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VP of Talent Acquisition

Set talent acquisition strategy and hiring plans

Enhances◐ 1–3 years

What You Do Today

Translate business growth plans into hiring plans. Define priorities, allocate recruiting resources, and set the strategy for how you'll compete for talent in a competitive market.

AI That Applies

Workforce planning models that translate business forecasts into hiring demand by role, location, and timeline, with market intelligence on talent availability and competition.

Technologies

How It Works

The system ingests candidate data — resumes, assessments, interview feedback, and historical hiring outcomes. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output is a recommended plan or schedule that accounts for the identified constraints and optimization criteria.

What Changes

Hiring planning becomes proactive. AI predicts hiring needs based on business trajectory and attrition patterns instead of waiting for requisitions.

What Stays

Hiring strategy involves trade-offs — build vs. buy talent, internal mobility vs. external hiring, speed vs. quality. Those require strategic judgment.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for set talent acquisition strategy and hiring plans, understand your current state.

Map your current process: Document how set talent acquisition strategy and hiring plans works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Hiring strategy involves trade-offs — build vs. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Workday tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long set talent acquisition strategy and hiring plans takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your board chair or lead independent director

What's the current accuracy of our forecasting, and how would we know if an AI model is actually better?

They shape expectations for how AI appears in governance

your CTO or CIO

Which historical data do we have that's clean enough to train a prediction model on?

They own the technology infrastructure that enables AI adoption

a peer executive at a company further along on AI adoption

What's our time-to-fill for the roles that are hardest to source, and where in the funnel do we lose candidates?

Their lessons learned are worth more than any consultant's framework

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.