Guest: Jon Whittle
What AI Means for Your Next 10 Years at Work
Episode 346 - As AI reshapes the workplace, experienced professionals face a new challenge: combining decades of expertise with emerging technological capabilities. Professor Jon Whittle explains why successful AI adoption depends on much more than technology, and what professionals over 40 can do to remain competitive.
Artificial intelligence is changing how organizations operate, what employers expect, and how professionals demonstrate their value. For experienced workers, the challenge is not to abandon decades of expertise, but to learn how to apply it in a workplace being redesigned around AI.
For professionals in their 40s, 50s and 60s, the conversation about artificial intelligence has become increasingly difficult to ignore. Every week brings another prediction about disappearing jobs, another announcement about AI agents performing sophisticated tasks, or another company explaining how technology will allow it to operate with fewer employees. For people who have spent decades building expertise, professional relationships and a reputation for delivering results, the uncertainty raises a legitimate concern: how much of that accumulated experience will employers value in five or ten years?
As a career coach working primarily with experienced corporate professionals, I see how this uncertainty affects people's confidence. Some are already looking for work after redundancy, while others are considering whether their current roles will remain relevant. Many understand that they need to learn about AI but are unsure what meaningful proficiency looks like, particularly when their professional strengths have traditionally been leadership, strategy, communication and organizational judgment rather than technology.
I recently revisited this question with Jon Whittle, an AI expert with more than three decades of experience, a former senior leader at CSIRO's Data61, and now a professor at Melbourne Business School. When we first spoke earlier this year, I was considerably more concerned about AI's implications for careers than he was. Several months later, despite significant advances in the technology, his position had not fundamentally changed.
What emerged from our conversation was a more useful way to think about career resilience. The biggest challenge for experienced professionals may not be that AI makes their expertise obsolete, but that employers increasingly expect them to combine that expertise with capabilities they have not yet developed. This is an important distinction because it shifts the conversation from defending an existing career to actively shaping its next stage.
The AI Jobs Debate Is More Complicated Than the Headlines Suggest
One reason I find the current conversation about AI frustrating is that it often treats technological capability and employment outcomes as though they are the same thing. A system demonstrates that it can perform a sophisticated task, and the next headline predicts the disappearance of an entire profession. Yet the distance between a technology performing a task successfully and an organization eliminating a role is considerable.
There is evidence of genuine disruption, particularly among younger workers. An August 2026 Stanford Digital Economy Lab working paper examined US payroll data covering millions of employees. It found no evidence of widespread economy-wide job displacement, but employment among workers aged 22 to 25 in AI-exposed occupations was 19% below where it would have been had it kept pace with less-exposed peers. Experienced workers showed no comparable employment gap. The findings are significant, although the analysis does not establish that AI alone caused every observed difference.
That distinction matters. The employment consequences of AI are unlikely to be uniform across generations, industries or professional disciplines. Junior employees whose work involves routine research, drafting, analysis or administrative tasks may face different pressures from senior professionals whose responsibilities involve negotiating complex decisions, managing relationships, influencing stakeholders and being accountable for organizational outcomes.
However, experienced professionals should be cautious about interpreting those differences as a guarantee of security. Employers can redesign roles, reduce hiring, consolidate teams or change expectations without eliminating entire occupations. The more relevant question is how the composition of a job changes as AI becomes capable of performing more of its constituent tasks.
Jon's assessment is that organizations are still struggling to translate impressive technological capabilities into meaningful business outcomes. He works with companies attempting to implement AI and sees considerable difficulty moving beyond software licenses, training programs and experimental projects. As he explained, organizations are ecosystems of people whose work depends on communication, influence, negotiation and collective decision-making.
That observation is important because it challenges the assumption that technical feasibility automatically produces organizational transformation. A company may be able to automate the preparation of a financial report without being able to automate the judgment required to explain its implications to a board, negotiate competing priorities or decide what action to take.
For experienced professionals, this creates both an opportunity and a warning. Their accumulated knowledge remains relevant, but they need to understand which parts of their work are becoming easier to automate and where their contribution can move further up the value chain.
AI Fluency Is Becoming Part of Professional Competence
During our conversation, Jon described a recent strategy workshop in which a CEO expressed frustration that members of his senior leadership team were not using AI sufficiently. The organization could track usage of its internal tools, and the CEO was paying attention to who was engaging with them.
It was a revealing example of how quickly employer expectations are changing. For many years, an executive could reasonably delegate technological implementation to specialists while concentrating on strategy, commercial performance and people leadership. AI is making that separation increasingly difficult because the technology potentially affects almost every business function.
Jon was unequivocal about the implications for experienced professionals: "I think it has become a non-negotiable for people to have AI skills right now."
There is evidence supporting the broader direction of his argument. The World Economic Forum's Future of Jobs Report 2025, based on responses from more than 1,000 employers, estimated that nearly 40% of existing job skills would change by 2030. AI and big data were among the fastest-growing skill areas, alongside technological literacy. At the same time, employers continued to emphasize analytical thinking, resilience, leadership and collaboration.
The implication is not that every executive must become a programmer or AI engineer. It is that technological literacy is increasingly becoming inseparable from broader professional competence. A finance leader needs to understand how AI changes financial analysis and reporting. An HR executive needs to understand its implications for recruitment, workforce planning and employee development. A marketing director needs to understand how AI changes content production, customer insights and competitive differentiation.
For someone seeking a new job, the challenge extends beyond listing ChatGPT or Microsoft Copilot among their technical skills. Employers need evidence that candidates understand how AI can improve outcomes in their particular field, where its limitations lie, and how to introduce it responsibly.
I would encourage experienced job seekers to examine their professional achievements through this lens. If you have led transformation programs, redesigned processes, improved productivity or managed complex stakeholder relationships, you already possess experience that can be relevant to AI implementation. What may be missing is the ability to explain how you would apply those capabilities in an AI-enabled organization.
This is also where I would challenge a common assumption about professional development. Completing an AI course may demonstrate initiative, but the certificate itself is not necessarily evidence of competence. Employers are more likely to be interested in whether you can identify a business problem, evaluate how AI might help, understand the risks and explain the results.
