Shownotes
In this episode of the Future Proof HR podcast, Thomas Kunjappu sits down with Stephanie Leal, Director of HR Learning and Development at Mission North. Stephanie is leading a company-wide initiative to build AI fluency, not just within HR but across client-facing teams serving some of the most innovative tech brands. What began with a simple usage survey has evolved into a structured learning program—Navigating AI—that combines show-and-tell sessions, AI principles embedded into onboarding, and ongoing cross-functional training.Stephanie shares how she shifted from AI skeptic to champion, helping Mission North employees transform curiosity into practical skills while balancing excitement with caution around data privacy and security. Her story offers a model for how HR and L&D leaders can drive adoption without mandates, creating a culture of experimentation and trust.Topics Discussed:
- How a baseline AI survey revealed 73% of employees were already “explorers.”
- Why mandates spread fear while experimentation spreads innovation.
- Building Navigating AI, a cross-company learning journey with measurable outcomes.
- Embedding AI principles into onboarding and company culture.
- Using show-and-tell sessions and super users to drive grassroots adoption.
- Balancing security, transparency, and responsible AI use.
- How L&D can leverage AI to create more personalized and scalable learning experiences.
- Why curiosity and continuous learning matter more than prior AI skills in hiring.
- The future of L&D: moving from manual training tasks to AI-powered content creation and strategy.
If you’re looking for a practical guide to building AI fluency across your organization while keeping HR at the center of trust, learning, and culture, this conversation with Stephanie Leal is packed with insights you can use today.Additional Resources:
Transcripts
So we wanted to see how many people were using AI,
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how many people felt comfortable.
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Or were nervous about it,
what were their fears?
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And then also what were the use cases
around what they're using it for?
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Because we really wanted to see
where can we fill those gaps?
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Where can we take some of the more manual
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or administrative or time-sucking tasks
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and use AI to help with that?
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And what really surprised me was that...
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73% of our staff described
themselves as explorers.
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So moderate understanding
of AI, moderate adoption.
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And we had no one self-report as a novice.
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They keep telling us that it's all over.
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For HR, the age of AI is upon
us, and that means HR should
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be prepared to be decimated.
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We reject that message.
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The future of HR won't be handed to us.
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Instead, it'll be defined by those
ready to experiment, adopt, and adapt.
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Future Proof HR invites these builders to
share what they're trying, how it's going,
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what they've learned, and what's next.
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We are committed to arming HR
with the AI insights to not
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just survive, but to thrive.
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Thomas: Hello and welcome to the Future
Proof HR Podcast, where we explore how
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forward-thinking HR leaders are preparing
for disruption and redefining what it
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means to lead people in a changing world.
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I'm your host, as always,
Thomas Kunjappu, CEO of Cleary.
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Today's guest is Stephanie Leal,
the Director of HR Learning and
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Development at Mission North.
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A strategic communications firm serving
the future of work and innovation economy.
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Stephanie is leading the charge
to build AI fluency across
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her company, not just in HR,
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but especially for client-facing
teams supporting emerging tech brands.
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Stephanie is building a practical
cross-functional learning
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initiative with measurable outcomes.
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She's also helping HR reimagine
its own role in this new landscape.
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Stephanie, welcome to the podcast.
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Stephanie: Thank you.
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Thank you so much.
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Thomas: So I'm so excited to talk to
you about how you've been thinking about
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bringing in the learning and development
mindset into your firm, especially for
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Mission North, where you are working with
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a lot of your clients who are
pretty tech and AI forward, right?
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Stephanie: Yes, correct.
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Yeah, I've been working at
Mission North for about 10 years.
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And over a decade, I've been able to
shape my career here in the HR space,
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deepening my expertise there.
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And really moved into a
learning and development role
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because it's the part of
HR that really excites me.
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It touches so many aspects
of the employee experience
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from onboarding to career development,
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to performance reviews,
and of course, training.
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So AI has really become
a top priority for us
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because of how much
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it doesn't just shape the
learning and development
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and HR space,
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but also it's a huge learning
opportunity for our whole workforce
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at Mission North and the impact
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it can have when we're upscaling
our employees and involving our
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skills and the ability to take
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those skills to our clients as they
bring their AI expertise to the world.
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So it's a really great
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opportunity right now.
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It's a really exciting space to work in.
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Thomas: So would you say, at least
for you, from an L&D perspective,
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is a lot of the L&D about
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AI?
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Stephanie: Currently, yes.
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So we launched a learning and development
initiative this summer that we're calling
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Navigating AI,
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a summer learning journey.
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And it's our biggest priority in
terms of upscaling our employees,
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because we want to make sure
that they feel confident in
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the new tools that they have at
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their fingertips, that they are finding
it supporting their work and their
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outputs, that it's giving them time
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back and more time and efficiency
so that they can do deeper
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strategic work for their clients.
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And then that they can also
take that to provide even better
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counsel, even better trust from
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our clients into not only
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are we advising you to reach a
broader audience with your tech,
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but we are also confident in the
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emerging tech that's
coming out for all of us.
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I think it's a double header.
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It's a two-pronged learning
opportunity for all of us.
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So I'm really excited
to be spearheading it.
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And I'm really
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excited that Mission North
is motivated and excited by
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this learning opportunity too.
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Thomas: Okay.
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I want to get into much more in depth
there how that works because of everything
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from the genesis of the program all
the way to how you're executing on it.
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But first, I was thinking we could
study that's saying about eight
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in 10 HR practitioners are using
AI in their day-to-day use cases,
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but only a tiny minority feel like they've
gotten any kind of job-specific training.
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Now, I think this is interesting for us to
talk about because it's in the context of
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setting up a whole L&D program
all about AI upskilling for
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not just HR, but the entire
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workforce.
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So as you're seeing this kind of gap
that's being talked about in this article,
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what are your thoughts?
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Stephanie: Yeah, I think one of my biggest
takeaways from the article was about how
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having a company mandate AI does not
spread innovation, it spreads fear.
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So we don't want it to come
from this you must use AI
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approach, but more of creating
an environment for all
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employees, not just HR employees,
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of experimentation, of sharing
resources, of sharing use cases
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and best prompts and things
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like that so that we can all
continue to evolve our skills there.
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I think for HR specifically,
I can understand why a company
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might not be able to offer HR
training specifically for AI.
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But one of the best things about HR as a
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profession is the networks that
are available because so many
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people on HR teams are one or
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two people in an organization or just one.
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So I've found that
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some of the HR focus newsletters
or templates, there's
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different organizations.
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Obviously,
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there's HR organizations like SHRM,
and then there are more specific
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places based on where you're located.
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But people are really
sharing resources right now.
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And so I think I would suggest that
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HR professionals leverage their networks,
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try to find those resources
because they do exist.
