Latest / The DEX Show: A Show for IT Change Makers / Deleting Em-Dashes 🤨 : REALITY BYTES AI WORKPLACE SPECIAL ft. HR Leader Gabi Tofani

Transcript

Deleting Em-Dashes 🤨 : REALITY BYTES AI WORKPLACE SPECIAL ft. HR Leader Gabi Tofani · The DEX Show: A Show for IT Change Makers

• 0:02
  Speaker 1: Hey, it change makers and welcome to the Deck Show
• 0:05
  Speaker 1: with tom Ac gra Let's get into it.
• 0:11
  Speaker 2: For many years, the technology adoption was very much it lad,
• 0:15
  Speaker 2: you might say. But one of the things AI is
• 0:18
  Speaker 2: changing is arguably this, because suddenly the questions are far
• 0:22
  Speaker 2: from merely technical. Their their cultural, behavioral, organizational. So many
• 0:28
  Speaker 2: questions come up when you're thinking about them, and we've
• 0:32
  Speaker 2: got it. We've got a great and very appropriate guest
• 0:34
  Speaker 2: to discuss it. But we also have a great and
• 0:36
  Speaker 2: very appropriate reality by its panelist with us. It's It's
• 0:40
  Speaker 2: wonderful Oreana. How you doing, Oreana?
• 0:42
  Speaker 3: Doing well? Happy to be here?
• 0:44
  Speaker 2: And I feel this is quite an Oriana coded topic
• 0:47
  Speaker 2: for today, don't you think.
• 0:50
  Speaker 3: In fact, Gaby and I had a conversation about this
• 0:53
  Speaker 3: topic a couple of months ago, and so I'm really
• 0:56
  Speaker 3: interested to hear how her perspective has changed.
• 0:59
  Speaker 2: It's good and you did spark because it was your
• 1:02
  Speaker 2: idea as an episode of a person, A very good idea,
• 1:05
  Speaker 2: it is. Let's welcome o wonderful guest Gabby to Fernni
• 1:09
  Speaker 2: next thing'shead of Global Talent success. I think maybe maybe
• 1:14
  Speaker 2: our first ever or our second ever HR leader on
• 1:18
  Speaker 2: the show, sign it for times no doubt. Welcome to
• 1:20
  Speaker 2: the Deck show, Gabby, Welcome to reality Bites in fact,
• 1:23
  Speaker 2: how are you?
• 1:24
  Speaker 4: I am great, happy to be here, Thanks for having me.
• 1:28
  Speaker 2: And maybe maybe just a word for listeners about yourself
• 1:32
  Speaker 2: and your time and next week? How long have you?
• 1:34
  Speaker 2: How long have you been here? Now? I can never
• 1:35
  Speaker 2: remember you not being here on my time, but that
• 1:37
  Speaker 2: doesn't mean you work.
• 1:38
  Speaker 4: I'm clattered. Yeah, no, I bet here five years, which
• 1:41
  Speaker 4: feels like EON's in a tech company's tenure. Yeah, time,
• 1:46
  Speaker 4: you've been here longer, right.
• 1:48
  Speaker 2: Just only narrowly, but yes, a little bit longer. But yeah, yeah,
• 1:53
  Speaker 2: And what about you, Arianna? How many how many years
• 1:54
  Speaker 2: have you got India about? At this point?
• 1:56
  Speaker 3: I've been here about five years now.
• 1:57
  Speaker 2: Okay, look at look at it's what you do. Notice
• 2:01
  Speaker 2: that a lot of Next thinkers who who turn up
• 2:04
  Speaker 2: on the show have had these these long tenures. And
• 2:07
  Speaker 2: that might have something to do with you as well, Gabby.
• 2:09
  Speaker 2: You know it might have something to do with the
• 2:12
  Speaker 2: v v HR, the HR philosophy at the company. What
• 2:15
  Speaker 2: do you think.
• 2:16
  Speaker 4: Yes, we like to create a work environment where people
• 2:19
  Speaker 4: want to stay, right, So that's all about talent success.
• 2:21
  Speaker 4: So Yeah, my role at Next Think encompasses a few
• 2:24
  Speaker 4: different things, but I oversee our global learning and development programs,
• 2:28
  Speaker 4: so everything from employee onboarding to employee skill development, leadership
• 2:33
  Speaker 4: development and bench planning, also talent management, so as we
• 2:37
  Speaker 4: think about succession planning and developing our bunch of leaders,
• 2:40
  Speaker 4: all of that and then newly under my remit is
• 2:44
  Speaker 4: esg So really thinking about sustainability globally across Next Think
• 2:48
  Speaker 4: and how we make an.
• 2:49
  Speaker 2: Impact fabulous, So I'd be I'd be interested to know, Gabby. Obviously,
• 2:57
  Speaker 2: Next Thing is quite a particular environment, right because it's
• 3:00
  Speaker 2: developing workplace technology or technology software for the workplace, and
• 3:06
  Speaker 2: that puts everyone in it it Next Thing, and of course,
• 3:11
  Speaker 2: to some degree, maybe increasing degree, yourselves in an interesting
• 3:14
  Speaker 2: position in terms of helping to facilitate the experimentation with
• 3:18
  Speaker 2: and testing of the things Next Think is producing. So
• 3:23
  Speaker 2: maybe talk about how that influences your work or impacts
• 3:27
  Speaker 2: your work, and how that dynamic between say HR and
• 3:30
  Speaker 2: IT has evolved over the years that you've worked with.
