Participants

Hosted by Isaac Sacolick, CEO of StarCIO

Special Guests

• Dana Sanderson

Digital Trailblazers

• Joanne Friedman
• Liz Martinez
• Joseph Puglisi
• Martin Davis
• John Patrick Luethe
• Heather May
• Derrick Butts

Summary

The episode focused on skill and outcome-based hiring in the AI era, with participants discussing how traditional hiring practices are evolving due to AI’s impact on the workforce. Isaac led the discussion, sharing research on the shift from credential-based to skills-based hiring, particularly for AI roles. Dana, a former CIO and podcast host, emphasized the importance of storytelling and articulating value delivered in past roles. Experts like Heather and Joanne highlighted the need for strong communication skills, domain expertise, and an understanding of broader ecosystems when seeking or filling leadership positions. The group also touched on the importance of networking, thought leadership, and adapting to the changing demands of AI-driven organizations.

StarCIO Research

Sources

• Skill-based hiring – PEBL and LinkedIn Economic Graph
• Outcome-based hiring – Vetta, WEForum, and ScienceDirect
• Performance-based executive recruiting – Bob Search and InsightGlobal

Transcript

[00:00:00] Speaker A: Greetings everyone. Welcome to this week’s coffee with Digital Trailblazers. Our 160th episode.

Today we’ll be talking about the intersection of AI hiring and getting hired, transforming to skills and outcome based hiring.

And as I’ve been doing over the last few episodes, I’m going to share some research that I dug up around this topic to get you warmed up and understanding what we’re going to be speaking about. Thank you for joining us today.

So let’s just jump right in.

First, let’s start with some very basic definitions so that we’re grounded. What skill based hiring and outcome based hiring is. You can see that on the left hand side here, skill based hiring is a recruitment method that prioritizes a candidate’s skills and competencies over traditional credentials like degrees and past job titles. And what it focuses the hiring manager on is what can this person do as opposed to all the different things listed on their resume or places that they work with or schools that they worked at.

This is a becoming a much larger trend in hiring. I’ll speak to some data around that. But for those of you looking for leadership roles, particularly transformation leadership roles, you might be feeling a little bit different. Like your skills around what you’ve done and what you’re capable around. Agile or data or product management really isn’t making a strong enough story to get hired.

And that’s because once you start getting into leadership roles, hiring leaders are looking for more outcome based hire programs. They vouch candidates based on problems they have solved and results they have delivered. So if you’re going to talk about digital transformation information, what value did you deliver to the organization? How much revenue did it drive?

What was your approach to change management? How many you know, how did you accelerate adoption? And lots of questions around what outcomes you’ve been able to achieve. Now in my research I found a third level of this. We’re not going to talk about performance based executive recruitment. We might cover that in a third installment around this. Performance based to me in our area is really about when the executive leadership and the board has already determined what they want, right? We’re focused on a turnaround, we’re going to do some m and as we need to clean up our operation, we need to spend hire somebody who can address some security deficiencies and they have a very specific set of goals in mind and that’s what they’re hiring for. You can see one of the questions they often ask is can the exec deliver financial results? So very often performance based is in areas like marketing and sales.

We will not be covering that to here. And it’s a big shift. Right. We’re moving away from what you have on paper to what you can accomplish. It requires much clearer role definition and it’s focusing on fairness. Some data around this really like this report from LinkedIn. It talks about just the impact around AI and the talent pipeline that’s required.

AI roles. Talent increases the talent pipeline by 8.2 times when you’re focused on skill based hiring.

Relying on skills when hiring for AI roles could increase the share of women by up to 24%.

And in New first time higher roles, we covered this a few weeks ago. The global talent pool would increase by three and a half times by focusing on skills. Really interesting report from the World Economic.

It talks about how AI is now a greater premium. Having AI skills is a greater premium. 23% higher salaries being reported than what a master’s or a bachelor’s degree is offering. So very interesting point there. And then some stats around recruiting from Insight Global.

Lots of people using AI in recruiting.

74% think AI can assess compatibility of an applicant and job. And 57% of hiring managers are using AI for skill assessment. And that number actually increases when you start looking at C levels in the hiring process. So it’s just some data to share with you. If you look at the very first comments in today’s coffee hour on LinkedIn, you’re going to see the references for, for what I just shared. You’ll see actually a copy of the slide as well if you want to go look at it or use it as reference as we talk about. And in my dashboard here I have the definitions of skill based hiring and outcome based hiring. I want to welcome Dana Sanderson, longtime listener friend of the coffee with Digital Trailblazer. He’s going to be our first response to my first question. Dana, when you think about how AI is changing hiring, what feels most outdated about the traditional ways we define roles and evaluate executives, transformation leaders and even individual contributors?

What do you think is outdated that skill based hiring is starting to address? Welcome to the floor, Dana.

[00:05:39] Speaker B: Well, first of all, thank you very much for the invite. I certainly have been an avid listener and certainly appreciate all the lessons I’ve learned along the way.

When I think about that, Isaac, you know, what feels most outdated is kind of how static and backward looking our role definitions, you know, still are. You know, we define executive roles often based on, you know, titles or reporting structures and years of experience.

Even though AI is accelerating how the work changes underneath Those very roles.

So in reality, you know, the job of an executive that’s hard to do something today probably won’t look like what they’re going to do in 18 months, probably will not look the same in 18 months.

And traditional valuation seems to outweigh often at ways where someone has worked and under underweight or underweights, you know how they think like in, in an AI enabled environment.

I think what matters far more is judgment and adaptability and the ability to lead through uncertainty.

Executives are often called on to make decisions, as we know, with very incomplete information.

