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Josh Tanenbaum (00:02)
This is sort of why I have this confidence that robots will not take all of our jobs, which is AI really enables us to more quickly gather rules or gather data where we were dependent on default rules. And then similarly, once we have new data to work with, we’re in charge of making a decision on how to address it.

Susan White (00:27)
Welcome to The JoyPowered® Workspace Podcast where we help HR and business leaders embrace joy in the workplace. I’m Susan White, owner of Susan Tinder White Consulting, an HR consulting practice. Joining me is my co-host and dear friend, JoDee Curtis, owner of Purple Ink, a large-scale HR consulting firm that I’m an executive collaborator with. Today, we’re going to talk about artificial intelligence. What do we as business leaders and HR professionals need to be aware of and following as this important technology continues to advance and be integrated into our workplaces? James Atkinson wrote an article in SHRM’s HR Quarterly magazine in the winter of 2025 entitled, “AI’s Impact on Talent Strategy.” James cited interesting statistics from SHRM’s 2024 Talent Trends about artificial intelligence. JoDee, let’s share some of those stats if some of our listeners have not seen that article. Would you like to start us off?

JoDee Curtis (01:29)
Only one in four organizations use AI to support HR-related tasks. I have to believe usage will be skyrocketing year over year until it’s universal.

Susan White (01:43)
Of the 25% of organizations that are using AI, two out of three use it to develop job descriptions. More than 42% use it to customize or target job postings to specific groups. And two thirds use it to review or screen applicant resumes, communicate with candidates, or automate candidate searches.

JoDee Curtis (02:07)
Beyond talent acquisitions, some organizations in the SHRM study reported that they are using AI in learning and development by identifying gaps, tracking progress, and pointing to resources.

Susan White (02:24)
I know I’m using ChatGPT, which is my platform of choice for now, for a variety of simple tasks. As an HR consultant, when I get requests to create an agenda, I might go to ChatGPT, tell them the things I want to talk about. They put it in beautiful order. Sometimes for job descriptions or job postings, if I really want to spice something up, I will ask ChatGPT to make it more interesting and have more flavor and more excitement. Sometimes I use it to gather thinking on training content, instructional manuals, sample procedures. I might go out and do some research, but I also then let AI see what it can produce. Clients that I work with are using AI in their ATS systems, especially with chatbots, with one-way recorded virtual interviews, etc. How about you, JoDee, with your clients? What are you hearing about AI in HR?

JoDee Curtis (03:18)
Yeah, well, I know even on our own team, we’re using them to assist with resume reviews in recruiting so we can upload resumes to search for certain keywords or key experience. Our applicant tracking system has some basic AI uses in it, but we’re doing that in Microsoft Copilot as well too, to put them in there. Some of the other things that you mentioned, like job descriptions and agendas, we’re using also. I’m using it constantly in my writing. will say I do… almost everything I write, I’ll write it and then I’ll put it into Microsoft Copilot to say, make it better, right?

Susan White (04:17)
Yes.

JoDee Curtis (04:17)
Or, or how else might I say this?

Susan White (04:19)
Right.

JoDee Curtis (04:19)
Or, you know, I think we’re, we’re not using it to write our blogs or to write our podcast scripts — by the way, podcast scripts is another way I’ve been doing it. And, but I like to write it first and then use it to make me sound a little bit smarter or smoother or powerful. I’ve been using that word in my search of some, I’ll write something and then I’ll say, make this more powerful. And I really like it.

Susan White (04:52)
Yeah, that’s terrific. We know we are just scratching the surface of the power of AI in human resources, so we’ve invited a guest today to get a broader perspective. The guest we have is Josh Tanenbaum. Josh is the managing partner of Rebalance Capital, a workforce tech and fintech venture capital fund that serves as a trusted source of innovation to HR leaders, one in four globally systemically important institutions, and one in ten Fortune 100 companies. Prior to his career in investing and investment banking at Partners Group and Citi, Josh was a human capital advisor at Korn Ferry supporting CHROs and their direct reports through mergers and acquisitions, leadership assessments, and talent acquisition. Josh has presented to two White House administrations and served as a judge for the Clinton-backed Holt Prize. He holds an MBA from Cornell and a BA from the University of Melbourne. Yes, Melbourne, Australia. Josh, welcome, we are so glad that you’re joining us today.