• 3:34
  Speaker 4: Yeah, I love that because I naturally, as an HR
• 3:38
  Speaker 4: person have and feel like I have a lot in
• 3:40
  Speaker 4: common with IT professionals because both our industries have sometimes
• 3:45
  Speaker 4: a bad reputation. You know, there's some stereotypes about IT
• 3:49
  Speaker 4: HR people, So I have some empathy for that that
• 3:52
  Speaker 4: we're trying to, you know, prove some of our corporate
• 3:55
  Speaker 4: teammates wrong. And that really is this idea that maybe
• 4:00
  Speaker 4: IT or HR is reactive and they're kind of just
• 4:04
  Speaker 4: cost centers to the business. And what we both have
• 4:07
  Speaker 4: in common and what I love about Next Think is
• 4:09
  Speaker 4: that we're pushing our respective functions to be more proactive
• 4:14
  Speaker 4: in our approach, really help the business solve complex problems
• 4:18
  Speaker 4: with our own strategies and really make a difference. So
• 4:21
  Speaker 4: we're not just cost centers or really strategic partners and
• 4:25
  Speaker 4: using the employee experience in different ways to really drive that.
• 4:30
  Speaker 4: So there's a lot of similarities, a lot of similarities
• 4:33
  Speaker 4: between IT and ASIA Are So I love.
• 4:37
  Speaker 3: That you bring up the way that Nick Sink is
• 4:39
  Speaker 3: really pushing the boundaries there and are there ways that
• 4:43
  Speaker 3: specifically being at Next Think and what we do affects
• 4:47
  Speaker 3: the way HR functions and how you prioritize things, how
• 4:52
  Speaker 3: you tackle the problems that you tackle.
• 4:54
  Speaker 4: Yeah. Absolutely, and it's been an evolution. So I see
• 4:58
  Speaker 4: the way Next Think's products parts our HR team is
• 5:01
  Speaker 4: something that's very evolving. As Next Think continues to expand
• 5:05
  Speaker 4: its products, we are like, oh, yes, perfect, let's add
• 5:07
  Speaker 4: that to how we're operating as an HR team. So
• 5:10
  Speaker 4: it's very complimentary. So as an example, when we are
• 5:14
  Speaker 4: launching some new initiatives, we'll use engage campaigns and we
• 5:17
  Speaker 4: use some of next Think's products as a compliment to
• 5:20
  Speaker 4: some of the HR program or we're doing. We really
• 5:23
  Speaker 4: see it as a partner, and in particular at this
• 5:27
  Speaker 4: very unique inflection point that we are with AI, I
• 5:30
  Speaker 4: think that tie between HR and IT is going to
• 5:34
  Speaker 4: be stronger than ever. Is stronger than ever. So I'm
• 5:37
  Speaker 4: really excited for us also to talk a little bit
• 5:39
  Speaker 4: about how we're looking at AI drive and employee AI
• 5:43
  Speaker 4: adoption because I see that as a huge partnership between
• 5:47
  Speaker 4: IT and HR. To make that happen within an organization
• 5:51
  Speaker 4: Next Think.
• 5:51
  Speaker 2: And beyond excellent and then more more curveble for you, Gabi,
• 5:55
  Speaker 2: before we do, which is I mean, I guess at
• 5:57
  Speaker 2: the heart of Next Think, of course is digital employee experience.
• 6:01
  Speaker 2: At the heart arguably of HR. Any HR team has
• 6:05
  Speaker 2: to be the employee experience to some degree. How do
• 6:08
  Speaker 2: you think your time at next Think has influenced your
• 6:12
  Speaker 2: understanding of what employee experience is or what's important about it.
• 6:17
  Speaker 4: I love that question. Yeah. One of the reasons why
• 6:19
  Speaker 4: I joined next Think five years ago was it was
• 6:23
  Speaker 4: right at the time when COVID was happening and we
• 6:27
  Speaker 4: were all moving from this in office environment to digital
• 6:31
  Speaker 4: and it made complete sense for a product like next
• 6:34
  Speaker 4: Thing to exist because we needed to really focus on
• 6:37
  Speaker 4: what is that digital employee experience? And when I joined
• 6:41
  Speaker 4: next Think, I was very I'm not surprised, but very
• 6:46
  Speaker 4: happy to see that our leadership team just innately understood
• 6:50
  Speaker 4: what a employee experience meant and why it mattered. We
• 6:54
  Speaker 4: know that when employees truly are feeling like they have
• 6:57
  Speaker 4: the tools to do their job, when they're supported, when
• 7:00
  Speaker 4: they have a leadership team that also supports them and
• 7:02
  Speaker 4: wants to see them be successful, they're going to do
• 7:04
  Speaker 4: their best work. They're they're gonna You're gonna get the
• 7:07
  Speaker 4: most that you can get out of them. So when
• 7:10
  Speaker 4: I think about next Thing and what we offer our
• 7:14
  Speaker 4: digital and end users, excuse me, is we we get
• 7:17
  Speaker 4: to give them the best experiences at work. And as
• 7:20
  Speaker 4: an HR person, I also see that we get to
• 7:22
  Speaker 4: give them their best experiences of work. How we do
• 7:25
  Speaker 4: that a little bit different but at the same same result.
• 7:29
  Speaker 2: Rate absolutely, and then you end up with, you know,
• 7:32
  Speaker 2: people racking up half decades and decades in the same way. Lazy. Again,
• 7:37
  Speaker 2: you must be you must be doing something right. But
• 7:39
  Speaker 2: it is also are saying there's a there's there's distinct
• 7:42
  Speaker 2: dex and e X, I guess, and yet there's there's
• 7:45
  Speaker 2: there's an increasing arguable proximity or growing indistinguishability between them, right,
• 7:53
  Speaker 2: and you've already you've already flagged it. But that AI
• 7:56
  Speaker 2: is one of those things that is changing that dynamic.
• 8:00
  Speaker 2: So turning to AI has this background in being used
• 8:08
  Speaker 2: to working and collaborating with it and monitoring adoption and
• 8:11
  Speaker 2: engagement with technology positioned you as a as a department distinctly,
• 8:15
  Speaker 2: perhaps compared to other HR teams who haven't historically had
• 8:19
  Speaker 2: to engage as closely with the concept of decks or
• 8:22
  Speaker 2: cross functional collaboration when it comes to AI adoption. A
• 8:26
  Speaker 2: bit of a mouthful as a question gamby, see if
• 8:28
  Speaker 2: you can make see if you can make sense of it?