And they need to understand what’s that impact at a system level. And you need to be able to guide an organization through change, constant change, which for the very one thing change is, that’s one thing that is constant. So those capabilities don’t always show up well in a resume or a static job description. And I think that’s why we need to start to move to skills and outcome based approaches and they’re becoming much more essential.

[00:07:24] Speaker A: Interesting. Now, Dana, you have a background in higher ed and I know you’ve moved on past there, but you, you run a podcast around higher ed. What’s the, you know, what’s the guidance for higher ed institutions about helping students become more employable in the AI era? What are you guys talking about there?

[00:07:49] Speaker B: Yeah, well, you know, as I left my previous employer, you know, AI, when it first came in and it still is, you know, it was unethical and you know, the conversation was all around cheating and with no disrespect, you know, probably, you know, the idea of cheating in higher ed and colleges, universities been around for hundreds of years. I’m sure when the calculator came it was probably the same thought was being made. And I think that conversation has now changed.

Where, you know, and much of the conversation is also is around, you know, the ethics and I think we’ll probably talk about that a little later, but the ethics of using AI. But I think the universities and colleges and you know, polytechs that have been able to adapt the skills that a student can understand and can use through the use of AI, you know, make will make that student a much better or more employer, employable student.

And when I think about it is, and this is my conversation I often had with students is like, why are you at a university? And one of the things you’re going to get out of university? Because if you’re thinking you’re here to get a degree that’s going to get you a job and that’s the job you’re in forever. Well, that’s a big mistake. I think really when I think about universities and students, it’s, it’s really about you need to have the ability to think right, you need to be a critical thinker. And I think what AI is going to be able to do in this, people pick up that skill is to help with some of the context and some of the content around that, maybe not the context. And you know, I think we’ll probably end up speaking a little bit about, you know, how important context is in terms of AI.

[00:09:26] Speaker A: Thank you, Dana. I made a note around here because we’ve captured a long time ago now just a bunch of competencies that are really important for AI. And when you try to do a match between things like adaptability, critical thinking, a response to a crisis, these just don’t show up on a resume. You’re absolutely right.

And they can come through in scenario planning and question a candidate. But you know, it’s important for us to be able to express this in our skills so that increases our ability to find opportunities and for hiring managers to be clear what they’re expecting of candidates. Derek, you got your first hand raised. We’re talking about skill and outcome based hiring.

What do you want to shed your ciso? What are you shedding from before and which of these two are you focusing on? On?

[00:10:22] Speaker C: Well, when you look at the roles in the traditional way they were described, they were pretty much defined for stability. And when you look at AI environments, they’re really not stable. They’re more unstable than stable. And the traditional roles they were looking for, like fixed responsibilities, separate things like strategies and risk and security. But when you look at AI, it’s really unpredictable and the operating conditions are going to be unpredictable. So I’m really looking at the AI cyber resilience reality of what are they really facing. They need to be able to make decisions on their feet. As Dana mentioned, they have to be able to think and they have to be able to do and make assumptions going to be the best for the organization moving forward. As Dana mentioned, also some of the credentials, people going to school for certain credentials or whatnot, credentials are good on paper, but how well do they apply it to a real world environment? You know, I want somebody that can think on their feet there. When they’re in an adverse situation, will they be able to respond to a failure? Looking at AI models behaving unexpectedly, how are they going to handle risk and will they understand how to transition or transition that risk to something more positive? Or contain it from the executive point of view, you know, as you mentioned earlier, Isaac, you know, looking for efficiency, growth, cost reduction and things of that nature. But from an AI resilience, I’m looking at the demands is really looking at how can I deploy and work with AI in a safe environment, how can I scale it, how can I contain AI failures? Those are kind of attributes of skills that I’d be looking for as I’m hiring somebody. And how can they prove it? You know, one of the things I used to do when I was hiring people, they said they had certain credentials or certain skills. I would say show me and give them a little scenario, give them five minutes to say prove what you know. And it’s one thing if they could think on their feet, that tells me they’ve got the aptitude to be able then to work in this environment and they can learn. But if they stumble and whatnot, they don’t really have what it takes to look at this. As I mentioned, AI is going to be more dynamic and not stable. And I need to get those skill sets, those mindsets, people thinking and that forward thinking to be able to think fast.

[00:12:15] Speaker A: Derek, maybe go and give us a real concrete example. You know, a senior security analyst has every AI buzzword on their resume and you’re saying those are credentials.

You know, you’re trying to evaluate what the person could do, what should they have on their resume?

[00:12:36] Speaker C: They should have that they work with certain tools. So there’s a lot of different chat bots out there, tools. You got Claude, you got Gemini, you got chatgpt, you got, and a lot of new ones that are coming out. I want to see one that they’ve been experimenting or at least using some of those tools in the workplace. And to what extent have they been working as validators? Have they been working with, looking at AI drift, have they been looking at the integration of these AI tools when it comes to the ecosystems of the business that they supporting. Even though it may be short lived or just a little bit of experience, I’m looking for the fact that they have that experience and the fact that what are they doing on their own? So I’ll ask them, in addition to what you’re doing on the job, what kind of learning are you doing on your own when it comes to artificial intelligence, prompting all those different tools that are out there, how to work with enterprise and integration in larger environments or smaller environments, what are some of the risks that you actually have seen or actually understand and can recognize it if it were to Come forth. So these are kind of things again asking them real world questions based on their experience and if they don’t have the experience, they’re not going to be able to address these questions. So that lets me know right then and there that’s not going to be the right person or have the right fit for this particular job.