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There are HR and L&D
specific AI trainings.
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And then also assess what their
companies are offering in terms of
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personal professional development and
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see if they can use the stipends that
their companies might offer, other
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kinds of training benefits like that
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to really seek out what
they're looking for.
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I know at my company, we
are mostly PR and integrated
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marketing professionals.
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And so our AI trainings are
really tailored to those skills.
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But for our HR team, we're
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constantly sending each other the
best prompts that we found from
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a newsletter or templates that
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we can use for our own work.
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There really is such a
great opportunity for
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knowledge sharing right now.
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Thomas: Absolutely.
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And it's great point that you talk about.
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There's not a single company
where the HR team is like the
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majority of the employee base.
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Stephanie: It can be a
lonely group of people.
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Thomas: Right.
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So it's interesting because
the article is talking
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about HR practitioners
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needing to practice what they preach
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because the L&D role is going to be,
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like you said,
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at least in your current state,
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a lot of it is about enabling AI
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and upskilling with AI skill sets
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for obviously for different
types of functions.
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But then you need to be able to practice
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what you preach a little bit.
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You need to understand the material.
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You need to be a little
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bit native in that.
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And so it's important for HR professionals
to get in there and just have
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something rolling.
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I'm actually a little bit skeptical about
the vast majority of HR practitioners
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actually using it today.
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Now it's maybe if you're doing like
a Google search and you're like,
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instead of doing a Google
search, you're doing it like in
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chat GPT, that kind of counts.
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And it's maybe if you're doing like a
Google search and you're like simple
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instead of doing google search you're
doing it like in ChatGPT that kind of
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counts and it's a self-reported kind of
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data but i think there is a big
opportunity so much so that I'm
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personally working on content
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and training for like HR professionals
to get started from nothing to
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like i know what ChatGPT is to like
actually getting more productive use
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and also the frameworks for how to
think about it because that's often
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missing like which direction how do
I apply it when should I apply it.
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And the article talks about a
gap then between the enthusiasts
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and like the rest that naturally
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will emerge if there's not like
any kind of structure and so
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I do see that happening right
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so there's enthusiasts maybe
like you right that right?
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And kind of like those are the folks
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who are listening to this podcast
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or like getting out,
trying things on their own,
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experimenting a bunch.
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And because we're in the early days,
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it's almost like that's like
the best experimentation
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and just being exposed constantly
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seems to be the better method
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than thinking of like rigid training
modules and trying your best.
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Although I'm curious because you're
rolling this out at scale at your
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company, but that's really interesting.
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Gives us a moment in
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time of where we're at.
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So let's come to your use of or your
program for around like L&D and how
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you started developing it, Stephanie.
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So when we're talking beforehand,
I think you said it all
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started off with a bit of a usage survey.
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And then that's how you went
downstream from all that.
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So was the survey about?
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What were you looking for?
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What did you uncover?
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Stephanie: Yeah, so we wanted to
see how many people were using ai,
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how many people felt comfortable.
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or were nervous about it,
what were their fears?
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And then also what were the use cases
around what they're using it for?
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Because we really wanted to see
where can we fill those gaps?
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Where can we take some of the more manual
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or administrative or time-sucking tasks
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and use AI to help with that?
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And what really surprised me was that...
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This was back in April.
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73% of our staff described
themselves as explorers.
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So moderate understanding
of AI, moderate adoption.
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And we had no one self-report as a novice.
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So low understanding and low adoption.
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I myself said I was a skeptic.
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And that is moderate
understanding, low adoption.
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I come from a more luddite sensibility
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than I might be letting on right now.
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But I thought that was really interesting.
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And there was no one who reported
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that they never used it, but
almost half the company or actually
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a little more than half the
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company was using it every day.
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So we knew we had people who
were definitely experimenting
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with it, but we didn't know how
comfortable they felt in it.
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Or we were worried that if we didn't
fill those gaps or those skills,
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that they wouldn't be using it
to the best of their potential.
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That maybe we would have
data at risk, whatnot.
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So we really wanted to understand
where people's baseline was.
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And then we wanted
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to know what their biggest concerns were.
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And that was, in fact,
privacy and data security.
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That was the top thing where people
were like, I want to try it out,
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but I'm nervous that if I say
237
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something, it's going to suddenly be
training public models on my data.
238
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Yeah.
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Thomas: So that's interesting.
240
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You have great employees
who care about that stuff.
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So actually, it probably has
to do with other trainings and
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onboarding and things that you've
243
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got going on.
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It sounds like the first baseline
where you're trying to just get an
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understanding of your population.
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It sounds like you segmented under either
skeptic, novice, explorer, or there's
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some advanced and a super user.
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And
249
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so that's interesting.
250
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So you got like a baseline of like
where like folks thought they were.
251
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And from there, what do you do next?
252
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Even before that, like
what was the intent?
253
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Like why?
254
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What was the trigger for you
to even send out the survey?
255
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Stephanie: It's interesting.
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Back in 2023, when this really started
to become something that seemed to
257
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be popping off, we came out with
an AI principles that were fairly
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generic, basically, try it out, use it,
259
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but don't say anything that
is proprietary information.
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And it shouldn't be the only
thing that you're using.
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At the time, I think there was
much more fear around the kinds of
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output that you would get from AI.
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And we had everyone do fairly
generic courses at the time we
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were using LinkedIn Learning.
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Just about what is AI.
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What is a large language
model and things like that.
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And then basic understanding of it.
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And we really wanted to get more
specific around how folks could use it.
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So it wasn't just, I'm trying
to draft an email or I'm writing
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a brainstorm or something.
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And more actual tasks that people use.
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And not to say that AI isn't great at
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crafting an email, but just that there
were more opportunities out there.
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We also wanted to make sure
that our employees knew that
275
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we were prioritizing it.
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So it wasn't just like
a flavor of the week.
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We're interested in this.
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We're going to forget about it tomorrow.
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So we did the survey.
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And then from there is really
when we started launching
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into more of a show and tell.
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We have people who are super users,
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let them show us the ways
in which they're using it.
284
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So that was really the
next step of the journey.
285
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Thomas: Just to make sure I understand.
286
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So in 2023, you'd set up some principles.
287
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And so there was already,
288
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it's in the water, people are
using it on their own, their
289
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subscriptions, with some guidelines
290
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about how you can use it.
291
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But then in 2025, it sounds
like the trigger was you wanted
292
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to have more structure around
293
00:13:52,636 --> 00:13:56,976
how you can get people from the
most surface level use cases
294
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to go deeper into specific
295
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workflows so that it can actually
make an impact on productivity
296
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and just fundamentally
297
00:14:04,566 --> 00:14:08,946
how the functions or whichever
function you're in, how you operate.
298
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So that was a trigger for the survey,
if I understand that correctly.