• 8:31
  Speaker 4: No, I mean, here's the thing. I think we're all
• 8:33
  Speaker 4: figuring it out. And you know what's so funny, Tom,
• 8:35
  Speaker 4: is like, when I think about what when we're faced
• 8:40
  Speaker 4: with these new challenges and you know, next thing, just
• 8:42
  Speaker 4: like any other company, we're kind of thinking about how
• 8:46
  Speaker 4: do we grow to the next level where investments and
• 8:49
  Speaker 4: when we're faced with certain problems, how do we address them?
• 8:52
  Speaker 4: And in the past, we were always able to kind
• 8:55
  Speaker 4: of look back and see like, Okay, maybe at this
• 8:58
  Speaker 4: time at this company, this how we approached it. And now,
• 9:02
  Speaker 4: for the first time, that's actually probably not necessarily the
• 9:06
  Speaker 4: best framework to use. It's now thinking about, okay, how
• 9:10
  Speaker 4: do we approach this problem with AI and really rethinking
• 9:14
  Speaker 4: the problems and the solutions in a way that we
• 9:18
  Speaker 4: truly have not before. So it's a really interesting time
• 9:22
  Speaker 4: because maybe what got us to where we are right
• 9:26
  Speaker 4: now is or isn't necessarily what's going to get us
• 9:28
  Speaker 4: to the next phase of growth. It really has to
• 9:30
  Speaker 4: be a different approach. So I would say, when when
• 9:33
  Speaker 4: I think about that from like an HR standpoint, you know,
• 9:37
  Speaker 4: we have insights from next Think products that are able
• 9:41
  Speaker 4: to really help us understand our full employees experience, the
• 9:46
  Speaker 4: full story of someone's employee journey. We use engagement survey
• 9:51
  Speaker 4: data internally within our own tools, but we also kind
• 9:55
  Speaker 4: of complement that with next Thinks data to help again
• 9:59
  Speaker 4: just fully understand where someone at in their journey from
• 10:02
  Speaker 4: a digital experience, but now also in particular from a
• 10:06
  Speaker 4: AI adoption experience.
• 10:09
  Speaker 3: Do you have like an maybe an anecdote or something
• 10:12
  Speaker 3: that illustrates how you've done that, like maybe a collaboration
• 10:16
  Speaker 3: or a time that that data that you might not
• 10:19
  Speaker 3: have at a different company has come in handy.
• 10:22
  Speaker 4: Yeah. I mean, ultimately, what we are trying to uncover
• 10:26
  Speaker 4: within our workforce is our next thinkers leveraging AI in
• 10:31
  Speaker 4: a way that two things. One from a co pilot standpoint,
• 10:35
  Speaker 4: is it making them more efficient? Is it making them
• 10:36
  Speaker 4: more effective at their jobs? But then also the co thinker,
• 10:40
  Speaker 4: so are they able to come up with better ideas?
• 10:42
  Speaker 4: Are they able to think things through at a deeper
• 10:45
  Speaker 4: level than maybe they would wouldn't have if AI wasn't there.
• 10:49
  Speaker 4: So how do you actually measure that is a really
• 10:53
  Speaker 4: tricky topic. How do you measure are your workers actually
• 10:56
  Speaker 4: more effective, more efficient, more impactful in the work using AI?
• 11:00
  Speaker 4: And Next Thing has been able to help support that.
• 11:03
  Speaker 4: So not that I'm trying to sell next thing right now.
• 11:06
  Speaker 4: But I do think as an HR person, it has
• 11:08
  Speaker 4: been actually really insightful what we've been able to pull
• 11:12
  Speaker 4: from that tool. So we're able to see what for
• 11:15
  Speaker 4: each we can break it down by different demographics. We
• 11:18
  Speaker 4: can break it down by what teams, what levels, what
• 11:24
  Speaker 4: countries and geolocations are using AI for so we're able
• 11:27
  Speaker 4: to see what tools are using. We're also able to
• 11:29
  Speaker 4: see what percentage of that workforce is using AI and
• 11:33
  Speaker 4: at what volumes, so how many hours a week are
• 11:36
  Speaker 4: they actively engaged in AI. So we're able to really
• 11:39
  Speaker 4: quickly split. Okay, I see our sales organization is at
• 11:42
  Speaker 4: this percentage, our engineering organization is a way higher adopter.
• 11:45
  Speaker 4: They're way more of an evangelist. So I to worry
• 11:48
  Speaker 4: maybe a little bit less about engineering, And we now
• 11:50
  Speaker 4: know that we need to focus a bit more on
• 11:52
  Speaker 4: the sales organization and come up with some really specific
• 11:55
  Speaker 4: enablement programs for them because and also their needs are
• 11:59
  Speaker 4: so different. When I think about what an engineering function
• 12:02
  Speaker 4: needs versus a sales organization, the way that we would
• 12:05
  Speaker 4: support them from an enablement standpoint is so different. So
• 12:09
  Speaker 4: what would it makes sense to have some global enablement
• 12:13
  Speaker 4: program to support AI adoption. The AI drive data really
• 12:18
  Speaker 4: gives us the ability to see, okay, where we might
• 12:20
  Speaker 4: you to segment certain focus areas for certain teams.
• 12:26
  Speaker 3: So are there also specific ways that you're finding out
• 12:30
  Speaker 3: like what do those teams need? What are those specific
• 12:33
  Speaker 3: use cases? How do you tailor those programs to the
• 12:38
  Speaker 3: different teams?