The Hardest Part of AI Transformation May Have Little to Do With Technology
Perhaps the most important insight from my conversation with Jon concerned the difficulties organizations face when attempting to implement AI at scale.
He has developed a framework covering 14 dimensions of successful AI adoption, drawing on research and his experience advising organizations. These dimensions fall into three broad categories: leadership and vision, people and culture, and governance and trust. He estimates that approximately 80% concern nontechnical factors.
This challenges the way many organizations initially approached generative AI. The assumption was that providing employees with access to sophisticated tools would naturally produce innovation, efficiency and productivity improvements. Companies purchased licenses, offered training and encouraged experimentation, but often failed to establish what they wanted to achieve or how work would need to change.
Recent research reinforces Jon's assessment. A 2026 McKinsey study on AI readiness found that 70% of surveyed employees and leaders felt personally prepared to adopt AI, while only 27% of leaders believed their organizations were ready to make the necessary changes. The study also found that organizational readiness was more strongly associated with capturing business value than individual readiness alone.
This helps explain why companies can have enthusiastic employees using AI every day without achieving substantial improvements in business performance. An employee might save two hours preparing a report, but if the organization has not reconsidered its processes, those hours may simply be absorbed by additional meetings, reporting or administrative work.
Jon made this point during our conversation. Organizations need to decide what they will actually do with the capacity created by AI. Otherwise, individual productivity improvements may never translate into meaningful organizational benefits.
For experienced professionals, particularly those with backgrounds in change management, operations, HR, strategy and transformation, this is a potentially important career opportunity.
I am already seeing this among my clients. Some senior HR leaders are working much more closely with technology executives, while others are taking responsibility for teams and initiatives that would previously have sat firmly within IT. Jon believes there is a credible argument for chief people officers to lead certain AI transformations because so much of the challenge involves changing human behavior.
I agree, with one qualification. AI transformation cannot become the responsibility of HR simply because it involves people. It requires close cooperation between technology, operations, finance, risk and people functions, supported by executive leadership that understands both the commercial opportunity and the organizational consequences.
The professionals who can bring these disciplines together may become especially valuable. They do not necessarily need to understand every technical detail, but they must know enough to ask informed questions, recognize unrealistic expectations and help organizations move from experimentation to sustainable implementation.
The Career Advantage of Learning While Between Jobs
One of the most encouraging parts of our discussion concerned professionals who are currently unemployed.
A period between roles can feel like a professional setback, particularly for people who have enjoyed long, successful careers. There is often pressure to spend every available hour applying for positions, contacting recruiters and trying to secure interviews. Professional development can feel secondary when the immediate objective is finding work.
Jon offered a different perspective. He suggested that people between roles may have an advantage because they have something many employed executives lack: sufficient time to experiment seriously with AI.
He described friends and colleagues who had used career transitions to develop their capabilities and subsequently returned to familiar professional roles with considerably greater technological confidence. They did not necessarily become AI specialists. Instead, they brought additional skills into positions where their existing experience was already valuable.
I have seen similar results in my coaching practice. One client in Europe invested several months in an executive AI program during his transition. Another, based in Australia, spent approximately six months working through free AI learning resources because paid programs were financially out of reach. The Australian client subsequently received two job offers connected to the AI knowledge he had developed.
These examples do not establish that AI training guarantees employment, but they illustrate how a transition can be used constructively. Learning becomes particularly valuable when it is connected to a clear professional direction rather than pursued simply because a topic is fashionable.
Jon's advice was refreshingly practical. Despite teaching executive AI programs at Melbourne Business School, he emphasized that formal education is not the only route to developing competence. His own learning approach involves examining an ordinary task and asking whether AI could help complete it.
"I wonder if AI could do that," he explained, describing how he regularly experiments with unfamiliar capabilities.
That approach is accessible to almost anyone. A senior professional might use AI to analyze a public annual report, develop alternative approaches to a business problem, build a simple research workflow or experiment with creating a presentation from existing material. The objective should be to understand what the technology does well, where it fails, and how much human intervention is required.
For job seekers, I would add another step: document what you learn. Being able to explain an experiment, its limitations and its potential business application can provide more convincing evidence of AI fluency than a generic claim on a résumé.
There are also important boundaries. Experimentation with public or fictional data is very different from uploading confidential employer information, customer records or commercially sensitive documents into an unauthorized system. Responsible AI use must include an understanding of privacy, security and organizational policy.
The goal is not to become dependent on AI for every task. It is to become sufficiently familiar with its capabilities that you can make informed decisions about when and how to use it.
AI Has Not Eliminated the Need for Professional Networks
Our discussion eventually turned to an Australian 60 Minutes investigation into AI and recruitment, including concerns about algorithmic bias and applicants being rejected without meaningful human engagement.
The stories were troubling, particularly those involving candidates who had submitted hundreds of applications without receiving responses. Yet Jon questioned whether the program had convincingly established that AI was responsible for those outcomes. He also observed that applying repeatedly without engaging professional contacts had never been a particularly effective job-search strategy.
His own career provided an example. In 2005, while seeking his first academic appointment, he submitted approximately 45 applications to universities around the world and received no responses. He eventually changed his approach, contacted his network and secured a position through a connection at a university in Virginia.
The experience predates the current generation of AI recruitment tools by nearly two decades.
This is a point I regularly make to my clients. The frustration of sending large numbers of applications and hearing nothing back is not new. What AI has changed is the ease with which candidates can produce and submit applications, potentially increasing competition and making an already difficult process feel even more impersonal.
However, I would not go so far as to suggest that recruitment technology is irrelevant or that concerns about algorithmic bias are exaggerated. These systems can influence who gets considered, how candidates are evaluated and whether certain patterns of disadvantage are reinforced.
AI-driven hiring also raises legitimate legal and governance questions. Employers cannot simply assume that a technology vendor has eliminated discrimination risks. The US Equal Employment Opportunity Commission's guidance on AI and employment decisions makes clear that selection procedures using software or algorithms can raise discrimination concerns under existing employment law. The guidance is US-specific, but the underlying principle is relevant internationally: automation does not remove an employer's responsibility for fair hiring.