Josh Tanenbaum (06:03)
Thanks for having me.

Susan White (06:04)
First question for you is how are you seeing organizations leverage AI effectively in traditional HR functions?

Josh Tanenbaum (06:13)
Sure. So one, when we think about AI, just to have a definition moment for a second, the way we think about it is in two spheres. One is reducing search costs, meaning how do you get information more efficiently, faster? And then two is enabling personalization, which is taking lots of points, aggregating it, synthesizing it, and ultimately offering a view on what a more personalized experience could be. And so where we see that reflected in sort of the human resources universe is, one, in performance management in particular. And so we see this in terms of, like, analyze your performance status and getting red flags, figuring out trends in your workforce. Do you have the right staff in the right places being utilized and developing low-focus plans with that data? And then similarly, this has become, I think, one of the issues now that everybody’s sort of playing with AI, which is how do you actually support middle manager readiness? And that is when you have so much more AI tooling, how do you switch on the EQ training for those middle managers to install all of these tools and use them effectively and educate and support it? And so really we’re seeing AI come up, if it’s done well, in technical fluency, strategic thinking, and emotional intelligence. Even that needs to be a philosophy that guides underlying AI models and its utility. And then also just how do you evolve models, having continuous learning mindset as a manager to make sure these AI tools are effective. And then lastly, I might just highlight recruiting. I think one of the things that always comes up is the historical bias in reviewing a resume. And so we see AI being used in surfacing candidates that have historically not been considered who have the skills, not the pedigree. We see in the acquisition process, using AI skill simulations almost to replace that resume to figure out exactly do they have the competencies that they’re marketing. And then similarly, there’s this sort of synthesis level in the acquisition process where you’re looking at a first look at does this person fit or not fit. And then of course the ongoing engagement experience in the talent acquisition process. So what that solves from, like, an outcomes perspective is A, time to hire is much lower, but also the optimal hire rate goes much higher. So failure, churn that are for the wrong reasons reduces.

Susan White (09:00)
Terrific.

JoDee Curtis (09:01)
Love it. Yeah. Thank you for sharing that. And what are you seeing AI replacing in HR and what do you believe it will never replace?

Josh Tanenbaum (09:13)
I will give credit to a book that I think is very inspirational called “Power and Prediction.” And Ajay Agrawal, who’s one of the original GenAI pioneers back in 2012 at the University of Toronto, makes this point about what is a decision? And he breaks down a decision really into two pieces. One is prediction and the second is judgment. And I think I agree with his articulation that prediction will be replaced, but judgment will not. And this is sort of why I have this confidence that robots will not take all of our jobs, which is AI really enables us to more quickly gather rules or gather data where we were dependent on default rules. And then similarly, once we have new data to work with, we’re in charge of making a decision on how to address it. So maybe tactically in the HR community, I think we just talked about resume screening, right? And scheduling and sort of AI-enabled automation, data entry, administrative tasks, things like that. But then what you can’t replace is that human touch. It can’t replace culture building. It can’t replace ethical decision-making, right? Because in and of itself, a decision cannot be made without both prediction and judgment. And so one example that comes to mind, both for cultural reasons, as well as for legal reasons, is actually when you fire somebody. So you might be able to get them performance data using AI tools, who would be the right set of people to include in a RIF. But the AI cannot fire that person for you. You need an HR leader who has an orientation to deliver that message, share an understanding to why and deliver an experience where as they get offboarded it’s done with a great deal of humanity.

Susan White (11:17)
I think we need George Clooney flying all over, right? Was that movie “Up in the Air”? Yes, that he would go and deliver that bad news, but you’re right, it takes that human touch. Yeah, love that Josh, thank you. Are there any organizations out there that you think are real leaders in adapting to and integrating AI into their HR functions? And any lessons learned, maybe, that you’re aware of?