• 12:40
  Speaker 4: Yeah, and that's where we rely really heavily on our
• 12:43
  Speaker 4: enablement partners. So I don't think HR needs to be
• 12:46
  Speaker 4: the expert on how each function should use their AI
• 12:51
  Speaker 4: tools because realistically the task I need to be done
• 12:55
  Speaker 4: in each job, those teams know what needs to get
• 12:58
  Speaker 4: done and they can think about how to customize AI
• 13:03
  Speaker 4: to match those workflows. So we rely heavily on enablement
• 13:07
  Speaker 4: partners to create and identify what tooling can we use
• 13:11
  Speaker 4: to really support that again, that copilot or that Cothnker
• 13:15
  Speaker 4: type of work that our employees need to do. But
• 13:21
  Speaker 4: when I think about from an HR standpoint, where we focused,
• 13:24
  Speaker 4: it's more on creating one giving people visibility and guidance
• 13:28
  Speaker 4: on what they can and can't do with AI. That's
• 13:31
  Speaker 4: another thing that AI drive is helpful with is identifying
• 13:34
  Speaker 4: where there might be some potential you know, so maybe
• 13:38
  Speaker 4: there's some AI tools that we don't want people to
• 13:40
  Speaker 4: use because they're not secure, So it does help with
• 13:43
  Speaker 4: creating some guardrails around that. And then what we also
• 13:48
  Speaker 4: do is we are thinking about how do we support
• 13:51
  Speaker 4: managers and really guiding their teams through how to use
• 13:55
  Speaker 4: AI wisely and in a way that doesn't impact the credibility.
• 14:00
  Speaker 4: So we're really thinking about and spending time on how
• 14:05
  Speaker 4: do you use AI as a people manager without losing
• 14:08
  Speaker 4: your humanity? Which is is also kind of an interesting
• 14:11
  Speaker 4: thing to think about.
• 14:13
  Speaker 2: I'm interested, Gabby, like, as a as an HR leader,
• 14:19
  Speaker 2: what stresses you out about AI?
• 14:22
  Speaker 4: So many things I want to hear about animal us
• 14:27
  Speaker 4: Oh man AI is naming.
• 14:30
  Speaker 2: Their examples were here, we want prissy for any specific I.
• 14:34
  Speaker 4: Went on maternity leave this past summer, and when I
• 14:38
  Speaker 4: came back, I swear every single conversation people were just
• 14:41
  Speaker 4: saying AI AI this AI that. I was like, oh my,
• 14:44
  Speaker 4: I'm sick of hearing the word AI work. But it
• 14:46
  Speaker 4: feels like every sentence every meeting is AI AI AI,
• 14:51
  Speaker 4: which is great, But also I think what can be
• 14:54
  Speaker 4: problematic is that we may be using AI too. Doesn't
• 15:04
  Speaker 4: want to say too much, But it.
• 15:06
  Speaker 2: Can be a real thing. That's the real that could
• 15:08
  Speaker 2: be that could in some instances be a concern. Right,
• 15:10
  Speaker 2: it can definitely be accepted you soon.
• 15:13
  Speaker 4: And I'm good with all the copilot, like, let's automate
• 15:17
  Speaker 4: all the mandate tasks of our lives and AI is
• 15:20
  Speaker 4: perfect for that. But what really concerns me is if
• 15:24
  Speaker 4: we're using AI for creativity or for innovation, what do
• 15:28
  Speaker 4: we lose if we over rely on AI? Like even
• 15:32
  Speaker 4: beyond work, Like when I think about our education system,
• 15:38
  Speaker 4: like the fact that we had to grind it out
• 15:39
  Speaker 4: and write an essay and like really think through and
• 15:42
  Speaker 4: kind of force us to think about the topic and
• 15:45
  Speaker 4: how to frame it. Now AI does that all for you.
• 15:48
  Speaker 4: So it's like, what are we losing with AI? Potentially
• 15:52
  Speaker 4: even in our students. So I'm thinking about our future
• 15:54
  Speaker 4: workforce what are they going to be like because they
• 15:57
  Speaker 4: have their reliance on AA to think for them is
• 16:01
  Speaker 4: so different than how we kind of learned and grew up,
• 16:05
  Speaker 4: if you will. But then I'm also thinking about our
• 16:08
  Speaker 4: own workers, like right now, what are they relying on
• 16:12
  Speaker 4: AAAI to do for them? That is also maybe they're
• 16:17
  Speaker 4: over relying on AI and we're actually losing their perspective
• 16:21
  Speaker 4: and their thoughts because they're just dependent on AI to
• 16:24
  Speaker 4: make decisions for them. That's not saying that's happening, but
• 16:27
  Speaker 4: that is a scary thought. Is if we you know,
• 16:32
  Speaker 4: for example, I asked someone a question the other day
• 16:35
  Speaker 4: about how we should approach a program and they said,
• 16:38
  Speaker 4: chat gpet said this, And I was like, I'm so
• 16:42
  Speaker 4: glad that CHATTPT said that. I could ask chat GPT
• 16:45
  Speaker 4: that too. I want to know what you're thinking because
• 16:47
  Speaker 4: you have information that in context that chattept definitely does it.
• 16:54
  Speaker 4: So that's that's what keeps me up at night, is
• 16:56
  Speaker 4: what are we losing with AI?
• 16:58
  Speaker 3: Too?
• 16:59
  Speaker 4: So I think it's really important for us as as leaders,
• 17:03
  Speaker 4: and it's not just an HR by the way, it's
• 17:05
  Speaker 4: on all of us to really hold the line on
• 17:08
  Speaker 4: like what does quality look like and what do we
• 17:10
  Speaker 4: expect from our people?
• 17:12
  Speaker 2: Strong agree, Yeah, So I think it's we underestimate the
• 17:17
  Speaker 2: degree to which AI is a sort of qualitative threat
• 17:20
  Speaker 2: to work and as there's a potential consequence there an
• 17:25
  Speaker 2: organizational competitiveness, right, I mean, do you imagine bit of
• 17:30
  Speaker 2: this way? An organization is defined by what distinguishes it
• 17:34
  Speaker 2: from its competitors, you know, and if everybody starts drawing
• 17:37
  Speaker 2: from the same vicarious sources, both distinguishing qualities will be eroded.
• 17:42
  Speaker 2: You know. It's just like peoples when they use it
• 17:46
  Speaker 2: excessively to communicate with one another, they stop sounding like themselves,
• 17:50
  Speaker 2: they start sounding like everybody else. You know, this is
• 17:52
  Speaker 2: a sort of blandification. If you will, I mean to
• 17:55
  Speaker 2: what degree, Gabby, I mean, at the moment, who knows.
