One AI Use Case in HR That Saves You $$$

Use it to build your solid Business Continuity Plan!

The adieu speech and the “Today is my last day…” email goes out.

“I would like to thank my leader and my team for giving me the opportunities…”

People smile.

Some reply: “Wishing you the best. Let’s stay in touch on LinkedIn!”

And then… the organization starts to forget.

In a slow, expensive way.

Because while we treat offboarding and exits like an HR checklist…

The real cost is that a person just walked out with a living library in their head.

The hidden work that begins after “Adieu!”

Here’s what happens next:

A new hire opens a tool they’ve never used.
A teammate inherits a project they didn’t build.
A leader asks, “Can we move faster on this?”

And everyone does the same thing:

They search.
They ping.
They wait.
They recreate.

This is the part of the work that doesn’t appear on the dashboards senior leaders see.

But it shows up in drag.

Before anyone leaves… we’re already losing time

APQC surveyed knowledge workers and found that they spend 2.8 hours/week just looking for or requesting needed information.

And APQC also reports the average knowledge worker spends 8.2 hours/week looking for, recreating, and duplicating information and expertise, i.e., roughly 20% of the workweek.

So even in “normal operations,” many companies are running with a knowledge leak.

Then someone resigns…

…and the leak becomes a flood.

The myth: “It’s all documented.”

Are you kidding me? It’s rarely all documented.

Because the most important knowledge is almost never the good stuff.

It’s the messy stuff in people’s heads that constitutes tacit knowledge.

• Which stakeholder needs a heads-up first.

• Which process breaks in the month-end and the year-end?

• Why we chose option B even though option A looked better on paper.

• What not to touch unless you want to ruin your week.

That’s not “documentation.”

That’s judgment.

And judgment usually lives inside people.

The “search tax” is not a metaphor anymore

“A recent Atlassian survey found teams waste a full quarter of their time just searching for answers before they even start doing the work.”

If you translate that into a standard 40-hour week, that’s ~10 hours/week spent searching before the work even begins. (That conversion is mine, not Atlassian’s.)

“Microsoft found 62% of people feel they spend too much time searching for information at work.

And Gartner found 47% of digital workers struggle to find the information or data they need to perform their jobs effectively.

So when someone leaves, the “search tax” doesn’t start…

It spikes.

Because the person who was the shortcut is gone.

The money number leaders can’t ignore

WalkMe’s 2025 research reports that enterprises lost over $104 million in 2024 due to underutilized tech and digital inefficiencies.

Different label than “knowledge sharing.”
Same lived reality:

When work is hard to find, hard to learn, and hard to transfer… organizations pay for it twice.

Once in time.

And again in momentum.

That’s the real offboarding cost

Not the laptop.

Not the access removal.

The part where a new person spends weeks learning what one departing person “just knew.”

The part where teams re-learn the organization…

one Slack message at a time.

Leaders: this is your moment to use GenAI well

HR - Offboarding in 2026 is not just about hosting a farewell party & saying goodbye.

It’s about safeguarding and transferring knowledge so continuity doesn’t depend on “who remembers.”

And as a leader, you now have an unfair advantage: Generative AI can finally make knowledge capture less painful for the person leaving and the people staying.

Not by replacing Mike.

By preventing the organization from losing “Ex-Mike.”

Foster a culture of knowledge-sharing (before the exit)

Knowledge transfer can’t be a panic project triggered by resignation.

It needs to be the norm.

That means: lightweight documentation habits, consistent updates, and a culture where “writing it down” is part of doing the work and not extra credit.

Because if knowledge-sharing only happens at the exit…

It will always be rushed, incomplete, and emotional.

Do this to cut down handover + KT time

Start by building (or tightening) a real Knowledge Management System.

Not a folder graveyard in SharePoint.

A living system.

(I wrote about this back in July 2024 and I still don’t see it happening nearly enough.)

https://blog.ailady.me/p/this-is-how-you-do-offboarding-in

Step 1: Record and transcribe the real knowledge
Record TEAMS/Zoom KT sessions. Transcribe them.
Even if a replacement hasn’t been hired yet, capture the knowledge while the expert still exists.

Step 2: Centralize what matters
Put the relevant emails, docs, code backups, SOPs, decisions, and artifacts into a single place people can actually search.

Leverage AI (the “Ex-Mike” move)

Now feed those transcripts and documents into an AI chatbot so it can summarize key decisions, surface insights, and make the knowledge retrievable. (Summaries still need human review, especially for high-stakes processes.)

Chatbots can be built with ChatGPT or M365 Copilot, for example.

This is also an area where newer tools for offboarding knowledge transfer are emerging.

Sensay, for example, positions its product as an AI offboarding platform that captures and transfers critical know-how, using an AI interviewer and making the output accessible via chat.

So your team can ask questions later like:

“What was Mike’s process for month-end?”
“Why did we choose option B?”
“Who do we need to align with before changing this workflow?”

And instead of archaeology…

They get an answer.

An Ex-Mike.

(But ethically: with consent, access controls, and clear boundaries on what’s captured.)

The line we can’t cross

If knowledge capture starts to feel like surveillance…

People will stop sharing.

So the responsible version includes:

• clear consent and transparency

• human review before “answers” become authoritative

• role-based access controls

• retention rules (not everything needs to live forever)

Trust is the infrastructure. Without it, the knowledge system collapses.

If teams are already losing hours every week to searching and recreating knowledge…
and the enterprise cost of digital inefficiency is now measured in nine figures…
then offboarding isn’t an HR process.

It’s a leadership decision.

So ask yourself:

• Where are you relying on “tribal knowledge” as a strategy?

• What would change if knowledge transfer became a designed product—not a meeting you schedule?

The future of work isn’t just adding shiny AI tools to your toolkit, it’s about stopping the waste first.

Stay curious,

AI Lady 💫

About the Author

I’m Priya Tahiliani, and I’ve spent the last 15 years at the intersection of HR and Technology. Most of my career has focused on SAP HCM and SAP SuccessFactors consulting, working with Big Four firms and clients across the globe.

I built and launched my company’s first AI tool by forging a great partnership with IT, and today I continue to work with HR leaders to help shape the future of work with AI.

Beyond work, I serve as Vice President of Public Relations at Toastmasters. I’m also the Founder of the AI Collective – Oakville Chapter in Canada, part of the world’s largest community for AI professionals - a network dedicated to learning and leading responsibly with AI.

And of course, I write the AI Lady newsletter, where I share my experiences, insights, and thoughts about how AI is reshaping our workplaces.