So again, if they can’t think on their feet from an AI perspective and my lens is going to be working on AI cyber resilience, those are kind of things I want from risk adverse. I want to be able to secure and deploy safely, but also want to say, do you have the whole enterprise spectrum in mind when you’re looking at AI deployment from an enterprise concept? And these are the kind of things I think, you know, even though they’re starting small and working small, I need to understand to what vast or limitations of your growth have you been limited to and what are you looking to do? And ask them where do you see yourself down the road, you know, what are your ambitions and what are your things you’d like to get into? And that gets me know how thirsty or hungry they are to actually dig into AI more.

[00:14:21] Speaker A: I think it’s a good sort of connecting point for everybody speaking. You know, you’re saying tell the story how you’re using AI tools and what you are accomplished. When Heather speaks, she’s, she’s got her hand raised. She’s a, she’s a few down the queue here. Heather, I’m going to be interested to know from you, like, where should we express this right? You know, we’re told to keep our resume short and I’m hearing storytelling here and I’m hearing the hiring manager should look for these stories even before they bring them into an interview.

Martin, what needs to change about hiring? And you know, are you looking for skills or you’re looking for outcomes?

[00:15:00] Speaker D: I think there’s various aspects to this and it’s never just one thing.

So if you think about when you’re hiring someone, first of all you want someone who’s a cultural fit.

So some of those things really, you have to get those by talking to someone, having a conversation, understanding the person far more. And to me that always comes first because if there’s no cultural fit, they can be as skilled as you like. But if they’re going to stick out like a sore thumb or really rough up the edges of everybody else in the company because their culture, their way of working, their behavior is so different to everybody else’s, then the skills and certifications don’t matter.

So that cultural fit is an all important piece to this. But then it comes down to do they have the ability to actually achieve the objectives you want? And that can be demonstrated in different ways. Yeah, certifications are all well and fine. It shows a degree of ability to learn and other things like that. So you can get clues, but they’re not the be all and end all. I’d rather have somebody who has the right cultural fit, has the ability to learn and the ability to understand some of the concepts they’re going to be exposed to and things like this so that you know that they can develop the necessary specific skills. Because let’s face it, a lot of the jobs we have, you’re not going to find the ideal candidate that has every single experience and every single skill that you want. So you’re always going to have to be having someone who you can develop into the role. Therefore the fit and their ability to learn and develop some of those skills you need is crucial.

[00:16:48] Speaker A: I love the statement that I put down do they have the ability to accomplish the objectives and demonstrates the ability to learn. Reason I put that there, Martin, is because like I’ve seen job wrecks that look like, you know, 75 things that people are looking for and we know what happens there. You know, type A personalities apply that are not afraid.

You know, women, introverts stay away from those types of job wrecks and ultimately they’re not serving any real purpose other than filling job bank.

[00:17:25] Speaker D: Yeah, and I think that’s, that’s an important point that you bring up just to kind of dive in that it’s been proven that women will actually apply for jobs only if they think they can meet all of the criteria. Men are far more likely if they meet three out of five criteria to still apply anyway.

So you have to be very, very careful with what you put down there in terms of who you want to attract.

[00:17:54] Speaker A: I agree, Martin. I also put it. We will cover another topic on this cultural fit and hiring. I think it deserves an hour. Today we’re talking about skill and outcome based hiring. Joe, welcome to the floor.

How do you think about this, this new world of hiring and what are you looking for?

For people to express their real skills and what they can do.

[00:18:16] Speaker E: Well, I’ll start with what I’ve always looked for. I’ve said this before and my thinking on this hasn’t changed. The most important characteristic of anyone that’s going to get a job with me is fire in the eyes, real drive, real ambition that has to come across first. And foremost, you know, I counsel people on their careers weekly for the MIT program. And when we, when we meet each week I impress upon people the importance of knowing their brand and, and we talk about companies needs and how your brand has to match to companies need.

So let’s start with on the, on the hiring side, clarity around what exactly it is you need. What is that hole in your staff or hole in your organization that you’re trying to fill? Is it to shore up security? Is, is it to enhance the resilience of your infrastructure? Is it to drive a business through a transformation? If you know what it is as a company that you’re looking for, you can then put together a more appropriate job requisition and you can float it out to people who, if they know their brand can, can say yeah, I’m a fit for that or I’m not a fit for that. And, and it’s, it’s a challenge in the AI world where everybody can take the job requisition and their resume and put them into AI blender and come out with the perfect cover letter and resume.

I think the resume is an artifact from another era. It’s really about how well you can articulate your accomplishments.

What is it that you really can do for a company, what are your capabilities? And I think it’s already been said that you have to be able to adapt and learn. And the last thing I’ll say is you’re no longer only a manager of people. It used to be very important. I think it was just mentioned a cultural fit.

I have to be able to manage a group of people well in future world, maybe tomorrow, I have to be able to manage a group of agents or bots.

That’s a skill that I think is increasingly going to show up on requisitions.

[00:20:31] Speaker A: Joe, that’s a good segue for the question I was going to ask Joanne. I mean so far we’re talking about skill and outcome based hiring, maybe instigated or accelerated because of AI. But Joanne, we have some real disruptive things happening in the AI in companies because of AI. You know, OpenAI and Anthropic came out two weeks ago and said 100% of our coding is now done with English and prompts without getting into writing actual code.

It’s, you know, the types of things that we’re doing in technology and in marketing in particular are changing drastically because of AI and it’s not knowing how to put hands on keyboards anymore to actually accomplish the job.

So I want you to go deeper, Joanne, into what are some of the skills that are non negotiable for technologists, in particular for transformation leaders and even into the executives, because of how AI is disrupting what companies are going to be looking for over the next few years?

[00:21:43] Speaker F: Well, before I begin, to those who may be listening, Happy Chinese New Year.