• 17:59
  Speaker 2: But going forward, do you envisage a role for HR
• 18:04
  Speaker 2: in moderating or directing the usages of AI internally to
• 18:11
  Speaker 2: make sure they're not just on a sort of governance
• 18:13
  Speaker 2: level safe, but actually, you know, on a level of
• 18:18
  Speaker 2: on a qualitative level, if.
• 18:19
  Speaker 4: You will, you know, yeah, I think similar to how
• 18:24
  Speaker 4: we think about performance in general, it's yeah, some of
• 18:28
  Speaker 4: it's on HR, but really it's ultimately who holds the
• 18:31
  Speaker 4: line as the people managers. So that's where I think
• 18:34
  Speaker 4: it's so important for us to really empower enable our
• 18:38
  Speaker 4: leadership teams to be able to call out when they
• 18:42
  Speaker 4: see AI slap. You know. For example, I the other
• 18:46
  Speaker 4: day was presenting something to one of our C levels
• 18:49
  Speaker 4: and he was like, that slide was definitely made by
• 18:52
  Speaker 4: Claude wasn't a gabby and I was like, yep, it was.
• 18:55
  Speaker 4: But then he kind of brought up the fact that
• 19:00
  Speaker 4: could that hurt my credibility if I'm presenting slides that
• 19:03
  Speaker 4: are so obviously made by AI. Now, to be fair,
• 19:07
  Speaker 4: I read reread those sides. I felt comfortable with the
• 19:09
  Speaker 4: content in them and the wording in them, but that
• 19:14
  Speaker 4: does potentially impact my credibility because it looks like I'm
• 19:17
  Speaker 4: just pushing out AI slop to my leaders. So I
• 19:21
  Speaker 4: think that's something that we all just have to as
• 19:23
  Speaker 4: people managers look out for ourselves of course and reflect on,
• 19:27
  Speaker 4: but also our own teams and call out when we're
• 19:29
  Speaker 4: seeing content that is so obviously AI generated and potentially
• 19:33
  Speaker 4: loses that employees tone of voice, their perspective. Was just
• 19:38
  Speaker 4: kind of a click simit kind of thing.
• 19:40
  Speaker 2: But it becomes a bit eccentric, doesn't I want to
• 19:42
  Speaker 2: ask goryanor about this in fact, because like you get
• 19:44
  Speaker 2: this kind of hole of mirrors where everybody's using AI,
• 19:48
  Speaker 2: pretending not to use it, trying to make their work
• 19:50
  Speaker 2: look less like, you know, to the point of like
• 19:53
  Speaker 2: adding typos, you know what I mean, Like these.
• 19:55
  Speaker 4: Literally totally removing on Dasha's taking out that and honestly,
• 20:04
  Speaker 4: like from Chad Jip too.
• 20:07
  Speaker 2: But now, I mean, just think of that process actually
• 20:10
  Speaker 2: becomes completely ridiculous. You know, I've done the work myself,
• 20:13
  Speaker 2: and I have to make it that like I haven't
• 20:15
  Speaker 2: done it myself by some additional additional moment of effort orion.
• 20:20
  Speaker 2: How do we find our way out of this ridiculous
• 20:23
  Speaker 2: naze of absurdity?
• 20:25
  Speaker 3: Well, I think I think it is tricky, right, And
• 20:27
  Speaker 3: and like Gaby said, it does come down to sort
• 20:30
  Speaker 3: of each individual and good management structures like not just
• 20:36
  Speaker 3: people managers, but also mentors, coaches, all that stuff. Right.
• 20:40
  Speaker 3: As somebody who has mentored a number of researchers in
• 20:44
  Speaker 3: my career, one of the things that I talk about is,
• 20:47
  Speaker 3: you know what, the way you present your work matters
• 20:52
  Speaker 3: a lot. Being persuasive matters a lot, and learning the
• 20:56
  Speaker 3: skills to do that so that it sounds fluid and
• 20:59
  Speaker 3: natural and convincing without being manipulative like those are all.
• 21:03
  Speaker 3: That's a huge suite of skills, right, and it's one
• 21:07
  Speaker 3: that you cultivate over the course of your career. And
• 21:09
  Speaker 3: it's one of the marks of for example, a persuasive speaker,
• 21:13
  Speaker 3: a good storyteller, a convincing leader, that they can put
• 21:18
  Speaker 3: ideas in ways that reach people but are still meaningful. Right.
• 21:23
  Speaker 3: And it's so funny. I remember walking out of a
• 21:26
  Speaker 3: talk number of years ago with one of our really
• 21:30
  Speaker 3: brilliant product leaders going, wow, people love that talk. You know.
• 21:34
  Speaker 3: It was really persuasive, and he's like, yeah, but there
• 21:38
  Speaker 3: was no message in it. It was just really it
• 21:42
  Speaker 3: made people feel good, but it didn't have much concrete
• 21:47
  Speaker 3: behind it. And it was really interesting because so when
• 21:49
  Speaker 3: I looked at my notes, it's like, oh, yeah, I've
• 21:51
  Speaker 3: got like two notes in here that are really solid,
• 21:55
  Speaker 3: and so I think it. I like that, Gaby, you
• 21:58
  Speaker 3: were stressing sort of the the relational aspect of this
• 22:01
  Speaker 3: and making sure that we think about things in context
• 22:05
  Speaker 3: and that when you reach out to somebody, you're trying
• 22:07
  Speaker 3: to access their particular perspective and body of knowledge, because
• 22:11
  Speaker 3: I do think that is what sets as a part
• 22:14
  Speaker 3: and allows us to produce good quality, right. And I
• 22:17
  Speaker 3: think also the research supports what you're saying, Tom. When
• 22:20
  Speaker 3: people ask AI tools for for example, business plan strategy,
• 22:24
  Speaker 3: things like that it is homogenized and people have done
• 22:27
  Speaker 3: comparison research where they put in different criteria right, and
• 22:31
  Speaker 3: they get the same outputs essentially, and that's a problem
• 22:35
  Speaker 3: because the context isn't the same. So I think it's
• 22:39
  Speaker 3: really great to hear the way that here Next think
• 22:42
  Speaker 3: we are thinking about that and we're trying to be like, Okay,
• 22:44
  Speaker 3: how do we understand what people's context is. How do
• 22:47
  Speaker 3: we make sure we're not trying to shove everybody in
• 22:49
  Speaker 3: the same size shoe.