For job seekers, two approaches remain important. First, applications need to communicate relevant qualifications and experience clearly, using language that reflects the actual requirements of the role. Second, candidates need to develop professional relationships that allow employers to understand their capabilities beyond what appears in a résumé.
This becomes particularly important for experienced professionals whose value may not fit neatly into a conventional job description. A senior executive moving between industries, for example, may have highly transferable experience that is difficult to communicate through keywords alone.
Professional visibility can help bridge that gap. During our conversation, Jon described how he had become increasingly active on LinkedIn and had started publishing longer articles on Substack. Initially, he had many of the reservations I hear from my own clients: concerns about time, relevance and whether he had anything sufficiently interesting to contribute.
His experience illustrates an important point. Professional reputation is not established only through job titles and formal credentials. It is also developed through the ideas we share, the conversations we contribute to and the expertise other people can see.
For professionals who have spent decades accumulating knowledge, thoughtful writing and professional engagement can make that experience more visible. It does not require becoming a social media personality. It requires finding appropriate ways to demonstrate what you know and how you think.
Career Resilience Requires More Than Technical Skills
There is one aspect of Jon's perspective that deserves particular attention.
When I asked which capabilities would remain valuable as AI improved, he challenged the familiar reassurance that creativity, empathy and judgment are uniquely human and therefore protected from automation. AI is already demonstrating capabilities in these areas, even if their nature and reliability remain contested.
I think this is an important correction to the career advice frequently offered to experienced professionals. Telling someone to concentrate on being creative or empathetic because AI will never possess those qualities is an increasingly fragile argument. It assumes that technological capabilities will remain within boundaries that have already shifted considerably.
Jon instead emphasized human communication and the ability to operate effectively in uncertain environments. Organizations still depend on people persuading colleagues, negotiating decisions, building consensus and coordinating complex work. He also argued that professionals will need more entrepreneurial capabilities, not necessarily to establish businesses, but to adapt, recognize opportunities and find ways to deliver results amid changing circumstances.
That perspective aligns with what I observe among successful career changers. The people who navigate transitions most effectively are not always those with the most impressive credentials or the longest tenure. They are often the ones who can translate their experience into a new context, develop relationships outside their immediate professional circle and demonstrate curiosity about unfamiliar opportunities.
There is also a difference between being willing to learn and being willing to reconsider your professional identity. Someone who has spent 25 years becoming an expert in a particular function may understandably resist the suggestion that the way they work needs to change. Yet career resilience increasingly depends on separating the value of one's expertise from the specific methods used to deliver it.
A professional's knowledge of customers, regulation, organizational dynamics or commercial strategy may remain highly valuable even when AI transforms the activities through which that knowledge has traditionally been applied.
The challenge is to recognize that distinction before an employer makes it on your behalf.
The Future Belongs to Professionals Who Can Combine Experience With Adaptability
The most reassuring aspect of my conversation with Jon was not his optimism about AI. It was his insistence that experienced professionals do not need to discard the capabilities they have spent decades developing.
When I asked what people should avoid doing, his immediate answer was: "Don't panic."
That advice deserves consideration, particularly because anxiety can produce two equally unhelpful responses. Some professionals become so overwhelmed by predictions about AI that they disengage altogether. Others respond by trying to learn every new platform, follow every development and accumulate credentials without a clear understanding of how those activities support their careers.
Neither approach is likely to produce a sustainable advantage.
A more constructive strategy begins with an honest assessment of one's current professional value. Which responsibilities depend primarily on producing information, and which depend on interpreting it, making decisions, influencing people or accepting accountability? Where could AI improve the quality or efficiency of the work? Which capabilities would make someone more valuable to an employer over the next five years?
The answers will vary considerably by occupation, industry and career stage. They also need to be revisited regularly because the technology is changing quickly, and the organizational response to it remains uneven.
There is no credible way to guarantee that any particular professional role will remain unchanged over the next decade. Nor is there sufficient evidence to conclude that decades of experience are about to become worthless.
What we can say is that employers are beginning to reconsider how work gets done, and professionals who understand both their business and the technology will be better positioned to participate in those decisions.
For people in the second half of their careers, that is a more useful way to approach AI than trying to identify a supposedly safe occupation. The objective is to remain capable of contributing as the definition of valuable work evolves.
Experience remains an asset. The task now is to make sure it continues to be relevant.
About Our Guest, Jon Whittle
Jon Whittle is Australia’s leading thought leader on AI for business. He hosts the podcast CSIRO Presents Everyday AI and is author of two books on AI: Responsible AI – Best Practices for Creating Trustworthy AI Systems and AI for Business – A Guide to AI Adoption. He regularly advises Boards and C-suite leaders on AI adoption, and he is a former NASA senior engineer and director of Australia’s national facility for R&D in AI, cybersecurity, robotics and quantum technologies.
About the Host, Renata Bernarde
Hello, I’m Renata Bernarde, the Host of The Job Hunting Podcast. I’m also an executive coach, job hunting expert, and career strategist. I teach professionals (corporate, non-profit, and public) the steps and frameworks to help them find great jobs, change, and advance their careers with confidence and less stress.
If you are an ambitious professional who is keen to develop a robust career plan, if you are looking to find your next job or promotion, or if you want to keep a finger on the pulse of the job market so that when you are ready, and an opportunity arises, you can hit the ground running, then this podcast is for you.
In addition to The Job Hunting Podcast, on my website, I have developed a range of courses and services for professionals in career or job transition. And, of course, I also coach private clients
Resources Mentioned in This Episode
Timestamps to Guide Your Listening
- 0:00 Is AI really coming for your job?
- 1:04 The AI veteran who never expected this in his lifetime
- 4:44 More worried than earlier this year?