Josh Tanenbaum (11:39)
Maybe we’ll start with the second half of that question…

Susan White (11:41)

Josh Tanenbaum (11:41)
…and then let’s go to the leaders who are kind of making the best of the situation that we have. So one, the consistent feedback that I get from CHROs is that we’re kind of muscling through the AI phase. We’re saying there’s this problem and that problem and this tool and that tool and they’re point solutions. And as CHROs, this universe has kind of evolved away from point solutions outside of healthcare and retirement. We need to solve for domain expertise. So what’s really absent of the ecosystem and what big tech firms are trying to create is the system-level technology where AI is at its center, solutions are built around it. And so, you know, in terms of who’s doing it well, you know, one thing I actually want to give credit to is Salesforce. I know we will talk a lot about sort of the job function of an HR leader, but what Salesforce has done really well is actually implementation of AI in governance. Figuring out what policies that enable performance thresholds, thinking about where has AI gone too far? Where does it need to be reeled back? Using skills-based models for performance calibration and pathing. I think those are just a couple of really good examples of where Salesforce has implemented AI. And then I also might shout Shopify, which is the online tech enabled store provider where they use AI as part of their justification for hiring. And so they’ve fed technology into their decision flows. So that’s an example. And then if I were to think about this in between the point solution land and the system levels land, IBM Watson launched Watson Talent, right? And they use it in their own hiring and building to really look at the full firm across the talent architecture to figure out what are the right data points to drive change in the organization.

Susan White (13:50)
Terrific.

Jodee (13:50)
Nice. Yeah, that’s exciting. Who are some of the providers that excite you that our listeners might be aware of?

Josh Tanenbaum (14:01)
So when I think about the landscape, there’s sort of talent acquisition, there’s workforce benefits, and then there’s ongoing employee engagement outside of benefits. And so on the acquisition side, a company that just announced a really sizable fundraise is Mercor, which has had exceptional revenue numbers in a very short period of time, founded by basically post-school students and what they do is basically match expert contractors to generative AI jobs, and then they help build the infrastructure layer to do that job matching and sourcing process. That’s one that comes to mind. And then second is inFeedo AI. inFeedo AI is focused on really enhancing engagement through conversational AI and natural language processing and making the employee voice richer both in its being elevated to management, but also in making those mutants more actionable.

JoDee Curtis (15:05)
Yeah.
Josh Tanenbaum (15:05)
On the benefit side, this is more the infrastructure side than, per se, something HR leaders would buy, but Ideon is another interesting company. This firm develops data sets that enable plan providers to support HR leaders in healthcare plan matching. We are all probably familiar with the concept of ICHRA, which is basically individualized, customized healthcare plans that particularly suits those that are not in sort of the top 15% of the workforce. It allows, at a much lower cost basis, individuals to customize their plans for their life. And I think it’s super indicative of where we are in this environment. Workforces have maturely diversified over time, and now we constantly hear this problem from CHROs of one size doesn’t fit all anymore. And so when you have data sets again, to this earlier theme of personalization, you’re able to at a much lower cost create much more value through the employees in this healthcare plan matching experience.

JoDee Curtis (16:16)
Nice.

Susan White (16:16)
What a great chance of retention and all the good things that come from that. So that’s wonderful. So what advice would you have to any of our listeners that are considering advocating for the higher usage of AI in HR at their organizations? You know, any risk mitigation tactics or anything that can help tell the full story to leadership so that they buy in.