• 22:50
  Speaker 4: Yeah. Another example that comes to mind for me is
• 22:53
  Speaker 4: the direcded performance review. So at Next think we've eliminated
• 22:58
  Speaker 4: performance reviews and the the kind of writing down.
• 23:02
  Speaker 2: Thank you for that chance to say thank you performance
• 23:10
  Speaker 2: after it.
• 23:11
  Speaker 4: Everyone does such a dreaded process because you it just
• 23:15
  Speaker 4: requires you to write down a bunch of words, and
• 23:17
  Speaker 4: then you have this dreaded conversation. So we really at
• 23:20
  Speaker 4: Next I pushed for these continuous performance conversations and again
• 23:23
  Speaker 4: going back to that human side of working with each other,
• 23:27
  Speaker 4: where you have a conversation about what went well, where
• 23:30
  Speaker 4: next quarter could go differently, where you want to focus
• 23:33
  Speaker 4: on and developed, and then you add in this AI
• 23:37
  Speaker 4: component to these performance reviews that I'm like, I want
• 23:41
  Speaker 4: to avoid this is imagine what this is happening in
• 23:47
  Speaker 4: companies across the world right now, where an employee is
• 23:49
  Speaker 4: writing a completely AI created review and then their manager
• 23:53
  Speaker 4: is responding in a completely AI created review. So we
• 23:57
  Speaker 4: just have ais talking to each other about each other's performance.
• 24:06
  Speaker 2: Biz. It's funny. I ask you open question for you
• 24:11
  Speaker 2: both about you know. One thing that's sort of struck
• 24:13
  Speaker 2: me for a while is you know, if someone's doing
• 24:15
  Speaker 2: a PhD, right, I believe to this day they have
• 24:17
  Speaker 2: to do like a viva at the end of their
• 24:20
  Speaker 2: PhD with it based sort of I don't know. I've
• 24:21
  Speaker 2: never been in one, but I think they stand there
• 24:24
  Speaker 2: and there's like a panel of academics who thrill them
• 24:27
  Speaker 2: face to face.
• 24:28
  Speaker 4: And class examination, cross examination.
• 24:32
  Speaker 2: Of what they what they've what they've learned or whatever, right,
• 24:35
  Speaker 2: and what they've submitted I guess. And back in the day,
• 24:39
  Speaker 2: or even maybe to some extent of this day, in
• 24:42
  Speaker 2: sort of the top top tier universities in the UK,
• 24:45
  Speaker 2: there are oral examinations and traditionally I think they were
• 24:50
  Speaker 2: more more a more conventional part of how people were examined.
• 24:55
  Speaker 2: I think this is a future of education, right, like
• 24:57
  Speaker 2: if you can no longer really us so to speak
• 25:01
  Speaker 2: what's on a page. You've got to get people in
• 25:04
  Speaker 2: front of other people, and they've got to be able
• 25:06
  Speaker 2: to ask answer curveball questions. They've got to be able
• 25:10
  Speaker 2: to express themselves. They've got to be able to take
• 25:13
  Speaker 2: the information and demonstrate that awareness by navigating their way
• 25:18
  Speaker 2: through it in real time, you know, before everybody's eyes.
• 25:21
  Speaker 2: Maybe there's an element of that in the future for
• 25:25
  Speaker 2: workplace as well.
• 25:27
  Speaker 4: You know, it's a great as you're saying, as I'm like,
• 25:30
  Speaker 4: think about interviewing and what's already happening out there. So
• 25:33
  Speaker 4: there's software is now that Actually I was interviewing some
• 25:36
  Speaker 4: candidates doing some initial phone conversations the past few weeks,
• 25:42
  Speaker 4: and there are a few conversations that I had where
• 25:46
  Speaker 4: there was a slight delay and then a very robotic
• 25:49
  Speaker 4: response from them. So I am.
• 25:52
  Speaker 2: I think I was going on, Gabby, you know, I'm
• 25:55
  Speaker 2: able to.
• 25:56
  Speaker 4: Say so, yeah, that's where it's like, Okay, you need
• 26:00
  Speaker 4: to have conversations face to base because I what's getting
• 26:04
  Speaker 4: lost in me talking to a candidate and getting an
• 26:07
  Speaker 4: a any I would know it was a smart response,
• 26:09
  Speaker 4: but it also Rihanna, what you said earlier about like
• 26:11
  Speaker 4: it didn't actually have depth. None of those responses from
• 26:15
  Speaker 4: those AI interview tools it gave me any depth, Like
• 26:19
  Speaker 4: I didn't walk away from that conversation feeling like, oh,
• 26:21
  Speaker 4: that candidate is someone that I would want to work with,
• 26:24
  Speaker 4: you know, So if there is something that we lose
• 26:28
  Speaker 4: when we overrely on AI for for certain things, for sure.
• 26:32
  Speaker 3: Yeah, I mean I really like how you've phrased this.
• 26:36
  Speaker 3: I think the future where you have to express your
• 26:40
  Speaker 3: ideas and words looks bright for folks who can express
• 26:43
  Speaker 3: the ideas as effect as as effectively as a lot
• 26:47
  Speaker 3: of the leaders do here. And it also makes me
• 26:50
  Speaker 3: reflect a little bit on that as like a skill set.