- 7:02 Why AI companies are asking to be regulated
- 9:54 The “uniquely human” skills AI is already eroding
- 14:52 Leading AI with imposter syndrome
- 18:31 50-something with a strong career? Start here
- 23:40 Why 80% of AI success isn’t technical
- 29:48 What not to do, and why a gap helps
- 33:56 What 60 Minutes missed about AI and hiring
- 40:28 Why 200 applications get you nowhere
- 46:34 Why an AI professor now posts every day
- 50:56 He left a 1,000-person role, with no website
- 54:43 Don’t build the website first
Transcript
Renata Bernarde: Jon thank you so much for joining me on this podcast. It’s not the first time we try to record this, so thank you for your patience for everyone listening. We did record an episode earlier this year, and the sound was terrible, and you never saw it. So I’m so sorry. I had a wonderful conversation with Jon that nobody knows about. But Jon used to host a podcast as well, so hopefully he’s familiar with those tech issues. He hosted the AI podcast for CSIRO. Here in Australia. He’s also published two books on AI, which I’m gonna link below in case you want to read them. He works now for the Melbourne Business School. He advises boards and C-suite leaders on AI adoption. He’s a former NASA senior engineer, and he is the former. Director of Australia’s National Facility for R&D, AI and Cybersecurity, Robotics, etc. That’s the CSIRO’s Data61. Jon, did you think AI was going to be as is now when you started your career looking at artificial intelligence back in the day? Was this what you imagined?
Jon Whittle: I absolutely not. No. I mean I’ve now I keep counting the years because I’ve now been in the AI field for I think thirty-two years. I’ve been around quite
Renata Bernarde: Wow.
Jon Whittle: quite a long time. And I think back then we had the dream of what it could become, you know, as we have it now. You know, you can just kind of talk to a machine almost as though it’s a human being. But having worked back then to try and make that dream become a reality, I think I’d come to the conclusion that it was never gonna happen in my lifetime. So it just shows just shows how wrong you can be, really, and just shows how
Jon Whittle: how fast and quickly things suddenly shifted because it really did happen all at once.
Renata Bernarde: And it’s so interesting because it’s been three decades of you interested in artificial intelligence. And for most people, people like me, we’ve only started using it a few years ago. So we’re babies compared to you. Do you get tired of explaining to people artificial intelligence? Is it getting too repetitive or are you also learning as you go and things are evolving very fast for you as well?
Jon Whittle: No, I’m I would say I’m definitely learning. What could because the nature of the technology has actually changed. So we’re now in the kind of generative AI era, which is I think there’s five eras in the history of AI. I think generative AI is kind of number three. and it actually works quite differently than what I learned thirty years ago. And they’re creating new inventions to make it better every single day. So I’ve I’ve been digging in myself just to make sure I’m on top of things so that when I explain it to people, I’m saying the right thing and I actually understand how it works. ’cause I
Jon Whittle: still think it’s actually really understand it’s really important that, you know, any kind of senior executive at least actually has some level of understanding of how AI actually works, ’cause there’s a lot of hype and misinformation out there. So it’s it’s worth just educating yourself a little bit, I think.
Renata Bernarde: Yes. Well I was educated in artificial intelligence by science fiction, so I don’t think I’m
Jon Whittle: well they maybe not the best source, you know.
Renata Bernarde: in my her phase, you know, but you know, I’m a big fan of “The Expanse” and Asimov reading and all of these amazing science fiction writers, “The Foundation”. I used to read all of those books. I find it all fascinating. So I have a very romantic view of everything, which is probably not a good thing. But I was also earlier this year when we had our conversation very worried about artificial intelligence impacting my work as a career coach and my clients’ work as well. And you were much more positive. You calmed me down. Are you more concerned today than you were when we spoke earlier this year?
Jon Whittle: No, I’m not actually. I think the general population probably is. so again, amazing how much has happened since we last spoke. I
Jon Whittle: think the AI tools have continued to develop in terms of their capabilities at a breakneck speed. but then we’ve had a lot of coverage in the media recently of so-called AI agents going rogue and hacking into government systems and things like that, which is a real concern. the these agents are pretty powerful now. And so the fact that they can find security vulnerabilities that may have been there for a long time, I think it is a concern and it’s something that every board should be thinking about. but then we also hear about you know, you know, X engineers from Anthropic or OpenAI claiming that there’s a 10% chance that AI is going to lead to human extinction by the end of the decade, which I think is nonsense. and there’s all kinds of reasons why they’re saying these things, which you know we may or may not get into. But I think that probably that what I’ve what I’m noticing is the general fear and anxiety levels amongst people have risen significantly. Interestingly enough, n not as much about jobs. I think when we last talked, it was all about AI taking our jobs. But it’s
Jon Whittle: it’s suddenly become even bigger than that. And it’s not just it’s gonna take our jobs, it’s gonna take our entire lives. so yeah, lots of people with fear and anxiety out there, I think. But I’m s I’m still positive. I think a lot of what’s out there in the media is overblown, overhyped. And I think we need critical thinking more than ever, I think, to really question some of these things that are being said and I find it quite ironic because we often talk about AI as taking away our critical thinking, but we really need it now more than ever, I think.
Renata Bernarde: Yes. Well, I think what’s happening that’s quite strange is that the companies that are building powerful AI systems are telling us how extraordinary these systems are, but then also asking governments to help regulate them. So as ordinary people, how should we interpret that? What’s going on?
Jon Whittle: So I don’t think anybody really knows what’s going on, other than the people saying those things. I did write a blog article about this recently though. We maybe we can link that in the show notes because I think that’s I
Renata Bernarde: Let’s do that.
Jon Whittle: think there’s a few possible things that may be going on. and I’m I’m not gonna make a prediction about which one is right. it could be just all a big marketing stunt, you know. Two of the big tech companies, Anthropic and OpenAI, are trying to head towards IPO. So there by saying, you know, these machines we’re creating are so dangerous. you know, and we’re the only ones that can make them safe, therefore you better invest in us just before our IPO. I think that could be part of it. I think regulatory capture could be another aspect of it, which is where they see that regulation is coming and they want to. Define the regulation themselves so that it is advantageous to them. And I think we’ve seen that play out in the US with the with the president’s White House AI Accord, which is essentially all the tech CEOs coming together and deciding to self-regulate. We know that doesn’t work. it could be that these people truly believe that these systems are so dangerous that they could lead to human extinction. I think many of them. probably do genuinely believe that. and the other the other thing that’s going on, I think there’s there’s a strange kind of cult like organization that pervades much of Silicon Valley, which has been widely written about, called effective altruism, which it has been described as a cult and it’s this belief that You know, we really should be thinking about future generations and it’s the very kind of long-termist views. and it’s it’s a bit sinister and kind of weird, to be honest. but it leads
Jon Whittle: to a lot of these, a lot of the people making these extinction claims are somehow linked to this effective altruist movement, including you know, the founders of Anthropic. They got some of their they
Renata Bernarde: Really?