Josh Tanenbaum (16:37)
If the intention is to get the firm to buy in when they’ve yet to adapt, it’s going to be tied to operational KPIs. It’s going to be focused on how can I reduce costs, how can I increase revenue or support business lines and their needs, or how to improve efficiency. Use the same number of people, but find a lot more efficiency with the people that we have. I think ultimately a CEO or CFO is the ultimate accountability partner that we have to build ties to. And if we speak their language, this will become a much easier case. Now, the question is, if you have some AI adoption, but you’re trying to figure out where you can do more or where you can be more strategic, then I think it’s really looking at what are the talent gaps that you have. Where is the literacy gaps that you have? And I think you can advocate to train people to say, if we’re able to invest in our people to adopt these technologies, this should be the output over the long term. I think that’s a worthwhile investment that most leaders will understand. So on the other hand, I think, as I mentioned in the Salesforce example, it is important to also look at where you have to roll things back and say this is what’s worked in our experimentation and this is what hasn’t. But the question is, to your point about mitigation, how do you build in checkpoints in your process, both from the procurement side and in terms of the actual execution side to monitor performance in AI? So for starters, when you’re doing pilots, start with a really small subset of your employee base and have very specific use cases that you’re measuring against. Similarly, look at the underlying server data. Like, where is it being held? Is it on your secure servers or is it on their cloud-based servers? And that in and of itself will be a big risk that we have to monitor in this equation. I think once you get past the security layer, then it’s really about how do you build in monitoring capabilities? When is agentic AI, when are these robotic voices that are creating things starting to be dangerous. And I think you want to start to look at employee voice if it’s internal to see where you’re starting to get negative feedback and then figure out what needs to be adjusted accordingly. So slow and steady wins the race. And you can take a bottoms-up approach and figuring out where to dig in or top-down approach. But no matter what, we have to align in a multi-stakeholder voice to make these things possible. Because it’s legal, it’s people, it’s IT, and it’s the CFO.

Susan White (19:33)
Great advice. Great advice.

JoDee Curtis (19:33)
Yeah, great. Josh, what should we be asking that we don’t even know to ask about? Or what else do our listeners need to know?

Josh Tanenbaum (19:47)
I think one of the things that scares me a bit about this technology paradigm is we’re talking about it like it’s more than just a technology paradigm. We’re saying AI this and AI that, but in reality we’re, like, conflating artificial intelligence, the prediction side and the automation side. And these are two different things. So I think I want to ask everyone to take one step back and ask the question. What are we solving for? And if we could define an intervention, what would that intervention look like? Don’t call it AI, because you might find that AI isn’t the only answer. Beyond AI, we’re already talking about quantum computing, as an example. We’re talking about lots of different technology paradigms that are increasingly being adopted that are very much on the frontier. And if we’re learning anything about AI, it’s that it is the fastest adopted technology paradigm in our history. It took electricity 90 years to get 90% adoption. It’s taken, if you take 2012 as the GenAI introduction, that — this is a debatable year to pinpoint, but that’s 13 years to get to 65%. And so if we don’t think about things as just a bucket, but if we look at things in terms of problems and solutions and defining them in the human experience, I think that will allow us to actually be much more efficient in solving problems. And quite frankly, when you have pressure to implement AI by a stakeholder that doesn’t understand what it does, that is a language that helps us ask more questions to get to the root of what we’re trying to solve.

JoDee Curtis (21:35)
Yeah.

Josh Tanenbaum (21:35)
So I think that’s one thing. I think the other thing that’s worth thinking about is what is going to be the center of truth of information. Some people use Workday, some people use ADP. If you have lots of different vendors in your lineup, keeping the center of truth becomes a lot harder. So I ask us to think about where do you want the central point of information to live and how well can all of your solutions in the HRM universe integrate into that center of truth. And that will help you think about the design of the innovation frameworks that you’re working.

JoDee Curtis (22:17)
Wow, very interesting.

Susan White (22:20)
I do love it. Well, Josh, we ask every guest a JoyPowered® question. So ours for you is, what’s one small step or change you made during your career that boosted your joy at work?

Josh Tanenbaum (22:32)
So I think there is an AI answer and then I’ll just give a non-AI answer if that’s okay too.

Susan White (22:40)
That’s perfect.