299
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Exactly, yeah.
300
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But then you got these results.
301
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And then was it as you expected
in terms of like most people using
302
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it once a day or for everything.
303
00:14:22,526 --> 00:14:26,266
Especially as you're looking at it
as an L&D team or like an exec team
304
00:14:26,556 --> 00:14:27,956
in terms of what you want to do next?
305
00:14:28,096 --> 00:14:31,436
Or did it surprise you and you
had to pivot the L&D approach?
306
00:14:31,706 --> 00:14:35,506
Stephanie: Actually, I feel like
it was surprising in a positive
307
00:14:35,506 --> 00:14:38,006
way, where I think I assumed that
308
00:14:38,006 --> 00:14:41,356
there would be more people who
identified as novices, people
309
00:14:41,366 --> 00:14:43,006
who never used it, people who
310
00:14:43,006 --> 00:14:47,246
were very against the idea of
incorporating it into their work.
311
00:14:47,606 --> 00:14:52,126
But it was really exciting to see
that people were really ready to jump
312
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in with both feet and try it out.
313
00:14:54,616 --> 00:14:56,076
What they were missing was that
314
00:14:58,165 --> 00:15:02,106
evangelizing and maybe the
hands-on workshops to really
315
00:15:02,476 --> 00:15:05,596
see what it could look like
in their day-to-day work.
316
00:15:05,596 --> 00:15:08,666
So that it was less theoretical
and more so tactical that they
317
00:15:08,666 --> 00:15:10,553
could really start using it.
318
00:15:10,553 --> 00:15:13,473
Thomas: So it sounds like your
strategy for that, you did next was,
319
00:15:13,653 --> 00:15:18,083
so you have the LinkedIn Learning and the
generic, like understanding what LLMs are,
320
00:15:18,233 --> 00:15:20,963
like how to use things so
that people are at that level.
321
00:15:21,243 --> 00:15:22,753
But then you went to
322
00:15:22,763 --> 00:15:25,473
getting your super users
who are self-identified to
323
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start doing show and tells.
324
00:15:26,743 --> 00:15:28,773
So the idea is evangelism, right?
325
00:15:28,773 --> 00:15:30,983
So tell me more about that,
what you did post-survey.
326
00:15:31,453 --> 00:15:31,793
Stephanie: Yeah.
327
00:15:31,793 --> 00:15:35,273
So after the survey, we did
it right before we had an all
328
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company offsite, which we hadn't
329
00:15:36,733 --> 00:15:38,143
done in a few years.
330
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It was a great opportunity to
get us all together in person.
331
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And one of the sessions
332
00:15:43,463 --> 00:15:48,043
that we focused on was the kickoff
of this AI show and tell, because
333
00:15:48,043 --> 00:15:49,843
we had certain teams of people
334
00:15:49,863 --> 00:15:53,493
for certain client groups were
beginning to really incorporate it
335
00:15:53,513 --> 00:15:54,793
in their day-to-day work for those
336
00:15:54,803 --> 00:15:58,713
clients and wanted to show it
off to the rest of the employees.
337
00:15:58,983 --> 00:16:01,683
And again, I am coming in as a skeptic.
338
00:16:01,693 --> 00:16:02,713
I was not a person who
339
00:16:02,713 --> 00:16:03,713
was using it every day.
340
00:16:03,713 --> 00:16:06,453
I was a little hesitant,
especially around security.
341
00:16:06,903 --> 00:16:09,023
And one of the AI
342
00:16:09,023 --> 00:16:12,613
platforms that we have in our
work tech stack is Gemini.
343
00:16:12,933 --> 00:16:14,313
We use Google Workplace.
344
00:16:14,323 --> 00:16:15,623
So to me,
345
00:16:15,623 --> 00:16:19,843
I thought Gemini was just that little
pencil icon that pops up when you're
346
00:16:19,843 --> 00:16:21,753
writing an email that says refine.
347
00:16:22,073 --> 00:16:23,853
And I truly did not
348
00:16:23,873 --> 00:16:28,753
realize that it had its own
sort of ChatGPT-esque platform.
349
00:16:29,523 --> 00:16:31,913
And I didn't know about
all of the other use cases.
350
00:16:31,913 --> 00:16:35,083
I didn't know about Gems,
which is essentially Gemini's
351
00:16:35,193 --> 00:16:37,273
custom GPT, or I didn't know
352
00:16:37,273 --> 00:16:38,583
about Notebook LM.
353
00:16:39,093 --> 00:16:45,048
And so in these show and tell
sessions, employees that I trust,
354
00:16:45,048 --> 00:16:51,168
that I work with, that I look up
to, the group how Notebook LM had an
355
00:16:51,178 --> 00:16:53,958
audio generating feature or the power
356
00:16:53,968 --> 00:16:59,238
of gems to cut out the constant
prompting of your Gemini.
357
00:16:59,318 --> 00:17:02,568
And it was really great, I think,
358
00:17:02,578 --> 00:17:04,578
that we did it in person
because you could really see
359
00:17:04,578 --> 00:17:09,338
people's wheels turning and a lot
of aha moments, not just my luddite
360
00:17:09,377 --> 00:17:11,558
aha moment, but people asking
361
00:17:11,558 --> 00:17:14,188
questions and really starting
to think about the ways that
362
00:17:14,188 --> 00:17:15,667
they could use it themselves.
363
00:17:15,688 --> 00:17:15,948
And so
364
00:17:15,948 --> 00:17:17,248
that was really the first iteration.
365
00:17:18,568 --> 00:17:23,127
And from there, we now do
AI spotlights monthly in our
366
00:17:23,127 --> 00:17:23,988
all hands.
367
00:17:23,998 --> 00:17:25,708
So we're always, again, just trying to
368
00:17:25,708 --> 00:17:29,658
find, hey, this is an opportunity
that we use specifically with
369
00:17:29,668 --> 00:17:31,558
this piece of AI to help this
370
00:17:31,568 --> 00:17:32,078
client.
371
00:17:32,078 --> 00:17:36,728
And then we do biweekly show and tell
sessions every Friday, every other
372
00:17:36,728 --> 00:17:38,978
Friday, around different use cases.
373
00:17:38,988 --> 00:17:42,308
So most recently, we did building a GPT.
374
00:17:42,908 --> 00:17:46,958
We've done building media lists,
which is something that PR
375
00:17:46,958 --> 00:17:48,538
professionals do, things like that.
376
00:17:48,548 --> 00:17:53,838
So it's been really interesting
and just a really great, they're
377
00:17:53,848 --> 00:17:57,118
informal, they're discussion-based,
someone's sharing their screen and
378
00:17:57,118 --> 00:18:00,188
then it opens it up for everyone
else to jump in and build their own.