Jon Whittle: got some of their very early investments. From this movement. Sam Bankman-Fried, the crypto criminal, was a big believer in that movement. So there’s there’s there’s a weird kind of ideology kind of pervading much of Silicon Valley as well, which I think again, I’m not saying that’s the only reason, but that could be playing into things as well.
Renata Bernarde: Okay. let’s talk about that but from not from a cult perspective, but
Renata Bernarde: from a parents perspective. Right? You’re a father, I’m I’m a mom.
Renata Bernarde: And I my clients are usually, around our age. And they talk to me about their careers, but then they’re talking about their kids as well, what is your view on what’s going to happen to junior people, people coming into the workforce now, if AI does the work that previously was clerical and admin and what do you think we’re going to be hiring younger people for these days? And are universities preparing for that?
Jon Whittle: Yeah. so a lot to say about that. So I think first thing I would say is that I mean I work with organizations every day who are trying to adopt AI. And I would say that for the most part they are very much struggling to get value out of it. So most organizations spent the last couple of years maybe rolling out some Copilot licenses, doing some corporate training, doing a few proof of concepts. But going from there to kind of enterprise-wide AI adoption at scale with clear ROI is a completely different story. And the reason it’s a completely different story is because at the end of the day, organizations are ecosystems of people. And so much relies on people talking to each other, influencing each other, negotiating decisions. And so forth. And that’s not something that AI can replace. And I don’t think it will be able to replace that anytime soon. in 20 years, who knows? But at least for the next kind of five to ten years. in terms of our kids and kind of what future skills we need, look, I think that’s again a really interesting question because Th there’s a common narrative out there that there are certain human characteristics such as judgment and creativity and empathy that are uniquely human and AI won’t ever be able to take. I’m actually not sure I agree with that. it used to be the case that we, back twenty years ago we always said, AI can never be creative. That’s a uniquely human thing. But now we’ve got AI creating artwork. movies even and so forth. And you can argue about whether that’s creativity or not, but I think there’s certainly some examples out there where you could show some of that AI generated work to people and they wouldn’t
Renata Bernarde: Again.
Jon Whittle: be able to tell that it was AI generated. So there is a case to be made that, you know, human creativity is different than AI creativity, but I think AI can be creative in certain ways. Similarly with empathy, I don’t think that’s uniquely human either. there’s been studies done that say if you compare an AI doctor to a human doctor, the AI doctor is often more empathetic as observed by patients. And the same with judgment, you know, it’s we’re seeing AI make its way into law courts. I don’t think it’ll be too long before we have, at least for kind of low risk decisions, some kind of automated judge in law courts. So we’ve got all these characteristics that we always thought were uniquely human, and they’ve kind of been eroded bit by bit. I often think of it’s like it’s like we’re humanity is the cliff at the end of the ocean and the waves are coming in slowly, but it does happen slowly, right? And then suddenly
Jon Whittle: there’ll be a big storm and the cliff kind of collapses. I think that we’re that’s kind of what’s happening with these human traits. That all sounds very negative. But to be more positive, I think I think for me the two things that will remain are our human to human communication. Because again, organizations are unless we completely rewrite how organizations work, which I don’t see happening anytime soon, they rely so much on people coming together, achieving consensus, convincing of ideas and so forth. And that’s not gonna go away. And I think what would become more important both for our kids but also for us in the short term is kind of hustle culture. I think this has already been already been a trend in employment. You know, we don’t have lifelong jobs anymore. You know, we have many, many different jobs in our career and we have to kind of reinvent ourselves multiple times. I think that’s going to become true even more. so I would be leaning into not necessarily becoming an entrepreneur, but learning some of those entrepreneurial skills so that you can figure in a figure out in a very uncertain environment, very complex environment, how to get things done. So I’d I’d say, yeah, communication and hustle culture.
Renata Bernarde: Interesting. I had dinner with a few friends Saturday night and two of them had just recently changed jobs to do AI implementation. And it’s interesting that, you know, one of them is quite comfortable with that, had done that before. The other one was like I’m not really sure. I think I have imposter syndrome, ‘Cause it is new for people to be implementing AI in organizations. So if these are people that might be very good at transformation in general, but not AI in particular, for example. And we were kind of laughing about this and saying how much AI has tricked us, you know, if we’re looking at things and we don’t know if it’s AI or not, and how come you’re now going to head AI for this organization? Ha. So it’s funny, but it’s not, you know, it’s something that’s new and it’s something I’ve seen with some of my clients as well, feeling that imposter syndrome when they are supposed to be. either leading AI implementation or adopting it and sort of leading a team that needs to implement it or needs to adopt it and not feeling confident. What would you recommend to these corporate professionals?
Jon Whittle: Yeah, good question. So first of all, there’s a lot of new AI jobs out there, which is kind of interesting in itself, right? Because we were told
Jon Whittle: that AI was going to take all our jobs. And yet, there’s actually some really good evidence out there. So there was an Australian government report that came out that said there’s no evidence that AI is leading to mass layoffs, at least not yet. And there was a report from CSIRO that actually said that the companies that are adopting AI the most are actually hiring the most. so there’s some interesting trends. but certainly what I’ve seen is there are lots of new categories of jobs now. chief AI officers or heads of AI have suddenly become very, very common. I think I saw a stat the other day that said that forty-five percent of Australian businesses now have an equivalent role, but then there’s a whole bunch of roles to support that. My favorite is called AI Enablement Officer, which I’ve seen quite a bit. Because I re I think, you I they’re enabling the organization to adopt AI, but it sounds like they’re enabling the AI, right? So it sounds a bit strange to me.