In the non negotiables, I would say for technologists, you know, AI and data literacy. And I’ll come back to data literacy itself in a moment.

It’s like washing your face, brushing your teeth. If you don’t have it, you’re not going to get very far. But what they really need to understand is how to translate and how to translate business problems into not only data and automation problems, but the other way around.

What is the problem you’re actually trying to solve? And more often than not, although It’s a deceptive UI, when you get a prompt from a ChatGPT or whatever and you type something in, you really have to be very careful. And I think people who are job hunting in particular need to be aware of this. You need to understand the difference in how you speak to a colleague at your own level versus how you speak at the board level versus how you articulate your ideas, because the outcome that you’re going to get from the AI is going to be that much different.

So I think the answer to your questions in one respect is that is now a new non negotiable. We really have to use LLMs and events to cut customer response time, let’s say as the example, from hours to minutes, to do it safely and at scale. Well, how do you translate that problem for multiple parties?

Because you’re managing up, you’re managing across and you’re managing perhaps below if you have a group of people reporting into you. So I think one of the non negotiables is we really have to be upping our game around voicing or putting into words the critical thinking skills that we have and understanding how to address those in the terms that are most relevant to the organization and the outcomes we want to achieve. And I think that is not only part of the critical thinking skills, but I would say for some folks in the arts side of the college world, English is a new language and you need to learn it.

[00:24:11] Speaker A: This is a pretty, you know, strong acceleration of a skill set that is not native to engineers. You know, we’re focused on math and science and physics and solving problems. And look what you just said.

Identifying business problems communicated, even articulating and selling ideas.

You know, these, this, these are things they taught in MBAs and barely, I would say, in my opinion.

[00:24:43] Speaker F: Well, you know, it’s funny that you should say that because someone asked me actually yesterday, a young person who is trying to find a job and has been looking for a while. And so I have an MBA from this school and I have a bachelor’s and I graduated with honors and whatever, whatever. And I asked him about critical thinking skills, which he didn’t quite understand.

And all of the language was very I’m Gen Z, I’m Gen A, almost Gen Z kind of language. And I said to him, how do you think that. That I. I said, do me a favor while we’re talking, throw it into Chachi bt, throw it into anthropic, whatever you want, whatever LLM you choose, and ask this question, does that language translate into business value?

And he got very embarrassed and he said, no, in actuality, it’s giving me very negative. This is where you have to change. I said, that’s exactly my point.

Because engineers, they understand code. Yes, we’ve all written code. We’ve all been there and done that, those of us on the call, and that’s well and good, but you can’t sell an idea anymore or an operational change that’s going to have a business impact using that language. My code can do this, this and this. I don’t care.

What I want to know is what value is it bringing to the table in either cost efficiency or revenue creation, period. Full stop.

[00:26:21] Speaker A: Thank you. Joanne, you mentioned AI literacy. We actually did a coffee hour around that at the end of December, and I just been spending the week listening to it. There were so much good insights in there that I have a blog post coming out on that on Monday that will be a guide and a checklist for developing AI literacy.

Joanne, let’s see. John, Derek, Heather, most of you are all quoted in it, so I will look forward to everybody’s comments on that next week. I want to bring Heather in. Heather, welcome back.

A lot of questions here for you. I’m going to read off a comment here from my good friend Mariela. She said HR is using AI to write the job posts. Candidates have no choice but to use AI to tailor the resume to bypass AI screening. Then AI is being used for first round of interview. So a candidate does not get to show more than what AI is dictating until he or she gets to a hiring manager. Heather, we got a lot of problems here.

A lot of broken things. Just in Mariela’s statement here, how do hiring managers fix this? And how do people who are looking for jobs fix this?

[00:27:36] Speaker G: Well, I think there’s a number of things and there’s so many comments that came up that I really would like to address.

But I think, and each of us who have been speaking has said their most important thing, and my most important thing is human.

That all of the technology, all of the philosophies doesn’t change the fact that if you can’t talk to a human being, you’re in deep doo doo. I mean, there’s no other way to put it.

So when you rely on the AI to write the job description, it doesn’t take into account all the other nuances that would be appropriate. So you just can’t rely on that just to get it out quickly. A candidate cannot rely on taking their resume and taking the job description and putting into chat or any other system to get the perfect resume because it doesn’t reflect authentically on who you are and what you can do for them. So some of the thoughts that I have is that absolutely, you gotta keep the human representative, whether it’s the internal or external recruiting team, the hiring a manager, staying involved and not being absent. And that could be on LinkedIn. When someone reaches out to you and says, I would like to speak with you about this role, I’d like to speak with you about your experience.

I know people that take a half a day, a week, every other week and just respond to those kinds of calls. So that’s one thought that I have.

The, the way that I counsel my candidates for, regardless of how, what my client wants, and I certainly concern myself, myself with them as well. But I like to see a resume that is reflective of what the person has done and chronologically and factually, et cetera. Then I ask for an alignment doc. So take those elements of the job description that you can absolutely speak to. And in both the resume and this alignment doc, it’s not going to be the laundry list that says, I can do this, I can do that. It’s going to be the dollars, the cents, the percentage, the change, the increase, anything that quantifies what this person has done relative to what they’re looking for.

When, as and when you get into the resume, excuse me, into the interview and you start talking to people, you want to flip this, the scenario at some point as a candidate and ask the interviewer what does success look like to you?

Because that gives you some insights that will not be on paper and so you can get a greater insight into what it is that someone’s looking for.

Regarding that upskilling. And I think someone said it, we have to be able to manage those AI agents also once you get into the job, because that’s critical. You’re just not a.

It’s one of the tools that you use.