379
00:18:00,188 --> 00:18:04,068
And yeah, it really generates
a lot of enthusiasm, I think.
380
00:18:28,704 --> 00:18:30,814
Thomas: So let me ask, so it
sounds like you're doing a lot of
381
00:18:30,814 --> 00:18:33,384
bottom-up sharing, just leveraging the
382
00:18:33,384 --> 00:18:37,054
work that's already happening
and trying to help that spur
383
00:18:37,204 --> 00:18:38,594
it to spread even further.
384
00:18:39,054 --> 00:18:43,954
On the other hand, another tactic
is the, which we talked about
385
00:18:43,954 --> 00:18:48,029
a little bit earlier, is about
having a mandate, let's say, right?
386
00:18:48,149 --> 00:18:53,289
Everyone needs to be using X and you need
to show Y progress in any kind of way.
387
00:18:53,639 --> 00:18:57,539
Was there anything communicated in
that from an executive communications
388
00:18:57,539 --> 00:19:00,029
level that's like more mandate-like,
389
00:19:00,039 --> 00:19:04,009
or is it completely all about
just, hey, opt-in and it's in the
390
00:19:04,009 --> 00:19:05,669
culture that like managers would
391
00:19:05,679 --> 00:19:08,849
recommend, hey, you probably want
to attend this or you should show
392
00:19:08,849 --> 00:19:09,319
this off.
393
00:19:09,419 --> 00:19:11,019
How did you balance that part?
394
00:19:11,479 --> 00:19:13,009
Stephanie: So we got
another group of people
395
00:19:13,009 --> 00:19:14,539
together back in 2023.
396
00:19:14,539 --> 00:19:16,089
We had an aI task force.
397
00:19:16,119 --> 00:19:19,369
We got the gang back together
with a couple new super users
398
00:19:19,399 --> 00:19:21,109
and we came out with an updated
399
00:19:21,249 --> 00:19:22,379
AI principle.
400
00:19:22,634 --> 00:19:27,349
Around our philosophies and around
the way that we want AI to be used.
401
00:19:27,379 --> 00:19:28,149
And again, we're not
402
00:19:28,149 --> 00:19:29,149
mandating it.
403
00:19:29,149 --> 00:19:34,679
It's not that intense, but
it's more so about how if
404
00:19:34,679 --> 00:19:36,509
you're using AI, you still need
405
00:19:36,579 --> 00:19:37,769
to have human oversight.
406
00:19:37,769 --> 00:19:39,669
You still need to be
doing quality control.
407
00:19:39,679 --> 00:19:41,334
We own our output.
408
00:19:41,484 --> 00:19:44,714
We need to also be fact-checking, we
need to make sure we're eliminating
409
00:19:44,714 --> 00:19:46,384
bias, all of those things.
410
00:19:46,694 --> 00:19:50,444
And then also, what do we recommend in
terms of the most secure AI platform?
411
00:19:50,444 --> 00:19:52,464
We have a paid Gemini account, we have
412
00:19:52,464 --> 00:19:54,384
a paid Team GPT account.
413
00:19:54,654 --> 00:19:58,944
And if you're using something like
Claude or ChatGPT, make sure that use
414
00:19:58,944 --> 00:20:02,484
it with a paid version so that you
can opt out of training their models.
415
00:20:02,494 --> 00:20:07,394
I think those kinds of guidances are
really important so that we're not just
416
00:20:07,554 --> 00:20:14,084
letting people go willy-nilly and then
inheriting that risk that comes with it.
417
00:20:14,194 --> 00:20:17,354
And then the last part of it
is about continuing to grow.
418
00:20:17,589 --> 00:20:19,284
It is going to continue to evolve.
419
00:20:19,294 --> 00:20:21,334
We're going to continue to evolve with it.
420
00:20:21,374 --> 00:20:24,474
We are not, we're not going
to set it and forget it.
421
00:20:24,494 --> 00:20:27,944
If we need to continue to
shape these policies or
422
00:20:28,084 --> 00:20:30,574
principles and update them, like
we are definitely going to do it.
423
00:20:30,914 --> 00:20:38,524
And the same with the different kinds
of AI opportunities or AIs that we
424
00:20:38,524 --> 00:20:39,954
want to invest in and things like that.
425
00:20:40,119 --> 00:20:41,194
We're going to keep looking
426
00:20:41,194 --> 00:20:45,009
into it to make sure that we are
supporting our staff and that they
427
00:20:45,034 --> 00:20:49,494
feel empowered to use it as a tool,
but not completely rely on it.
428
00:20:51,654 --> 00:20:51,824
Thomas: Okay.
429
00:20:51,834 --> 00:20:56,724
And then can you tell me about,
are you putting this into the
430
00:20:56,754 --> 00:20:58,224
onboarding process at all?
431
00:20:58,234 --> 00:21:02,954
Or does it even go into the
employee culture to the point
432
00:21:02,974 --> 00:21:05,124
of even in job descriptions or
433
00:21:05,124 --> 00:21:05,924
in interviews.
434
00:21:05,924 --> 00:21:09,754
How does this mindset and
set of activities, if at all,
435
00:21:09,774 --> 00:21:12,314
does it apply to the
new employee experience?
436
00:21:12,664 --> 00:21:13,084
Stephanie: Yes.
437
00:21:13,094 --> 00:21:14,704
So we are definitely
438
00:21:15,654 --> 00:21:20,314
putting the AI principles into the
onboarding with the employee handbook.
439
00:21:20,314 --> 00:21:26,254
So it is a part of our policies at Mission
North that we expect that folks are
440
00:21:26,254 --> 00:21:27,644
using it and we want to make sure that
441
00:21:27,644 --> 00:21:28,424
you're using it thoughtfully.
442
00:21:29,659 --> 00:21:34,499
We also, in addition to these show
and tells and hands-on trainings,
443
00:21:34,989 --> 00:21:41,319
we also rolled out a series of trainings
from section that are focused on PR.
444
00:21:41,329 --> 00:21:42,009
So there's four
445
00:21:42,009 --> 00:21:45,939
courses that people take
asynchronously, and that is also
446
00:21:45,939 --> 00:21:46,889
going to be a part of onboarding.
447
00:21:47,239 --> 00:21:47,409
So
448
00:21:47,409 --> 00:21:51,414
in addition to attending your
typical compliance trainings at
449
00:21:51,414 --> 00:21:52,674
the beginning of onboarding, you'll
450
00:21:52,674 --> 00:21:55,684
also have these to watch asynchronously
through the first month with
451
00:21:56,304 --> 00:21:57,764
different checkpoints as you
452
00:21:57,764 --> 00:22:00,984
go through to make sure that you
feel comfortable and confident.