Jon Whittle: but yeah, there’s lot there’s lots of new AI jobs out there. And I think to your point, there simply aren’t enough people who actually really know anything about AI to fill those jobs. And so they are by definition being filled with people that come from a business background or a transformation background or a change management background. And they’re being put in charge of, you know, rolling out this AI across the organization, but we’re really without the no fault of their own without the background. And I think it’s quite a pressured place to be in because a lot of boards and CEOs are very gung-ho about AI. They go off to trips to Silicon Valley and they see all this amazing stuff and they get told that it can just happen just like that. And so they come back and then they tell their AI enablement officer, move faster, move faster. Why can’t we just get this done? But it’s not that easy because you’re dealing with lots and lots of people in an organization and again you have to kind of convince them, negotiate with them. So those jobs I think are there. I think they’re quite tough. And yeah, definitely nothing to be ashamed about in having imposter syndrome ’cause I think lots and lots of people are in that position right now.
Renata Bernarde: So if somebody’s listening to this and driving home, they’re fifty something, they have had a successful corporate career, they’re good at what they do, they’re watching AI develop and they’re starting to wonder whether the expertise that they’ve had will sort of be valued in the next five, ten years of their career. What would you tell that person to start doing today?
Jon Whittle: So I think all of the things that they’ve done are still valuable. but in addition to that, I think it has become a non-negotiable for people to have AI skills right now. so I’ll give you an example of this. I was running a strategy workshop for an organization yesterday, and it was very clear coming from the CEO that He was quite frustrated that his immediate leadership team was not using AI enough. And in his mind, you know, there are all these kind of productivity benefits to be gained. And, you know, he’s he was tracking, you know, he’s got stats on they’ve got an internal tool and he was tracking how many people are using it, when they’re using it, and finger pointing at the ones that ones that weren’t. So I think it’s become a non-negotiable because that CEO is not the only one like that. I think every everyone is like that. So I would say you do need to build up those AI skills. Now I reckon pretty much everybody I know now uses AI, generative AI. I still occasionally find one or two people that have never used it. But they’re rare. They’re a rare breed now. But I would say that most people are not using the full capability of it. You know, they may be using twenty percent. they are using it to summarize documents or do some kind of basic analysis or something like that. But there’s so much more that you can do with the tools. you know, if you’ve not played with things like Claude Cowork or Claude Code or even letting Claude take control of your Browser, and I only mention Claude because that’s the tool that I tend to use the most. The other AI tools can do this as well. so try out the more advanced features, I would say, and try and position yourself to be the person who, yes, you’ve got domain expertise, yes, you’re an executive, but you also are a couple of steps ahead of everybody else in terms of how you use AI. where you use AI and how to use it responsibly as well.
Renata Bernarde: Mm-hmm. When the CEO was mentioning, he finds people are not using enough, is it Copilot? Is it when they’re adopting it internally in a workspace, they can only track what they’re allowing their employees to implement. Do you find that there is a lot of policies around what’s what type of AI you can use in the corporate environment?
Jon Whittle: There is. So I see a couple of different things going on in organizations. So many of them are just rolling out Copilot.
Jon Whittle: and the problem with Copilot is that there’s lots of features there that may be enabled or disabled by the organization. And a lot of them may be disabled for good reason for security or privacy purposes,
Jon Whittle: for example. And so you then get into an interesting situation where people might be using more capable tools at home. in their personal life and they’re doing all this amazing stuff and then they want to go to work and do that amazing stuff at work as well and they can’t because the tools that they’re using are locked down. So that’s one way organizations do doing it. There’s quite a few organizations out there though as well that have actually built on top of the generative AI tools to have a kind of an enterprise version for themselves and they may have spent even a couple of years building this things up. And it has pretty secure access to the organization’s data and so forth. So you can actually do a lot with those, but might be a bit more of a learning curve there because they tend to be a bit more kind of bespoke. So and then you’ll you’ll also see organizations out there who are even leaning into the open source aspect of AI, and rather than going to a big vendor, they’ll actually take one of the open source models, they’ll install it themselves. have their own kind of computing infrastructure to do that. Pros and cons of that, I think. but yeah, it’s kind of it’s it’s it’s all over the mark, I think.
Renata Bernarde: Yeah. Well you explained is exactly what I hear from my clients that they want to use at work but they just don’t like Copilot. So they end up working from home on the side using Claude or ChatGPT and then it doesn’t show that they’re actually using it because they just haven’t really adjusted to Copilot. And it’s interesting, isn’t it? Because I remember back in 2017 going to a Salesforce event in San Francisco and hearing so much about their investment in AI and now we see Salesforce not doing so well compared
Renata Bernarde: to some of their competitors and other businesses. What is it that makes a s a company do well in NI AI versus Is it the adoption? I don’t know, because Salesforce was well adopted up until now, and then all of a sudden is you know there’s a real push against using it and other competitors taking over. What makes a company’s investment in AI succeed compared to others?
Jon Whittle: Yeah, fun funny you should ask that question, because I’ve spent a lot of time looking at exactly this.
Jon Whittle: and there’s there’s actually quite a lot of good research out there now that has looked at AI adoption at scale within organizations and has looked at what works and what doesn’t. one of my absolute favorite pieces of research on this comes out of Stanford Digital Economy Lab. It’s called the Enterprise AI Playbook, and they went into 51 companies that had adopted AI and really kind of unpicked what they did that made it successful. I’ve taken that research plus lots of other research plus my own experience out there, and I’ve I’ve come up with what I call 14 dimensions of AI adoption, which is 14 things that you need to do to get to make AI work at scale within your organization. And most of them are nothing to do with the technology. So eighty percent of them are non technical, I would say. Yeah.
Renata Bernarde: really? Okay. I’m super curious now. Give me an example.