And I know I’m saying a lot of sound bites that I just heard, but one of the other thoughts that I had was there have been disruptions throughout business, and hiring and recruiting is no different. And I remember when I started, in my early career, I was using books and magazines and ripping things out of these newspapers, photocopying them, sending them to my clients for research, and responding to different information tools. When I started using online tools, I was like, oh, my God, you know, there’s Lexis, there’s Amy, which is the predecessor to Lexis, and Dialog. So many different tools that really disrupted the industry. The information center went away. Those books, I packed them up for other clients. You know, decades of tools in your information, in your card catalog, all that went away. And AI is now the current disruptor.

So as you do these interviews, you can’t just rely on what AI tells you that you’re looking for or what is a candidate you want to show. And so that storytelling that someone referenced is so critical, you’ll be able to. And you can give people scenarios. And yes, you have to think on your feedback, but not everybody can. And I think Liz referenced that in one of her notes during this call. Not everybody learns that way, not everybody responds that way. But if you can put the. Take the pressure off, you’re not looking for the answer. You’re looking for the process.

And I started doing this decades ago. I would give people like 10 questions. If you were looking for the size of the market for X, what would it be that you’d look for?

Excuse me, what would it be that you would do? And when someone said, I go to the Internet, I go to the Internet, to me, that’s not creative. You want to show what are the things that you can do. Maybe in this case it’s going to be the prompt that you use, the different sources that you go after. So that conversation is going to be so, so critical. And I have so many notes here, Isaac. I don’t even want to monopolize the call. But these. There are so many ways that we can look at this, but you want to make that distinction between humans and technology.

[00:32:49] Speaker A: Thank you, Heather. For those of you who do not know Heather, she’s an executive recruiter in this space.

Whenever I’ve used Heather to help me find a role. She’s always going back to me and said what does a successful person look like? What are they accomplishing? And this goes back to something Dana said earlier. We have to be a lot better about how we’re expressing our job wrecks and what we’re looking for. And like I think job rec is broken and we’re going to have to find new ways of expressing it. Let’s just hold off a second. I’m just going to say hello to everybody.

Welcome to this week’s coffee with Digital Trailblazers. We meet every week to talk about topics transformation leaders are facing in their jobs, in their lives, in their ability to find new jobs. And today we we are talking about skill and outcome based hiring.

Very excited to see you all here in this week’s topic. Let me just share. Next week’s conversation will be about National Entrepreneurs Week opportunities for digital Trailblazers. We’re going to talk about a little bit about people who went from startups into corporate and corporate back into startups. We’re going to cover that angle so that folks who are looking for opportunities could see a much broader playing field of where you can go look for jobs. And then on the 27th we’ll be talking about DevOps in the AI era, restating QA’s mission, a topic Liz introduced a few weeks ago. Some new topics I added here. Culture fit in hiring. What does it mean to manage AI agents? You could see we’re always looking for new ideas. I captured them right over here in our conversation. Liz, you have a statement here. Your advice is to abandon the applications unless you have a warm intro.

And Liz, I’ll tell you, I don’t think that’s good enough.

What are you looking for? What are your thoughts around AI skills?

What are non negotiables in this very difficult hiring period?

[00:34:50] Speaker H: So AI skills has to me has turned into such a buzzword that it’s actually completely a misnomer.

Understanding how to communicate has there’s a few things that have been in almost every single person’s comments today.

Really good communications, understanding how to listen and understanding how to project your thoughts at the right level with the right with different people. This is just something that you’re going to have to learn and it’ll be make you successful for your whole entire life. And if you’re not doing it then that’s going to relegate you to be easily replaceable by AI. That’s number one. And when we talk about communications, it’s two ears and one Mouth making sure that you really have good listening skills. The second piece of people keep saying in different ways is a results orientation. Making sure that we that you’re thinking through what is the business that you’re trying to accomplish. How do you add the top line? How do you, you know, protect the bottom line? These are skills that are, like you said, sometimes poorly taught at the MBA level. But there are also skills that you can do, you can learn even when you’re in high school. There’s nothing wrong with learning good communication skills and good business orientation even when you’re in high school. So I think those are the places that you really need to look.

And you know, I’m sort of speaking to people who may be looking for jobs, but in terms of a warm intro, you’re right, they’re hard to find and even if you have one, doesn’t necessarily make a difference.

[00:36:36] Speaker A: Thank you, Liz. I’m going to go straight. John, I think this is the longest you’ve waited to do your first talk at this coffee hour. So you want to talk about what’s changing AI skills or even outcome based hiring? Go ahead, John.

[00:36:52] Speaker I: Oh, thank you so much. Yeah, thank you so much for having me on. I double hit the mute button. I think one of the things that’s always really important on the leadership side is really having the good leadership skills, having accountability. And those to me are non negotiables for people in leadership positions. But now with AI, I think some of the things that are really important is one is curiosity. You got to be curious on what the new technology is that’s coming out. You got to stay up on learning, so you have to be a self learner. And I think the other one is that as a leader you have to be able to choose good technologies when you have limited information. And so I think being able to make good decisions on which technologies to use is just really important in the type of environment that we’re in. And so those are the ones that I love everything else that people have said, but the ones I wanted to add are really for tech is curiosity and the learning, it just never stops in this type of fast moving technology environment that we’re in.

[00:37:53] Speaker A: Derek, I want you to be the first to chime in on this notion of outcome based hiring because it’s very much prevalent in both IT and security roles for however many years you’re in market, 5, 10, 15, 20 years.