453
00:22:01,304 --> 00:22:03,004
Obviously, because new hires will
454
00:22:03,004 --> 00:22:08,264
have missed the sort of hands-on
show-and-tell workshops that have already
455
00:22:08,264 --> 00:22:08,674
occurred.
456
00:22:08,674 --> 00:22:11,244
So they could watch them, they could
watch a recording, but we also just
457
00:22:11,244 --> 00:22:13,439
want to make sure that folks are
checking in with them to say, do
458
00:22:13,439 --> 00:22:14,569
you have any questions around AI?
459
00:22:15,579 --> 00:22:19,459
In terms of job descriptions and
interview processes, it's definitely
460
00:22:19,459 --> 00:22:21,099
a conversation that we're having.
461
00:22:21,309 --> 00:22:25,114
Because I think when I talk to
other HR leaders, I think the
462
00:22:25,144 --> 00:22:28,574
thing that concerns people the
463
00:22:28,574 --> 00:22:31,974
most is a lack of
transparency around AI use.
464
00:22:32,229 --> 00:22:38,119
I heard a story about someone doing an
interview and using ChatGPT while they
465
00:22:38,119 --> 00:22:40,449
were on the interview to generate answers.
466
00:22:40,599 --> 00:22:43,469
That feels a little, again, luddite here.
467
00:22:43,489 --> 00:22:47,109
It feels duplicitous from
a HR recruiting standpoint.
468
00:22:47,499 --> 00:22:56,059
But at the same time, I think it's okay to
use ChatGPT to improve your resume or help
469
00:22:56,059 --> 00:22:57,279
craft a cover letter.
470
00:22:57,289 --> 00:23:01,579
And I think it's okay to also
use ChatGPT to craft your job
471
00:23:01,579 --> 00:23:02,939
descriptions or things like
472
00:23:02,939 --> 00:23:03,349
that.
473
00:23:03,349 --> 00:23:07,989
And I think as long as you're being
transparent about where AI is coming in,
474
00:23:08,279 --> 00:23:10,329
and then the human component as well,
475
00:23:10,819 --> 00:23:14,259
that kind of saves or avoids some of
476
00:23:14,319 --> 00:23:18,619
the heartache or confusion
around how it's being used.
477
00:23:18,829 --> 00:23:22,219
I think folks rightfully
are concerned about
478
00:23:24,339 --> 00:23:33,069
AI assessing resumes and cutting
people without any human check on what
479
00:23:33,069 --> 00:23:34,259
the AI is doing.
480
00:23:34,259 --> 00:23:38,099
And so I think as long as companies
are being transparent about what tools
481
00:23:38,099 --> 00:23:42,489
they're using, the way in which
it works, how they are continuing
482
00:23:42,489 --> 00:23:44,599
to have a human touch on those
483
00:23:44,609 --> 00:23:49,409
processes, I think people will feel
a lot less afraid of it in general
484
00:23:49,409 --> 00:23:50,309
and just more.
485
00:23:50,449 --> 00:23:53,769
Also, it creates a level of trust for the
company that you're looking to work for.
486
00:23:53,889 --> 00:23:56,229
At Mission North, those are
definitely conversations we're having.
487
00:23:56,229 --> 00:23:57,839
We're not quite in those directions
488
00:23:57,849 --> 00:24:03,729
yet of adopting AI tools in that space,
but we'll definitely be transparent.
489
00:24:04,039 --> 00:24:05,039
I trust that the company
490
00:24:05,039 --> 00:24:10,089
will be transparent about any
kinds of extra AI touches that
491
00:24:10,089 --> 00:24:12,379
might be a part of those processes.
492
00:24:12,889 --> 00:24:16,159
Thomas: I was more
interested in how you talk
493
00:24:16,169 --> 00:24:17,609
about expectations.
494
00:24:17,639 --> 00:24:22,629
And if you think about your
company at 70% explorer, right?
495
00:24:22,669 --> 00:24:24,129
And as your average
496
00:24:24,149 --> 00:24:27,479
company has turnover and you're in
a couple of years, a completely new
497
00:24:27,479 --> 00:24:32,359
workforce, what is the expectation
for prospective new employees?
498
00:24:32,379 --> 00:24:34,229
Because that's, I think, part of the fear.
499
00:24:34,429 --> 00:24:37,039
It's almost in 2022, you're trying
to say, are you guys remote?
500
00:24:37,059 --> 00:24:38,029
Are you hybrid?
501
00:24:38,029 --> 00:24:39,009
I need to understand this.
502
00:24:39,489 --> 00:24:41,619
And there's a similar
question, I think, for talent.
503
00:24:41,809 --> 00:24:43,819
Are you AI native?
504
00:24:43,819 --> 00:24:44,519
What does that mean?
505
00:24:44,549 --> 00:24:45,889
Like, how much do I need to know?
506
00:24:45,949 --> 00:24:48,289
Am I actually going to be
able to succeed at this job?
507
00:24:48,539 --> 00:24:51,589
It's almost like a question
that employers and employees are
508
00:24:51,939 --> 00:24:53,229
going to be like navigating as
509
00:24:53,229 --> 00:24:55,069
this shift is happening.
510
00:24:55,499 --> 00:24:59,229
And I think it's communicated in
job descriptions and sometimes,
511
00:24:59,229 --> 00:25:01,719
and oh, how we work and what
we do and things like that.
512
00:25:01,719 --> 00:25:03,269
But then I think that is something
513
00:25:03,269 --> 00:25:06,029
that's, you're talking about it
with the existing employee base,
514
00:25:06,029 --> 00:25:07,729
but then now you have it also in
515
00:25:07,739 --> 00:25:10,639
new hire orientation and it's there.
516
00:25:10,639 --> 00:25:15,549
And then it goes even upstream into
expectations and even evaluation
517
00:25:15,869 --> 00:25:18,149
of skill set to get people started.
518
00:25:18,549 --> 00:25:22,294
But it seems at least from what I'm
hearing at Mission North, it's like you
519
00:25:22,294 --> 00:25:24,244
want people who are curious and are...
520
00:25:24,244 --> 00:25:26,954
even if they've had no exposure,
they're going to be going through
521
00:25:26,954 --> 00:25:28,404
this in the onboarding process.
522
00:25:28,404 --> 00:25:30,724
And that should be an expectation.
523
00:25:31,724 --> 00:25:33,844
If you've literally never
touched an AI tool, you're
524
00:25:33,844 --> 00:25:38,034
going to be within the first three
months and you got to get ready, right?
525
00:25:38,314 --> 00:25:39,154
Stephanie: Mm-hmm.
526
00:25:39,164 --> 00:25:39,584
Yeah.
527
00:25:39,584 --> 00:25:44,474
One of our values is stay curious
and another one is test yourself.