Jon Whittle: Yeah, so they fall into three categories. So leadership and vision, people and culture and governance and trust. So from a leadership and vision point of view, the from the top down, the organization has to have a has a very clear understanding of why it wants to apply AI, what it’s trying to achieve, you know, a strategy, which a lot of organizations don’t have because they we were told that you just make the tools available to people and people will experiment and then great things will happen. They’re now realizing that’s not quite. case. So there’s much more of a call now to say, you know, what are the real business problems we’re trying to solve? And we’re AI that helpers and being very, very clear on that. And so having a strong vision. Then there’s people and culture, which is frankly good old-fashioned stuff about any transformation, you know, good change management, good communications. There are a few kind of AI specific factors like, you know, do you need human oversight of everything that AI does. We’re kind of told that you do because AI could hallucinate, right? So you have to have a human in the loop. But actually the research shows that if you put a human in the loop all the time, you won’t get any savings because you’ve just moved someone’s job from creating things to checking the work of an AI. And that actually you need to set things up with an escalation model so that 80% of the time you just kind of let the AI get on with the job. And if it’s low risk and you save your human oversight for the high risk cases. also in that category there’s things like are you planning for what to do with any time savings that you might get from AI? So, you know, people will say they might say, for example, well, I’m saving two hours a week from using AI, but does that mean that they’re going to the beach on a Friday afternoon ’cause they’ve saved two hours? No. It means that they’re probably spending more time in pointless meetings or producing documents that nobody’s going to read, right? So the organizations that are successful are the ones that actively plan to say, well, our workforce is going to change this time this save this so much time, and this is what we’re going to do with that time. And then the third category is governance and trust, which is where all the stuff about security and privacy and so forth comes in, becomes super important. For those organizations who are trying to implement AI agents, because they are very non-deterministic. They, you know, you’ve got to get the guardrails right, even at an organizational level. And that requires a lot of effort, a lot of experimentation, and a lot of constant monitoring. So,
Jon Whittle: yeah, those are the three things leadership and vision, people and culture and governance and trust.
Renata Bernarde: One of the things that I notice that is aligned with what you’ve just said is some of my clients who are chief people officers starting to l n not only some of them networking really heavily with their counterparts in IT, which is very uncommon as you
Renata Bernarde: probably remember. But I have one that now is managing the tech team.
Jon Whittle: Yeah, and that is a new trend. so I think
Renata Bernarde: Yes. It’s fascinating.
Jon Whittle: I think there is a case to be made that you should put your chief people officer in charge of an AI transformation because most
Jon Whittle: of it is about people and there are precedents to this. So Atlassian, big Australian tech company has done this. I think their chief people officer is has now a title of chief people officer and an AI enablement officer.
Renata Bernarde: yeah.
Jon Whittle: Most don’t do it. I still would say ninety percent of the organizations I work with put the CTO or the CIO in charge. but y yeah, at the at the very least, as you say, you need the chief people officer working very, very closely with the CIO. but I think there’s a case to be made that if it’s the right CPO, that the CPO could actually lead the whole thing.
Renata Bernarde: Yeah, that’s fascinating. we discussed what people should do, you know, today and start now. What would you tell them not to do?
Jon Whittle: Don’t panic.
Renata Bernarde: Don’t be like Renata early in the year. Don’t panic. Okay.
Jon Whittle: Yeah, look I get I don’t don’t panic. I mean take everything you read with a with a little bit of a pinch of salt. you know, and I because I think fear can lead to inaction. You know, we become the kind of the bunny rabbit in the headlights, just not knowing which way to go. And that’s not gonna help you at all. So I think try and Take a kind of growth mindset, be optimistic about this stuff, and recognize that all the skills that you built up in an executive career are just as valuable as they ever were. It’s just that you need to add a new layer on top of that, which is to kind of build up your AI skills as well. And I’ve seen people, I’ve had friends and colleagues who’ve done this really successfully. Maybe they’ve been laid off and they’ve had time. searching for new roles and they’ve used that time well to upskill themselves in AI. It doesn’t mean they’ll necessarily go to an AI role. they might go to the same kind of role they had before, but they’ll be five steps ahead of everybody else in that organization because you actually do need time to learn that stuff. It’s not quick. And most people who are working don’t have that time, right? They don’t have they d they don’t have the time
Renata Bernarde: I agree. Yeah.
Jon Whittle: to take, you know half a day every other day to learn this stuff. So you’re in actually in many ways a luxurious position if you’re between roles, ’cause you do have that time and if you use it wisely, you could enter your new role really well ahead of your of your colleagues.
Renata Bernarde: Yes, yes. I have some great examples of that with my clients. and it’s an upskill that’s totally worth the investment during a transition if you can afford it. And frankly, i when I say you can afford it, some of them you don’t need to pay. You know, you can just find free programs online to do. I have a client in Europe who spent a few months doing a executive AI program overseas that yeah I think was really important for him for his transition. And one here in Australia that spent six months doing everything he could find that was free. Because he couldn’t afford to pay anything and ended up with two job offers and that
Renata Bernarde: are that were related to his AI training. So I thought that was really
Jon Whittle: Yeah, and I
Renata Bernarde: Incredible.
Jon Whittle: look I prob I probably shouldn’t say this because I’m at Melbourne Business School and we have AI courses for execs, which are wonderful. I teach some of them. But
Jon Whittle: you know, you don’t need a course to learn the stuff. That’s the beauty of AI. I think you can learn it through
Renata Bernarde: But some people like the structure, some people like the n and the collegiality. Yeah, yeah.
Jon Whittle: Sure. Yeah. So I would I would never say don’t do it, but you can actually get a you can get a long way through just experimenting. and, you know, w the way that I because I’m still experimenting as well. And so the way I try to do it is if I’ve got a task and I’m about to kind of delve into it, I’ll just stop myself and say, I wonder if AI could do that and then give it a go and sometimes it works and sometimes it doesn’t, but you learn a lot.
Jon Whittle: And you probably if you are gonna take a formal course you would I’d still say do some experimentation for yourself first because you’ll then go in much better prepared. You won’t go in as a blank sheet of paper into that course. You’ll have you’ll have some lived experience of trying to use it, which most people have nowadays anyway. but
Jon Whittle: yeah, you can get a long way without spending any money, I think.
Renata Bernarde: And we can learn from each other because we’re all experimenting individually, it cocooned in our offices. So the good thing about being a career coach helping so many people is I learned so much about how my clients are using AI in different ways. And I was like, I hadn’t thought of that. Let me try that. So having
Jon Whittle: Yeah. Yeah. That’s right.
Renata Bernarde: conversations as well is so good. Let’s go back to job searching and AI. Did you end up watching the 60 Minutes on Sunday night? You did?
