideration is that an HR Project could organize such a gap as a “vacancy plan”: the current gap, planned employee transitions between positions, and any overstaffing – still an early working sketch, not a finalized feature.
How does role mapping show what’s changing?
Role mapping shows the difference between a position’s current state and its target state, expressed as a concrete action plan. The current state is today’s competencies and actual tasks in the role; the target state is the new requirements resulting from the transformation; the difference between them becomes a list to work through. One early sketch assumes a competency-match indicator, e.g. “3 of 5 required” – an illustration of a possible format, not an established standard.
| Position today | Target position | Competency gap (illustration) |
|---|---|---|
| Customer service agent (tier 1) | Automation Ops specialist | Bot training and oversight, AI response quality review |
| Complaints consultant | AI-assisted escalation specialist | Handling complex/emotionally sensitive cases AI doesn’t take on |
| Software developer | Software engineer in an architect role | Designing solutions and reviewing AI-generated code |
Paths such as Support Ops, Automation Ops, or Analytics – mentioned as reskilling directions for customer service teams working with AI – aren’t MintHCM module names, but an example of how companies are already naming new roles today (McKinsey, 2025). A similar pattern shows up in software development: the “architect” role, who designs solutions and reviews AI-generated code, is gaining importance, as 66% of developers name reviewing AI-generated code as their top frustration with these tools (Stack Overflow Developer Survey, 2025).
Why isn’t role transformation enough without soft signals?
Hard data on workforce gaps and competency match doesn’t show whether an employee is actually ready for the change. Employee engagement and a manager’s assessment – often informal, based on observation – add context to the competency-match indicator that numbers alone don’t capture. McKinsey describes this as treating reskilling as change management, not just a training rollout: companies are shifting agents handling repetitive tickets into QA, knowledge upkeep, and bot-training rotations, watching who actually fits (McKinsey, 2025).
How is this different from a KPI dashboard?
A KPI dashboard shows an organization’s current state at a given moment, while an HR Project would show the process of moving from that state to a goal over time. Analytics in MintHCM answers the question “how many vacancies do we have and what’s our headcount right now” – that’s reporting on the current state. An HR Project would answer a different question: “how do we get from this state to the goal, and how long will it take.” The two approaches complement each other rather than replacing one another.
Frequently Asked Questions
How does vacancy planning differ from recruitment? A vacancy plan would organize a future hiring need before a specific candidate appears, based on a forecasted workforce gap – recruitment starts once a vacancy is actually open in the Recruitment module.
Can AI replace a position entirely, or only transform it? In the scenario described, AI takes over part of the tasks (routine tickets, code generation), while the employee shifts to tasks requiring judgment, oversight, or customer contact in complex cases – that’s a transformation, not a replacement of the position.
How does the competency-match indicator differ from a standard performance review? A performance review describes results in the current role; the competency-match indicator (early sketch) would compare an employee’s profile against the target position’s requirements, before the transition happens.
Why aren’t the numbers alone (gap, match) enough without a manager’s assessment? Because they don’t show an employee’s readiness and engagement for the change – two people with an identical match score can differ in motivation and pace of adaptation, something only a manager sees.
Would missing competencies automatically generate a training task? Not in the current direction of thinking – the training decision would stay with HR, not automation, even if the list of missing competencies were visible in the system.
Does this scenario come from a live MintHCM system? No. This is a hypothetical illustration of a development direction – the HR Project, vacancy plans, and role mapping are concepts, not features available in MintHCM today.
Summary
This scenario shows how an HR Project could bring together three elements that today function separately: the workforce gap, role mapping, and a manager’s assessment. None of these elements alone gives a complete picture of a transformation – only together, in one place and over time, do they form a plan that can actually be tracked. This closes the three-part series on the HR Project in MintHCM: from diagnosing the problem, through defining the concept, to illustrating how it would work.
Sources
- World Economic Forum, Future of Jobs Report 2025 – Skills outlook – https://www.weforum.org/publications/the-future-of-jobs-report-2025/in-full/3-skills-outlook/
- McKinsey, Agentic AI and the future of customer experience (2025) – https://www.mckinsey.com/capabilities/operations/our-insights/the-future-of-customer-experience-embracing-agentic-ai
- Stack Overflow, 2025 Developer Survey – AI – https://survey.stackoverflow.co/2025/ai