528
00:25:44,474 --> 00:25:45,544
So I don't think
529
00:25:45,554 --> 00:25:51,844
that we would, I don't think having
a lack of AI skills is disqualifying,
530
00:25:51,854 --> 00:25:56,594
but I do think that candidates for any
position in any company need to have
531
00:25:56,664 --> 00:26:00,942
that continuous learning Mentality
where it is a new skillset that we
532
00:26:00,942 --> 00:26:03,972
are all, that we, no one is immune to.
533
00:26:04,032 --> 00:26:05,682
We are all learning together.
534
00:26:05,952 --> 00:26:09,327
And to have that, that, that feeling of.
535
00:26:09,627 --> 00:26:10,625
curiosity.
536
00:26:11,015 --> 00:26:13,915
And I think that will set candidates
537
00:26:13,935 --> 00:26:16,595
up for success no matter what
job they're applying for.
538
00:26:16,595 --> 00:26:20,595
Because I imagine it
was similar when people
539
00:26:20,595 --> 00:26:23,505
started using computers or
the internet and shifting the
540
00:26:23,505 --> 00:26:24,785
way that they're doing work.
541
00:26:25,095 --> 00:26:31,915
I think that we should all take this
opportunity to look at it as an exciting
542
00:26:32,015 --> 00:26:37,335
learning adventure, as opposed to
something that is inherently destructive
543
00:26:37,385 --> 00:26:39,615
or inherently a bad idea or something.
544
00:26:39,615 --> 00:26:42,595
I think it's a mindset.
545
00:26:42,655 --> 00:26:45,565
And I think that candidates
in all industries
546
00:26:45,865 --> 00:26:50,555
have an opportunity to really say,
I'm working on my skills and I'm
547
00:26:50,555 --> 00:26:52,985
ready to jump in where I need to be.
548
00:26:53,005 --> 00:26:57,235
And then from the employer side
of things, it's on our end to
549
00:26:57,235 --> 00:26:58,585
make sure that we're providing
550
00:26:58,595 --> 00:27:01,635
those asynchronous trainings
to give everybody the same base
551
00:27:01,645 --> 00:27:03,535
knowledge and then support that
552
00:27:03,535 --> 00:27:06,045
experimentation and support
those knowledge sharing.
553
00:27:06,075 --> 00:27:07,845
And not just to say, these are the
554
00:27:07,845 --> 00:27:11,295
things that I did well, but these are
the prompts that really failed me.
555
00:27:11,345 --> 00:27:15,545
Or these are the things that I tried
to do and I came up with a really
556
00:27:15,545 --> 00:27:17,575
bad answer or something like that.
557
00:27:17,625 --> 00:27:21,845
To show that, to have people
have the freedom and the safety
558
00:27:22,155 --> 00:27:23,505
to experiment in that way.
559
00:27:24,700 --> 00:27:25,790
Thomas: I love that mindset.
560
00:27:25,790 --> 00:27:29,490
Now, let me go through an exercise
with you because you mentioned in
561
00:27:29,490 --> 00:27:33,940
the past you're skeptic, luddite,
and also being in on the HR side,
562
00:27:33,940 --> 00:27:37,820
you think about risk and policy
issues, but you've had an evolution.
563
00:27:37,830 --> 00:27:40,120
So maybe let's like straw man it for you.
564
00:27:40,120 --> 00:27:44,430
What are your thoughts about
AI and how it's coming into the
565
00:27:44,430 --> 00:27:49,140
workforce and how it could apply
to you and how has that evolved?
566
00:27:50,190 --> 00:27:55,190
Stephanie: I think when I first started
hearing about AI, I was eye rolling.
567
00:27:55,195 --> 00:27:58,720
I don't really know how
this is going to affect me.
568
00:27:58,795 --> 00:28:01,850
I don't really see this
coming into my day to day.
569
00:28:01,850 --> 00:28:03,850
And people are talking a lot about it,
570
00:28:03,850 --> 00:28:04,770
but it seems different things like NFTs
571
00:28:07,040 --> 00:28:09,000
were once something that people
were talking a lot about.
572
00:28:09,005 --> 00:28:11,690
So I was skeptical to say the least.
573
00:28:12,040 --> 00:28:16,120
And I think over time, especially in this
574
00:28:16,120 --> 00:28:23,050
last year and a half, you can
really see it starting to integrate
575
00:28:23,060 --> 00:28:24,820
seamlessly with your workflows.
576
00:28:24,820 --> 00:28:24,950
So
577
00:28:25,080 --> 00:28:28,970
So, you know, at first I remember
people talking about, oh, yeah, I
578
00:28:28,970 --> 00:28:32,700
use ChatGPT to look up restaurant
recommendations for my book club.
579
00:28:32,720 --> 00:28:34,380
And I was like, that's weird.
580
00:28:34,390 --> 00:28:35,550
Isn't that just a Google search?
581
00:28:35,570 --> 00:28:37,630
I've never looked at ChatGPT before.
582
00:28:37,870 --> 00:28:41,560
And then suddenly, especially
with sort of the support of my
583
00:28:41,560 --> 00:28:45,860
company, talking about good prompts
and the ways in which to use it,
584
00:28:45,870 --> 00:28:49,830
suddenly crafting better prompts
and suddenly getting better outputs
585
00:28:49,870 --> 00:28:55,060
and seeing how asking the right
questions gets you even better answers.
586
00:28:55,110 --> 00:28:57,140
When I first started
using it, I definitely
587
00:28:57,160 --> 00:29:01,320
asked a question that you would ask a
Google search, give me a list of this.
588
00:29:01,640 --> 00:29:02,660
And then I got
589
00:29:02,660 --> 00:29:04,620
answers that didn't really help me.
590
00:29:04,950 --> 00:29:08,810
And then suddenly to learn,
you need to put in the context,
591
00:29:08,810 --> 00:29:10,470
you need to, who is your audience?
592
00:29:10,490 --> 00:29:12,360
What kind of output are you looking for?
593
00:29:12,410 --> 00:29:15,720
What do you not want to see all of
those things, basically treating AI
594
00:29:15,890 --> 00:29:19,640
like an intern, giving them
a lot of specificity, you'll
595
00:29:19,640 --> 00:29:20,820
start to see better outputs.
596
00:29:20,820 --> 00:29:24,820
And I think, again, it was that
experimentation piece, and that sort
597
00:29:24,820 --> 00:29:27,170
of drive from my company and from my
598
00:29:27,170 --> 00:29:32,830
industry of AI is not going away,
for Mission North, for HR, for L&D.
599
00:29:33,420 --> 00:29:34,290
Better to jump in
600
00:29:34,290 --> 00:29:36,090
with both feet than to be afraid.
601
00:29:36,340 --> 00:29:39,260
Better to see how it can work
for you versus backing away
602
00:29:42,230 --> 00:29:42,690
from it.