And you build up skill sets in different technologies and capabilities in them. You’ve gotten certifications, almost an Alphabet suit in all these things that you can do. And now here you are in the last couple of years and the script is flipped and the question a CISO is going to ask is what are you going to do in the first 12 months to help me reduce my risk exposure and improve identity management? Or you know, Martin, when you come on, talk about, you know, you know, not all the different frameworks and change management that you know, but you know, tell me, you know, how did you increase adoption of our of a CRM? How would you go about doing that when, when people are just stuck behind in the layer of clay of working with the tools are currently using? So Derek, I just find, and Martin, I just find that there’s a transition that probably took 10, 15 years for people to go from, you know, here’s all the bells and whistles into my resume to being able to articulate what outcomes you can drive. And now all that is compacted to a point where we have much younger people who have to talk about what outcomes they can drive with a lot more confidence.

How do you provide advice to them, Derek?

[00:39:41] Speaker C: Derek yeah, I think you’re looking at the bigger picture instead of the enterprise is where I focus. So instead of looking at just the best value and deliverable outcomes for the organization, I’m looking at what are the best resilient and relevant outcomes and results for the organization. So this also comes because now in an artificial world, it’s not just about delivering value, it’s now delivering and how to avoid harm or being safe when you actually deploy these tools. Looking at the bigger realm of risk mitigation, looking at containments, how to improve these things. These are all things go into the quantification of resilience maturity. So now before you had looked at companies looking at what’s my security posture? Now I’m looking at what’s my AI maturity security posture. These are things that are going to have to be evolved, doesn’t happen overnight. So I have to introduce things like AI governance. I have to look at AI risk modeling. I have to look at AI incident response. I have to look at all the cross function areas and decisions that need to be made and look at how AI is going to be relevant and affect each of those events across the board. I have to look at the time it’s going to take me to now not only identify an AI risk or issue or challenge, but to detect it and mitigate it and contain it. I need to be able to prove audibility.

All these things now they’re moving that much faster, means My systems need to be upgraded. So I need to get my ecosystem upgraded to now work in an artificial intelligence world. I need to get my business culture upgraded to think and work in an artificial intelligence world as well. And this also goes back to showing to the decision maker. If I’m looking at these, what are the trade offs that I’m looking at? You know, the, the simplicity of the things that I need to do. Money, revenue, generations, yes, that’s my key focus. But can I do it in a secure manner? Can I use artificial intelligence to help me get that canal, minimize my risk at the speed at which I want to go? Can I take the lessons that I learned, institutionalize across my business culture to make sure I’m doing the best thing moving forward and also building the resilience portfolio.

The entire organization, as mentioned in last week’s discussion, it’s not just one person that’s in charge of executing this, it’s the whole organization that’s really required to do this. So if I’m an executive looking at this, I want to be able to migrate and AI digitally transform my entire organization to have the best outcome for my leadership.

[00:41:55] Speaker A: Folks, if you’re struggling with this, I’ve got a bunch of experts here talking about how to translate what you’re doing into skills and outcomes. And if you’re a hiring leader or manager, the same goes what to look for, how to express your job recommendation. I got a lot of experts here.

Martin, my same question to you. How do you help people cross that chasm where they can talk about outcomes in terms of what they’ve personally accomplished and capable of doing?

[00:42:25] Speaker D: I think it’s important to think about the value delivered. And I’ve always, whenever I’m kind of writing these things down or talking with somebody, coaching them them is think about how you’ve delivered value to the organization.

Because that’s what really matters. Yeah, the.

How you, how you’ve delivered value and your approach to delivering value, because that’s as well. So being able to demonstrate that you’ve taken the right steps to get there and your thought processes, your structure, that’s also so crucial. And if you even think about, think back to doing an exam, especially at university or something like that, they often used to say show how you’ve reasoned and your logic to get to the end result.

Because sometimes even if the answer is wrong at the end, your approach has been spot on. You’ve taken the right steps to get there. So it’s so important to demonstrate the intent, demonstrate the thought processes, demonstrate the value.

And by working your way through, you can show that you have the ability to do critical thinking, the ability to be logical, the ability to make things work.

Because if you’ve got those skills and you’re thrown into something new, you can reason it through, you can actually take the steps necessary. So if you’re having an interview, then think about what outcomes you’ve delivered and how you got there. That’s going be to kind of critical. And the more you can show those clips of where you’ve delivered value in your resume, the better because you’re then kind of starting to put a hook in there that people can see, say, hey, I delivered this and it delivered X to the company. And then that kind of maybe gets people more interested. Obviously it’s a very difficult situation with AI reviewing resumes and everything like this.

[00:44:20] Speaker A: Thank you, Martin. You see, I already captured what is your approach to delivering value to the organization. Have concrete examples, show your reason and approach. I think that’s really good practice question for anybody who is looking to get hired or anybody who’s looking to hire someone. Joanne, just hold off a second. I want to bring Dana back in to the conversation talking about AI skills and outcome based hiring.

Just share your some of your thoughts around that.

[00:44:50] Speaker B: So first of all, there’s been such incredible information sharing here. It’s almost impossible to keep up with, but I’d have something new, but let me give it my best shot. So I think there’s a couple things here and I think when it comes back is I think it’s really important that people be able to connect their outcomes and to the context. And what do I mean by that?

Martin just talked about impact and what was achieved and what was done. And I think it’s really important through that that we understand what, how, what choices were made and what people actually stop doing as opposed to what they continue to do and how they manage through all those different constraints.

A couple other points I’d make is, oh my God, I wish academics. I hope there’s some academics listening to this because I think there’s a, a big miss in what’s being presented, what’s being taught in universities around AI with respect to what’s happening in what we’ll call, to what we’ll call to be the real world. And I think really, I think somebody brought it up before. It’s, you know, part of that, that new skill is, you know, the liberal arts, once thought of as not being that important, are becoming much, much more critical because we go back to the Same sorts of discussions. It’s about being great communicator, it’s about being a great listener, it’s being a great storyteller. And, and the ability for people to actually say, be very explicit about what changed, you know, with their leadership or, or what changed when they were working, you know, did they reduce, reduce risk or did they make better decision in making, you know, in, in the context of the environment I work in is, you know, did, did we, did we make the student experience?