Josh Tanenbaum (22:40)
The AI answer is finding, identifying low-value areas of work where AI can be implemented so you can start to think about the richer things in life. I think that is where you can save time and put your energy elsewhere. It has made my life at work. I would say the non-AI answer of what I did in my career was actually make a career switch, which is, I’m not telling you HR leaders to necessarily leave HR, but ask yourself, have you explored enough of the world to be excited with your life? As a recruiter, once upon a time, what I learned was you can do well in your life on two fronts. One is technical and the other is functional. You can either have industry expertise or functional expertise. If you’re listening to this podcast, it’s because you bring really robust, rich HR leadership experience. And if you feel like you love your place and this is the extent of your world and that’s exciting, that’s great. But if you think you can apply HR into a new industry,

and really develop your intellectual curiosity, stretch your imagination, I think life becomes so much more satisfying both in the work and out of it.

Susan White (24:09)
Thank you.

JoDee Curtis (24:10)
I love it. Love it. And Josh, how can our listeners reach you if they would like to connect after today?

Josh Tanenbaum (24:20)
Thanks for asking. So probably two places. One is LinkedIn. That’s probably the best place to interact. And it’s just my name and where I — Rebalance Capital. And then our email is just josh at rebalancecap.com. So there it is up on the air. If you’re looking for guidance, happy to have a conversation in terms of how you’re adopting AI. But also if there are companies that you fear are not enterprise grade and don’t want to spend, like, six months through an RFP to be a waste of time in the end, feel free to just send over the company to us and we’re happy to take a look for you and give you a free write-up.

JoDee Curtis (25:02)
Yeah, nice. Thank you.

Susan White (25:04)
Thank you so much, Josh. I’ve learned a lot and I’ve so enjoyed having you on the show.

JoDee Curtis (25:08)
Me too. Yeah.

Josh Tanenbaum (25:09)
Likewise, Susan, JoDee, thanks so much for having me and congratulations on this great work. Amazing that people get SHRM credits for this and kudos to you for being the center of expertise that people gravitate around.

JoDee Curtis (25:21)
Thank you.

Susan White (25:22)
Thank you very much.

You may be wondering how do I learn more about artificial intelligence, especially on what you may want to bring into your organizations that could enhance your people management. SHRM offers a specialty credential called AI + HI specialty credential that our listeners may want to check out. In this program, participants identify and analyze potential uses of AI in recruitment, talent management, performance management, learning and development, and employee engagement. JoDee, I think you’ve taken a portion of this specialty credential, haven’t you?

JoDee Curtis (25:57)
Yes, I took the course itself and it was fantastic. I have to admit, I felt like I was maybe a five on a scale of one to 10 in terms of my knowledge around AI. After the first class, I’d say I moved down to, like, a two or three. Only because…

Susan White (26:17)
Oh, when you realize what you don’t know.

JoDee Curtis (26:17)
yes, there was so much I didn’t know. But I am trying to, almost every day, implement more and more of the things I’ve learned on there. So it’s a very good course.

Susan White (26:31)
That is terrific. We will put a link to the specialty credential that SHRM offers in our show notes.

JoDee Curtis (26:39)
Yeah. Yeah.

On to our listener question. Susan, our listener asks, “How do you respectfully cut an interview short when you learn early on that is not a good fit?” By the way, I love this question.

Susan White (26:58)
Yeah. You’ve found yourself in many an interview I bet where you’re thinking, oh no…

JoDee Curtis (27:02)
Yes.

Susan White (27:02)
…this is not…

JoDee Curtis (27:03)
Yes.