603
00:29:42,945 --> 00:29:44,060
It really changed my mind.
604
00:29:44,070 --> 00:29:49,190
I could really see that there is a
lot of advantages to just playing
605
00:29:49,190 --> 00:29:51,010
around with it and just
learning the tools.
606
00:29:52,110 --> 00:29:54,585
Thomas: So then a dual
question, looking forward
607
00:29:54,585 --> 00:29:58,008
a little bit based on what you've
seen, let's talk about HR and
608
00:29:58,245 --> 00:30:01,215
L&D and that function, your job,
609
00:30:01,235 --> 00:30:03,885
and this function that we're all
thinking about future-proofing.
610
00:30:04,465 --> 00:30:06,925
So how do you think the L&D
611
00:30:06,925 --> 00:30:10,105
function is shifting going forward?
612
00:30:10,345 --> 00:30:12,375
You've seen it happening
for you as well, right?
613
00:30:12,375 --> 00:30:12,585
And then
614
00:30:12,585 --> 00:30:15,415
based on that, do you have the
implicit question is what advice
615
00:30:15,435 --> 00:30:16,945
would you have for your peers who are
616
00:30:17,185 --> 00:30:21,385
in a similar kind of role
working for an organization where
617
00:30:21,625 --> 00:30:22,805
there is at least a potential
618
00:30:23,015 --> 00:30:25,915
for a lot more adoption
and upskilling with AI?
619
00:30:25,925 --> 00:30:30,380
Stephanie: Yeah, I think
in terms of everyone knows
620
00:30:30,400 --> 00:30:33,360
that a one-size-fits-all approach
doesn't work and that there are
621
00:30:33,360 --> 00:30:35,380
many different kinds of learners.
622
00:30:35,410 --> 00:30:40,240
And so you want to be able to hit people
where it is the most effective for them,
623
00:30:40,240 --> 00:30:44,870
where they can absorb materials
and it has an impact on them.
624
00:30:45,445 --> 00:30:52,385
And I think what's really exciting about
L&D and the AI capabilities is the way in
625
00:30:53,335 --> 00:31:01,955
which AI can really assist the kinds of
learning resources that you're creating.
626
00:31:02,145 --> 00:31:06,635
So for example, I might be
putting together training
627
00:31:06,645 --> 00:31:08,775
and so I'm creating a deck.
628
00:31:09,435 --> 00:31:11,815
and I'm customizing it and whatnot.
629
00:31:11,825 --> 00:31:15,375
Then I'm creating a resource that
people can refer to after the training.
630
00:31:15,435 --> 00:31:16,355
So that's something.
631
00:31:16,625 --> 00:31:22,075
And then I'm either giving the
training live or I'm recording myself.
632
00:31:22,855 --> 00:31:28,515
With bloopers and all and rewrites and
all, and then distributing that around.
633
00:31:28,575 --> 00:31:30,015
And that all takes time.
634
00:31:30,015 --> 00:31:33,445
And I'm one person and that is
that is a huge chunk of my day.
635
00:31:33,775 --> 00:31:37,305
Whereas if you incorporate AI,
there are capabilities where
636
00:31:37,305 --> 00:31:38,995
AI can create videos for you.
637
00:31:38,995 --> 00:31:41,485
So you're no longer pointing
around your screen, but you're
638
00:31:41,495 --> 00:31:42,575
actually showing something that
639
00:31:42,575 --> 00:31:45,775
maybe is visually engaging for
people who are more visual learners.
640
00:31:46,015 --> 00:31:49,135
And that also isn't just your
face or a deck that you created.
641
00:31:49,415 --> 00:31:54,045
There's also capabilities with AI for
creating those kinds of presentations or
642
00:31:54,125 --> 00:31:56,525
resources from those presentations.
643
00:31:56,535 --> 00:32:00,245
And then the last thing that I
learned just this year is the
644
00:32:00,245 --> 00:32:02,855
capabilities of audio generation.
645
00:32:03,115 --> 00:32:07,065
So for those folks who are more audio
learners who want to listen to a podcast
646
00:32:07,065 --> 00:32:11,460
while they're taking a walk, all of a
sudden, those sorts of suddenly, that is
647
00:32:11,505 --> 00:32:14,145
something that you can create
in a matter of seconds,
648
00:32:14,145 --> 00:32:17,685
minutes by just uploading
resources and generating a summary.
649
00:32:17,715 --> 00:32:21,285
So there's just a lot more
with getting that time back.
650
00:32:21,455 --> 00:32:25,505
Then suddenly you have more time
to work with people one-on-one.
651
00:32:25,515 --> 00:32:26,115
Maybe they went
652
00:32:26,115 --> 00:32:28,805
through a training, but it's just
not sticking and they need someone
653
00:32:28,805 --> 00:32:30,675
to show them they learned by doing.
654
00:32:31,035 --> 00:32:32,965
Suddenly you have more
time to devote to that.
655
00:32:32,965 --> 00:32:35,305
You have more time to devote
to other areas of upskilling
656
00:32:35,685 --> 00:32:36,915
that people are focused on.
657
00:32:37,265 --> 00:32:39,045
And a big part of L&D and HR is
658
00:32:39,065 --> 00:32:41,805
obviously the soft skills and
getting to know people and
659
00:32:42,045 --> 00:32:44,335
working, talking about conflict or
660
00:32:44,335 --> 00:32:47,435
things that make people tick or where
they want to go in their careers.
661
00:32:47,465 --> 00:32:52,100
And suddenly you have time back to really
focus on those tasks that you can't
662
00:32:52,100 --> 00:32:55,910
really put a price on or you can't, those
are the ones that you can't automate.
663
00:32:56,250 --> 00:32:59,660
And so I think it just
gives us as L&D and HR
664
00:32:59,660 --> 00:33:05,805
professionals an opportunity to
automate and make some of those tasks
665
00:33:05,945 --> 00:33:11,655
more efficient so that we can put more
time and energy towards the strategy
666
00:33:11,815 --> 00:33:13,765
and the people focus of our jobs.
667
00:33:15,235 --> 00:33:15,435
Thomas: Yeah.
668
00:33:15,435 --> 00:33:18,045
And actually it sounds like you're
going even further than the automation.
669
00:33:18,045 --> 00:33:18,165
It's
670
00:33:18,165 --> 00:33:19,905
actually creating a better product.
671
00:33:19,930 --> 00:33:23,345
So for less time invested, you're
creating a more personalized
672
00:33:23,365 --> 00:33:25,775
product with different
modalities of learning.
673
00:33:26,205 --> 00:33:29,045
And also I think what you described around
674
00:33:29,355 --> 00:33:33,195
presentation creation and just
content creation is probably just
675
00:33:33,265 --> 00:33:36,935
a generic, like for any kind of
knowledge worker who's putting content
676
00:33:36,945 --> 00:33:39,025
together can be made more efficient.