Did we actually strengthen it and, and did we build organizational capability? And I often think, you know, while AI is, you know, AI is certainly, how do I put this? Microsoft. I hate to bring up Microsoft, but Microsoft to some extent actually did a pretty good branding when they said it’s a copilot. I really think AI is that thing that sits beside you. It doesn’t do your thinking, but can help you make better thoughts and better decisions.

But you cannot always trust what it says. Back to, you have to be a strong, critical thinker.

[00:47:10] Speaker A: Thank you, Dana. I got a bunch of people raising their hands and we’ve got 13 minutes left. I don’t want to take any time from them. Go ahead, Joanne.

[00:47:19] Speaker F: Okay, a couple of things. First of all, I want to mention, you know, the, the question before about how do you manage AI if it’s part of your team? You can’t, you can’t unless you have the authority and the accountability for it. And usually that’s a group because the AI will go across functions and across rules. So let’s be very careful about how you manage it. You have to have the authority to do so. And that leads me to my second point and something that Martin mentioned as well, which is not only are we in need of being able to discuss how we produce value, but we need to be able to do it in the context of the type of organization we’re telling the story to.

Domain expertise is making a big comeback and a lot more often than people realize, because what companies are starting to look at is their ecosystem.

If I’m a manufacturer, I’m looking at my supply chain and my customers. Customer. So that notion of an ecosystem around the companies that you’re talking to, you need to be able to translate your value and the value you’ve created into that bigger picture. And this is where highlighting domain expertise becomes very, very critical. I’m a critical thinker. I’ve been able to provide value, but I’ve been able to do it in this environment.

Not narrowly, but broadly, because skills are translatable across sectors and across industries.

So when you position the statement of how I create value, make sure if you’re looking for a job that you can articulate well, how did that impact the other parts of your ecosystem, your trading partners, the companies that you do business with, how does it benefit them as well? Because the. That’s now becoming a critical item for leadership across sectors, across industries.

[00:49:19] Speaker A: Interesting. Thank you, Joanne. Let’s go to Liz. Liz, you gave me a new topic is selling a critical skill set to drive transformation in AI adoption. I am putting that on the list. Go ahead, Liz.

[00:49:31] Speaker H: Well, I just want to piggyback on a couple of things that Joanne mentioned because I’m wondering if, if domain expertise is really what’s most value or the ability to think more broadly across the ecosystem.

You know, I think that, and that actually dovetails into how people are measured or KPIs or whatever it is that people are measured against.

And we all know that what is measured is, gets, gets done or whatever. There’s some. How come I can’t think of this phrase that what you measure actually gets worked on? Right.

So if in fact what we’re giving people is very myopic measurements that are not ecosystem based, then they will actually be. Thank you. What you measure gets managed. Thank you, Dana.

But then we’re not really supporting the idea of more of an ecosystem thought process and getting people to think that way. And if you’re not, if you’re in the job market, showing that you can, demonstrating that you can think that way will be extremely valuable to organizations who do have that mindset. And if they’re not necessarily ready, then it’s a good, a good signal not to necessarily work there.

[00:50:55] Speaker A: Actually, as I captured that here, learn the ecosystem of your industry. I think it’s a really smart comment. In healthcare, extremely complicated ecosystem construction, very complicated ecosystem manufacturing with very wide and deep supply chains and distribution channels, very complicated ecosystem. And by understanding that that’s where you can find opportunities just, you know, in your job that you have now before you have to go out looking. I think it’s a really good comment to share with people. Thank you for Liz. I’m going to move on to John and Heather and Derek. We’ve got three people in eight minutes. Go ahead, John.

[00:51:35] Speaker I: Just short comment is a lot of times when you ask people what they do and what they delivered, they, they’ll speak for their whole organization and that can cause serious mismatches. And so I think it’s really important for, for the people that are hiring to figure out like what level and like the amount of management versus actually direct hands on that they need people to do. And then when, when they’re interviewing people, make sure that they’re, they’re getting people the same level that the. So, so that there’s no expectation mismatch. And so because a lot of times when people speak, they’re, they’re really describing what their organization does, what their team does, what the. But, but when you need a leader, like you’re hiring for a specific person to either manage, lead or directly do something. And so you got to get a good match between what you need and what the other person is experiencing. Otherwise it’s just not going to be a good hire. And that’s super important with what we’re talking about.

[00:52:23] Speaker A: Thank you, John. Heather, welcome back.

[00:52:25] Speaker G: Thank you.

2 comments and I know we’re at the end, so these will be my final comments.

When Dana mentioned that he thinks that universities are missing the boat, I can tell you that one of the other disruptors which was outsourcing, I literally went to India and, and I worked with some of the universities there to try to develop curricula that would meet the needs of businesses. And I think that this would be another time to do that so the companies recognize what they need and make sure that classes and programs are offered accordingly. And then my daughter had learning issues when she was younger and when she got to college and she was successful in spite of that. So she found ways of accommodating. And as we learn, which is the theme here, as we learn how to use AI, one of the things that she taught me is as she got to college, that my thoughts have thoughts. And that expression meant so much to me as a parent. But I think in business when you realize using AI you can’t just take everything for face value, you’re getting a thought. How are you going to apply that thought? How are you going to use that thought? How are you going to expand upon it?

So my sound bite for the day is thoughts have thoughts.