• 26:53
  Speaker 3: And I'm sure we'll also have AIS that will support
• 26:58
  Speaker 3: that learning journey, you know, I'm sure we'll have AIS
• 27:01
  Speaker 3: that looks smoother and smoother all the time. But I
• 27:04
  Speaker 3: do hope that we also think about, you know, what
• 27:09
  Speaker 3: is the purpose and what is the sort of driving
• 27:12
  Speaker 3: emotion behind it? And you know, the work is a
• 27:17
  Speaker 3: kind of performance at times. It's funny. We started off
• 27:21
  Speaker 3: our pre show conversation talking about performances and actually the
• 27:25
  Speaker 3: oral tradition of bards, you know, storytellers back and.
• 27:29
  Speaker 2: If we did. There's no comforull cycle.
• 27:32
  Speaker 3: It's just a beautiful thing. You know, humans are storytellers
• 27:35
  Speaker 3: and I don't think we're ever going to lose that.
• 27:37
  Speaker 3: But I hope we also think about, you know, when
• 27:39
  Speaker 3: do we want more of a polished performance and when
• 27:42
  Speaker 3: do we need to just connect, you know. And I
• 27:47
  Speaker 3: feel like HR is always trying to strike that balance, right,
• 27:50
  Speaker 3: like you said, trying to make sure that you're not
• 27:55
  Speaker 3: just seen as like a cost center but really a
• 27:57
  Speaker 3: partner and all that.
• 28:00
  Speaker 4: So maybe a.
• 28:02
  Speaker 3: Hopefully less loaded question. But because we are talking about
• 28:06
  Speaker 3: HR and your partnership with all these different teams, can
• 28:10
  Speaker 3: you tell us if you see anything changing in the
• 28:12
  Speaker 3: traditional silos between HR IT leadership AI teams? Are these changing?
• 28:19
  Speaker 3: Is it growing pains, is it going to be something
• 28:22
  Speaker 3: entirely new, or is it just learning new skills and
• 28:27
  Speaker 3: the same functions.
• 28:30
  Speaker 4: Definitely seeing a change. I mean, as an example, Microsoft
• 28:34
  Speaker 4: recently adjusted their chief people officer to also having that
• 28:37
  Speaker 4: AI enablement into their roles. So I think this is
• 28:41
  Speaker 4: happening across companies. Is we're realizing that AI is going
• 28:45
  Speaker 4: to completely transform how work is done in an organization,
• 28:49
  Speaker 4: and we need our workforce to get behind that. Now,
• 28:53
  Speaker 4: one caveat I'll say is I do think that HR
• 28:56
  Speaker 4: and enablement teams we can support our workforce and terms
• 29:00
  Speaker 4: of giving them the tools, giving them the training, and
• 29:03
  Speaker 4: giving them the access. But I also think it's on
• 29:06
  Speaker 4: each individual employee to drive that change and learn that. Like,
• 29:10
  Speaker 4: I think each of us have the responsibility to really
• 29:14
  Speaker 4: figure out how do we use AI in our roles.
• 29:17
  Speaker 4: So for example, we're in our employee Engagement survey, we
• 29:20
  Speaker 4: ask specific questions on do you see your as part
• 29:25
  Speaker 4: of your responsibilities to learn AI and use AI in
• 29:28
  Speaker 4: your role? And we have a you know, I think
• 29:29
  Speaker 4: we have about ninety percent of our workforce that agrees
• 29:32
  Speaker 4: with that other ten percent I'm concerned about because if
• 29:34
  Speaker 4: they don't see AI as something that they should be
• 29:37
  Speaker 4: using and leveraging, I'm concerned they're going to get left behind.
• 29:41
  Speaker 4: But you know what other thing that comes to mind though,
• 29:43
  Speaker 4: is like I think there's a there's a pendulum of
• 29:46
  Speaker 4: like over rotating on training AI that And what I
• 29:50
  Speaker 4: mean by this is like I'm seeing some people say
• 29:53
  Speaker 4: I want to do a training. I mean there's a
• 29:55
  Speaker 4: whole market now for AI trainings like how to use
• 29:59
  Speaker 4: AI for each are or how to use cloud for it,
• 30:03
  Speaker 4: and I'm kind of I'm a little bit skeptical of
• 30:05
  Speaker 4: those things because the way that you learn the best,
• 30:09
  Speaker 4: at least from my own experience, is actually playing with
• 30:12
  Speaker 4: it and using it yourself. So I we really what
• 30:14
  Speaker 4: we're trying to build in our culture is and this
• 30:18
  Speaker 4: is something that comes from HR. This is something comes
• 30:20
  Speaker 4: from it, This comes from our leadership team. Is this
• 30:24
  Speaker 4: genuine curiosity. So I think the conditions of good a
• 30:28
  Speaker 4: adoption in a workforce is really created by all of
• 30:32
  Speaker 4: those leadership HR. It creating a culture of being curious,
• 30:37
  Speaker 4: of being interested, and being able to jump in into
• 30:41
  Speaker 4: cloud and just figure it out. Like I created a
• 30:44
  Speaker 4: dashboard just by playing vibe coding. I didn't realize I
• 30:47
  Speaker 4: would ever be a vibe coder, but now I have
• 30:50
  Speaker 4: the ability to create dashboards that I never in a
• 30:54
  Speaker 4: million years would have been able to before AI. So
• 30:57
  Speaker 4: it's really unlocked the ability for the workforce to be
• 31:02
  Speaker 4: way more creative and way more impactful than they ever were.
• 31:05
  Speaker 4: I mean, I was joking with my boss that if
• 31:08
  Speaker 4: AI takes my job, that's okay, because in the meantime
• 31:11
  Speaker 4: I'm going to do some of the best work of
• 31:14
  Speaker 4: my life because I'm able to do things that I
• 31:17
  Speaker 4: never was before. So that's what's cool about AI is
• 31:22
  Speaker 4: how much it allows non technical people to actually make
• 31:27
  Speaker 4: an impact as well. But the conditions to create that.
• 31:30
  Speaker 4: It's really just driving curiosity, allowing people to be curious,
• 31:34
  Speaker 4: allowing them to practice, giving them the right tools, and
• 31:36
  Speaker 4: that's where it really plays into. But it's it's going
• 31:41
  Speaker 4: to be iterative. I mean, I think we're all learning
• 31:44
  Speaker 4: how in what this future of work will look like.