Susan White (27:03)
…going to be someone we hire. Well, I’ll tell you, I am uncomfortable cutting an interview short. Given the candidate has likely prepared for it, they probably did a little worrying about it, fretting. I’m guessing they dressed up. They took time away from other work or life commitments that they have. And then if it was an in-person interview. They certainly probably drove there or got public transportation there, somehow commuted to see you, thought in their minds it was going to be maybe 30 to 40 minutes with you. I really do believe that that individual sitting across from you, even if it’s virtual, they deserve your attention for at least 25, 30 minutes. You may want to check yourself when you’re having that thought, my gosh, this is not the person. Maybe you’re having a first impression bias in play. Maybe there’s something that person said or did, or they looked a certain way, or there’s something that’s causing you to judge. My vote, my recommendation would be to take a breath, realize you’ve already carved out the time. Let’s show this person respect. If there’s any biases that I think are surfacing here, why don’t I like this person? Set it aside for the moment and listen. Take that time and truly, actively be present physically, emotionally, mentally. And at the end of 25 minutes or so, you certainly can take the time to thank them for coming in. If you feel really confident in your decision, go ahead and tell them then that you don’t think it’s going to be fit on your end and why. Well, that’s very, very courteous. Now, you may not know that or that may not be your protocol. You might want to decide that after the person’s gone, you’re going to in a few days send them a decline email or whatever your practice is. But I just feel like cutting an interview short isn’t the right thing to do. JoDee, I’d love your opinion. You may have very different perspective on this.

JoDee Curtis (28:55)
Susan, I would say I’m… have been somewhere in between. do, I am such an efficiency person. My Maximizer strength wants me to always be…bring out the best of a situation or process. And so I don’t like to waste the candidates’ time either, but I do believe everything you said about, you know, they’ve spent time preparing and it should be worth me learning more about them. I try and even think, you know, might there be something else that this person could be a fit for? So maybe they’re not for this role.

Susan White (29:35)
Sure.

JoDee Curtis (29:39)
But I’ll tell you, I spent many years just trying to create conversation with people who I knew or I felt like were not going to be a great fit. But now, I think if there is something very obvious that I know they’re not going to be a fit, I’ll just tell them. And I’ll just tell them why.

Susan White (30:02)
Yeah, I really do appreciate that and respect it. Before the person leaves, let them know. Don’t go home with hope. Yeah, when you know. Yeah, that’s fair. Thank you.

JoDee Curtis (30:07)
Yeah, yeah, yeah, yeah. And just drag it out for them too. So yeah, yeah.

Susan White (30:15)
So JoDee, it’s time for in the news. A 2025 State of the Workplace Workforce Trends and Productivity Benchmarks Report that was released March 11th, 2025 by the ActivTrak Productivity Lab says that the average workday the United States is now eight hours and 44 minutes, which is 36 minutes shorter than it was prior to 2022.

JoDee Curtis (30:45)
Very interesting.

Susan White (30:45)
I know. They followed over 218,900 employees in 777 companies between January 1st, 2022 and December 18th, 2024. Another interesting finding is that 58% of employees in this study use AI tools in their work in some way, shape, or form. The length of the average workday is going down as the use of AI in the workplace is going up. That does kind of make sense to me. I think it is a good news story for us as we’re seeing that AI may well be making us more efficient and relieving us of some time-consuming work tasks that often kept us at our desks or machines at…

JoDee Curtis (31:13)
Mmm. Yeah, that’s good.

Susan White (31:31)
…clock out times.

JoDee Curtis (31:32)
Yeah.

Susan White (31:33)
During my corporate years of working in large organization, I always worked more than eight hours. I would say… I tried to think, I probably worked at least nine hours a day and then sometimes on the weekend go in and go out. But I always thought I was abnormal because I was, like, worried and I was fretting and wanted to make sure everything was done. But so it startles me when I see the stat that the average work hours in 2025 is eight hours and 44 minutes a day. But maybe because people are connected all the time that they are…

JoDee Curtis (32:02)
Yeah.

Susan White (32:03)
…working even though we think they’re at home or they’re, you know, it’s evening and they’ve got the kids to bed, maybe folks are working. So, surprises me.

JoDee Curtis (32:10)
Yeah. Yeah. Well, I’m sure that my hours are keeping that average up higher. I’m not always proud of that, but I’m not helping the average. Let’s just say that.

Susan White (32:18)
No. You’re always working, I know.

Please tune in next time and make it a JoyPowered® day.

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JoDee Curtis (33:10)
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Susan White (34:24)
Thank you.