[00:53:44] Speaker A: Interesting. Maybe we’ll have your daughter join us here and we’ll have a whole topic just on that.

Go ahead, Derek.

[00:53:53] Speaker C: Yeah, so again, a lot of good discussion here. Ecosystem, cross function, all these different outcomes, KPIs. I mean, I think it’s the biggest thing that walk away is the skills that you’re looking to hire. The biggest thing I would look for can it deliver results without sacrificing resilience.

It has to be able to focus on the greater enterprise. It has to be able to Focus on the outcomes, the key performance and what’s the demands of that industry is going to be. But at the end of the day, it has to be able to withstand the uncertainty that artificial intelligence is going to bring and be able to think through that proactively versus reactively. Those are the kind of things that are going to give you the best value for the buck move moving forward. And those are the kind of things leadership need to help align to moving forward.

[00:54:35] Speaker A: It’s an interesting point. I don’t know how to capture that, Derek, but what you’re getting at is that, you know, we used to think of people as, you know, innovation drivers and others who are, you know, risk managers and you’re, you’re suggesting that people need a little bit of both and be able to articulate trade offs between both. I think that’s really, I think that’s really smart way of looking at hiring and looking to make sure you are hirable. Go ahead, Joe.

[00:55:05] Speaker E: I just want to add one thought.

There’s another dimension to looking for a job.

People can be measured on performance, skills and all that stuff we’ve been talking about, but you also have to be able to demonstrate that you can be trusted or relied upon. And to that end, I suggest that people build their network and have others who can speak to their trustworthiness.

It’s very hard to sell your own trustworthiness in an interview situation, but this is where references can be invaluable. People you’ve worked with that know your style, know who you are, know that you have, have their back when they really need it, those people can speak up for you. And, and I will take someone I can trust over someone who’s very adept at skills any day of the week.

[00:55:53] Speaker A: Joe, I’m going to let you plug what you think is some of the better ways to build your network. Liz said earlier in the comments you need to get walked into job opportunities. That means proactively networking. What should people be doing both as a hiring leader or as a potential candidate?

[00:56:12] Speaker E: Oh my goodness. I could go on for an hour on this one.

[00:56:15] Speaker A: Isaac, you got three minutes?

[00:56:17] Speaker E: Yeah, yeah. Look, it’s, it’s critically important that you not sit in front of your computer screen and click on Apply, Apply, apply. This is, it’s a waste of time, frankly.

Companies have needs. They don’t always have a job requisition, they don’t always have a posting. But somebody at the company knows that there’s a hole in their staff or a hole in their, in their organization that has to be filled by someone with a certain set of characteristics.

It’s not so much who you know in this. In this world today, it’s who knows you. So I. I counsel people to get out there and make sure that you have a clear and concise statement of your brand. What are you good at? What do you really excel at? What problems can you solve? And you need to spread that to everybody you meet every day of the week, in every situation. Not just executive recruiters, not hiring agencies, everybody you meet because you don’t know who knows who. And that person might know someone at a company that has the need that your skills fit and that’s how your job finds you. I’ll stop there, but I could go on.

[00:57:27] Speaker A: I. It’s a perfect place to stop. I think that networking is a skill set that everybody needs to do very proactively, whether you’re doing it through online channels, whether you’re doing it through communities like the Star CIO Digital Trailblazer community, whether you’re going to SIM events, which Joe and I are both actively involved with.

Find something that works for you and dedicate yourself to being able to meet other people, have a conversation with other people, make an introduction to other people. I think it’s just so important.

Joanne, do you have a final thought here?

[00:58:05] Speaker F: Yeah, very quick final thought. To Joe’s point and to many of the others, just as we, you know, speak on. On coffee with digital Trailblazers, Key point, especially in an AI world, become a thought leader.

They can be your own thoughts, they can be topical, they can be something that you’re tinkering with, they can be your hobby. Be a thought leader in whatever domain you choose, but be a thought leader.

[00:58:32] Speaker A: We are going to have to cover that, Joanne, because I get that question a lot. I mean, obviously I’m a thought leader. I’ve written books. I speak and people come to me and say, should I start a blog or a podcast or whatever channel they think they’re most interested in? And most of us who are speakers here are doing things like that. I think we’re going to dedicate a session about become a thought leader and what that means and what your opportunities are and what you’re signing up for. Thank you, Joanne, for that. Folks, speaking about thought leader, I will be on Michael Krigsman’s CxOTalk just in a little bit over an hour.

Michael runs one of the best shows on the Internet. I think he’s in episode 600 or something like that. This is a show around advice for CIOs around delivering value from AI. You can get to the event@cxotalk.com there’s also a link in the comments that you can join on LinkedIn. Very similar to here. You could share Comments Throw me a softball. I love hitting them Our Upcoming Coffee hours on the 20th we’ll be having National Entrepreneurs Week, opportunities for digital trailblazers to go and get involved in startups. And on the 27th we’ll have DevOps in the AI era, restating QA’s mission. I’ve got four more topics here to figure out when I’m going to schedule them.

Jay The URL is CxO cxotalk.com and if you scroll up at the very top of the comments from today, you’ll see a link from LinkedIn. You could just do a search on CxOTalk on LinkedIn to find it. I just don’t have it handy right now. Folks, thank you for joining this week.

Good luck to all the Olympic athletes that are out there. It’s also Olympic Week. I’m a big Olympic fan and I’ll see you all here next week at the coffee with Digital Trailblazers. You can find our next event at starcio. Com Coffee, which will redirect later today, and you can also find our past episodes at drive starcio.com Coffee. Thank you Dana Sanderson for being our special guest today and thank you to all of our speakers, everybody. Have a great weekend.