• 31:48
  Speaker 4: So I don't have a exact picture of what that
• 31:52
  Speaker 4: looks like, but it is a constant collaboration when what's
• 31:55
  Speaker 4: nice is that we have more data than ever to
• 31:57
  Speaker 4: support understanding where teams need support and where we may
• 32:02
  Speaker 4: need to dig in deeper. But it's a cultural thing,
• 32:06
  Speaker 4: it really is. I mean another example I have for
• 32:10
  Speaker 4: building a culture of AI curiosity influency. So that's sort
• 32:14
  Speaker 4: of been a mandate from our executive team, from Pedro
• 32:19
  Speaker 4: and his leadership team that we they just naturally expect
• 32:22
  Speaker 4: everyone to use AI. I mean we should be curious,
• 32:25
  Speaker 4: we should be thinking about how to use it and
• 32:28
  Speaker 4: being creative and our approaches of of AI usage so
• 32:35
  Speaker 4: and One way that we've incentivized that is, I mean,
• 32:39
  Speaker 4: tom Oreana, you probably in our our company next Thing kickoff,
• 32:45
  Speaker 4: we announced some AI use case winners, so we're trying
• 32:48
  Speaker 4: to reward people that are thinking creatively about how to
• 32:52
  Speaker 4: use AI and their work and really highlight those. So
• 32:56
  Speaker 4: another another way that we've done that at Next Think
• 32:59
  Speaker 4: is we've created this grassroots and I shouldn't say we
• 33:02
  Speaker 4: was really Stefan Weber, who was on our enablement team,
• 33:05
  Speaker 4: created this grassroots Next Think AI Eagles, tom Oriana, are
• 33:10
  Speaker 4: you a part of that Next Think AI Eagles.
• 33:13
  Speaker 3: No, but I did submit to the competition my custom
• 33:16
  Speaker 3: to did. I didn't win, but you know it's a
• 33:19
  Speaker 3: fairly narrow application and people are using it, so I'm happy.
• 33:23
  Speaker 4: Okay, we need to get you both the next Think
• 33:25
  Speaker 4: AI Eagles. It's a great We meet what bi weekly
• 33:30
  Speaker 4: and we share different use cases across the company. It's
• 33:33
  Speaker 4: cross functional, so you know, engineers will be talking to
• 33:36
  Speaker 4: HR people, dot and IT people, marketers all across the board.
• 33:41
  Speaker 4: But it's been great, Like, for example, I was trying
• 33:44
  Speaker 4: to figure out how to automate a workflow and someone
• 33:47
  Speaker 4: I prompted the group. I was like, hey, this is
• 33:49
  Speaker 4: what I'm trying to do, and someone from marketing reached
• 33:51
  Speaker 4: out and was like, oh, we already have a tool
• 33:53
  Speaker 4: that can help you with this. So it's been great
• 33:56
  Speaker 4: in terms of just creating like an internal network and
• 33:59
  Speaker 4: creating a wayareness around where there's ways that existing tools
• 34:04
  Speaker 4: with the next thing, we don't have to recreate the
• 34:06
  Speaker 4: wheel every time we're trying to build something. So that's
• 34:10
  Speaker 4: been a really great internal platform for us because it's
• 34:13
  Speaker 4: gotten all the people to share different ideas and make
• 34:18
  Speaker 4: some new connections too. It doesn't hurt.
• 34:21
  Speaker 2: So you use AI all the time, but don't look
• 34:24
  Speaker 2: like you're using AI's But there's the paradox, isn't there
• 34:28
  Speaker 2: there's the ongoing paradox.
• 34:31
  Speaker 4: We're deleting the aashers.
• 34:33
  Speaker 2: Yes, yes, yes, yes, that's the real innovation is using
• 34:38
  Speaker 2: it in a way that doesn't look like you're using it.
• 34:41
  Speaker 3: The formativity of it, yeah, a.
• 34:43
  Speaker 2: Little bit, a little bit. Well, it's delightful to have
• 34:46
  Speaker 2: you have your gap. You really really really enjoyed it.
• 34:50
  Speaker 2: Oh I did have a no, No, we covered it.
• 34:53
  Speaker 2: We covered it. I was going to bring back the
• 34:55
  Speaker 2: mention of the interview process and how you were kind
• 34:58
  Speaker 2: of using you is it spontaneously? So I say that again,
• 35:03
  Speaker 2: delightful to have you on. Gabby, really really enjoyed it.
• 35:05
  Speaker 2: And it's just it's just such an endlessly interesting topic.
• 35:12
  Speaker 2: You know, Tim used to joke or we're we're talking
• 35:14
  Speaker 2: about AI again, and of course we are. It's not
• 35:17
  Speaker 2: Dolvo is it. It's not trivial like and it's not
• 35:20
  Speaker 2: a It's also inexhaustibly fascinating in terms of the different
• 35:28
  Speaker 2: angles you can take on it. So this was one
• 35:30
  Speaker 2: I really really enjoyed and thanks for thanks for bringing
• 35:34
  Speaker 2: those perspectives, Gabby, and thanks, I guess for for helping
• 35:37
  Speaker 2: and make next thing a nice and nice place to work.
• 35:40
  Speaker 2: You know, we we're three of us probably are testify.
• 35:43
  Speaker 4: To that, right, savin Oriata, thank you so much for
• 35:46
  Speaker 4: having me. You two also make next a great place
• 35:49
  Speaker 4: to mark. It's not just hr T, but's doing that,
• 35:52
  Speaker 4: so I thank You're proud that you do as well
• 35:55
  Speaker 4: appreciate it.
• 35:57
  Speaker 1: That's it for this week's Deck show. We'll be back
• 35:59
  Speaker 1: now next week, and if you don't already, be sure
• 36:02
  Speaker 1: to follow the show so you don't miss an episode
• 36:04
  Speaker 1: until next time.