677
00:33:39,025 --> 00:33:43,305
But then the delivery of that
whole process can happen in less
678
00:33:43,315 --> 00:33:46,325
time and yet be more personalized.
679
00:33:46,605 --> 00:33:51,175
On top of that, you have more time to work
potentially one-on-one, one-on-two with
680
00:33:51,195 --> 00:33:55,105
different individuals to really make sure
that they're getting the most out of the
681
00:33:55,105 --> 00:33:57,405
content and also growing and learning.
682
00:33:57,405 --> 00:34:02,515
And in that way, you're maximizing your
impact for the organization as a whole.
683
00:34:02,875 --> 00:34:02,905
But
684
00:34:05,605 --> 00:34:08,355
then I would imagine the
floor starts going up, right?
685
00:34:08,355 --> 00:34:16,415
The standards for what can one person
L&D team deliver over time will be,
686
00:34:16,435 --> 00:34:20,235
the expectations will go up because
you should be able to do much more,
687
00:34:20,255 --> 00:34:21,514
but then you have to experiment
688
00:34:21,525 --> 00:34:24,675
along the way to figure
out how to do that.
689
00:34:24,745 --> 00:34:26,574
It's hard fought insight.
690
00:34:27,195 --> 00:34:31,364
So this is all very interesting.
691
00:34:31,485 --> 00:34:32,355
I have to ask.
692
00:34:32,415 --> 00:34:37,105
So going forward now with the program,
you've done a survey, you've gotten
693
00:34:37,105 --> 00:34:40,875
in all these show and tells, you
incorporated into all hands, you've had
694
00:34:40,905 --> 00:34:43,375
incorporation into onboarding meetings.
695
00:34:43,670 --> 00:34:46,215
What's next do you think
for your L&D program?
696
00:34:46,811 --> 00:34:49,420
Stephanie: Well, we are coming
out with our fourth PR specific
697
00:34:49,420 --> 00:34:52,773
course and following that up
with another show and tell.
698
00:34:52,773 --> 00:34:58,433
But I think the next step overall is to
really just assess how this summer went
699
00:34:58,793 --> 00:35:00,648
and where people identify now.
700
00:35:00,653 --> 00:35:02,713
I was looking over the survey questions
701
00:35:03,253 --> 00:35:07,753
and just thought, I think we
can probably send this survey
702
00:35:07,783 --> 00:35:09,853
maybe a couple of tailored questions,
703
00:35:10,113 --> 00:35:11,513
but just the same questions
704
00:35:11,513 --> 00:35:13,563
of how do you identify as an AI user?
705
00:35:13,563 --> 00:35:16,583
How often are you using it and
really see what the shift has been?
706
00:35:16,613 --> 00:35:19,933
Because I know personally, for
me, I would definitely, I have
707
00:35:19,933 --> 00:35:24,133
definitely shifted in my AI use, and
I've definitely improved over time.
708
00:35:24,133 --> 00:35:27,833
And so I do think that another
survey is in our future.
709
00:35:28,853 --> 00:35:32,773
And then I think the next step for us
is also thinking about what kind of
710
00:35:32,773 --> 00:35:33,123
agentic AI do we want to incorporate or
711
00:35:37,303 --> 00:35:41,743
are there other specific tools
that we want to invest in for our
712
00:35:41,753 --> 00:35:45,778
PR professionals outside of just
the tools that we already have.
713
00:35:45,778 --> 00:35:51,568
And that's our next iteration is
how can we pinpoint specific tasks?
714
00:35:51,588 --> 00:35:55,848
And if it's not something that we can do
with Gemini or Team GPT, is it something
715
00:35:55,848 --> 00:35:59,458
that we can do with something
that someone is building for
716
00:35:59,458 --> 00:36:01,688
us or for PR firms in general?
717
00:36:02,068 --> 00:36:04,768
Thomas: Customized for a function
or just specifically for you guys.
718
00:36:04,768 --> 00:36:05,298
Yeah, absolutely.
719
00:36:05,298 --> 00:36:06,288
That's the next level.
720
00:36:06,288 --> 00:36:07,948
There's so much more to uncover.
721
00:36:08,368 --> 00:36:10,398
So excited to see where it all goes.
722
00:36:10,398 --> 00:36:14,448
So where can people, how can people
best connect with you, Stephanie, if
723
00:36:14,448 --> 00:36:17,148
they want to learn more about you or
what you're doing at Mission North?
724
00:36:17,548 --> 00:36:19,758
Stephanie: Yeah, you can find
me on LinkedIn, Stephanie
725
00:36:19,768 --> 00:36:21,558
Leal with Mission North.
726
00:36:21,568 --> 00:36:24,048
And I'm excited to touch
base with you there.
727
00:36:25,228 --> 00:36:25,798
Thomas: Wonderful.
728
00:36:25,868 --> 00:36:30,338
Thank you for sharing your journey
personally, as well as how you've
729
00:36:30,338 --> 00:36:34,428
seen it, the transformation slowly
but surely happening at Mission North
730
00:36:34,468 --> 00:36:38,888
and how you're supporting it and a
little bit of a vision of what how
731
00:36:39,458 --> 00:36:44,828
an L&D team supporting an upscale
initiative for an entire organization
732
00:36:44,908 --> 00:36:46,488
towards AI that could look like.
733
00:36:47,278 --> 00:36:50,498
So that is something that at
least a lot of people are thinking
734
00:36:50,498 --> 00:36:53,118
about if not already executing on.
735
00:36:54,048 --> 00:36:55,558
I think it's going to be massively
736
00:36:55,918 --> 00:36:56,468
valuable.
737
00:36:56,478 --> 00:37:01,318
So thank you for the conversation
and for everyone out there who
738
00:37:01,318 --> 00:37:04,758
are future proofing your
orgs and your HR teams.
739
00:37:04,768 --> 00:37:08,178
Thanks for listening and hope
you had a couple of takeaways and
740
00:37:08,498 --> 00:37:09,958
we'll see you on the next one.
741
00:37:10,168 --> 00:37:10,678
Bye now.
742
00:37:12,148 --> 00:37:15,208
Thanks for joining us on this
episode of Future Proof HR.
743
00:37:15,448 --> 00:37:18,058
If you like the discussion, make
sure you leave us a five star
744
00:37:18,058 --> 00:37:20,938
review on the platform you're
listening to or watching us on.
745
00:37:21,358 --> 00:37:24,298
Or share this with a friend or colleague
who may find value in the message.
746
00:37:24,598 --> 00:37:29,548
See you next time as we keep our pulse on
how we can all thrive in the age on AI.