Jon Whittle: I did. Yes, did. I did.
Renata Bernarde: Okay. I’d love to talk to you about it then. Because I felt like they tried really hard to dramatize the situation, but I wasn’t really convinced it was that dramatic. Was it the same to you, or is it because it’s normalized for me because that I deal with that every day?
Jon Whittle: Look, it definitely was the same to me. And look, I have been on some of these programs. I’ve been interviewed for some of these programs. So I know how they work. they go in with a very particular narrative that they want to push. And they will I’ve I’ve had with some journos some pretty aggressive questioning to try and get me to say something that will align with that narrative. And you know, there’s all the people that were interviewed there, there will have been pretty heavy editing of what they
Jon Whittle: said and they will have cherry picked the things that fit that narrative. look I think there were some real stories in there, right, which are kind of really sad, you know, people applying for hundreds of jobs and not getting any calls back. So there’s there’s, as you will know better than anybody, there are definitely those kind of stories out there. it wasn’t clear to me, I don’t think they made the case that it was the AI necessarily that was rejecting them. That the evidence there was a bit thin. that’s not to say that there can’t be AI systems that do have bias, because we’ve known that’s been a problem throughout the history of AI. But there’s also cases where AI can be less biased than humans. In fact, Barb Hyman, who was Barb Hyman, who was interviewed on that show, who’s the CEO of Sapia I do know not well, but
Renata Bernarde: She’s great, by the way. Do you know her personally? Yeah.
Jon Whittle: we’ve been on an awards panel together.
Jon Whittle: so she set up Sapia.ai quite some time ago.
Jon Whittle: And in fact, they one of the results the early results that they had was that their AI hiring tools were actually less biased towards women than you would typically find with human recruiters. so I think I think my takeaway from the whole thing was that as ever with AI, you can do it well or you can do it badly. and
Jon Whittle: if you do it badly you’ll create problems. and if you do it well you might solve some problems.
Renata Bernarde: Yes. So for those of you listening and you don’t know what we’re talking about, 60 Minutes Australia did a an investigation on AI and recruitment and potential gender bias and other biases of applicant tracking systems for recruitment. and they had if you’re overseas, they had a case study in Australia, one in England and one in the US. So it was very international. I think they do that on purpose so that they can repackage it for other markets. It’s available on YouTube. I will put the link below if you want to watch it. One thing that happened that I thought was really interesting was the American job candidate. I forgot his name, but he was saying I’ve I keep applying for jobs in finance. He’s in an executive in finance and I get rejected really, really quickly. I’ve noticed that the applicant tracking system ha is very common in its workday. Workday is a very common applicant tracking system. So I think I’ve been red flagged by Workday and they red flagged me. And I said, Well, that can’t be because workday is a software that you acquire as a as a corporation and then you implement it in your HR department and the HR department designs it, they’re not gonna be sharing names between companies, right? So that’s what I thought. I th and that’s I think what was implied in the 60 Minutes investigation that
Renata Bernarde: he had been blackmarked by workday. And I said, Well, that can’t be. And I am dictating this, so I’m I’m talking to my ChatGPT and saying, look, this can’t be right. You know, it’s not c this lawsuit is going to go nowhere. And ChatGPT said, No, no, you I think there is a case here and I’m like, okay, ChatGPT tell me what you what you think is the put the potential legal case. The potential legal case could be the workday coding and design of the system. potentially being biased, maybe workday needs to readjust its software so that the bias doesn’t continuously happen, you know? And I’m like, I hadn’t thought
Jon Whittle: Yeah, it’s yeah.
Renata Bernarde: of that.
Jon Whittle: Yeah. I mean and this is this has always been a problem with AI because at the end of the day, AI is statistics. And it’s
Jon Whittle: only as good as the tr the data that it’s trained on. So you can go back right to I forget when it was, but a couple of decades ago, there was a system called COMPAS in the US that was used by parole boards to help make decisions about whether a criminal would re offend or not. And they would grant parole or not based on that. and it was used in
Renata Bernarde: Kind of a “Minority Report” situation. Remember that movie we talked?
Jon Whittle: well not yeah, I do rem that was more I think kind of th well I guess that was also prediction. Yeah. This was in a very
Renata Bernarde: Remember, Renata learns AI through science fiction in movies, Jon.
Jon Whittle: There you go. There you go. But it’s that system was used for a number of years and then until somebody did a kind of retro retrospective study on it, and they found that the system was twice as likely to flag black defendants as reoffenders as whites. And so that was one of the very early examples of these systems having bias in them. Now, there has been a huge amount of work since to make sure you get the a good curated data set that’s represented Of the sample population. And so these issues don’t occur anywhere near as much as they used to. But that’s not to say they can’t happen. And
Jon Whittle: there’s certainly lots of examples out there of where bias has happened. But the other thing that struck me about that 60 Minutes episode, and I’d be interested in your take on this because. All these people that they were interviewing would say things like, well, I sent out a hundred applications or two hundred applications and I didn’t hear anything back. I’m still looking for a job. And I was just thinking, you know, in what world do you think you’re going to get a job just by throwing a whole bunch of applications out there? you need to
Renata Bernarde: No. Yeah.
Jon Whittle: you need to activate your network and talk to people and you know, you know, you use your human communication skills to stand out from the crowd, not just throwing a CV. in the deluge of all the other CVs that are out there.
Renata Bernarde: Well, the situation hasn’t changed before AI and after AI. It’s the same. Before AI, people used to send hundreds of applications and hear nothing back as well. Yes, the scale of job applications has increased. I think what has happened is because you have Claude and ChatGPT helping you write applications, you feel like you can do more. There
Renata Bernarde: is this sense that you keep yourself busy by just the volume of the number of applications. And there is no barrier of entry for job applications. Anybody can send a job application. What has happened is more people are sending more job applications now because they can use their time more productively on the weekend by asking ChatGPT to spit out different types of resumes and send them out to different jobs. It you won’t get a job from that. You won’t get a job from that.
Jon Whittle: No, correct. And I can remember I can remember back in two thousand five and I was going for my first academic job and I sent out not hundreds, but I sent out about forty five applications to various kind of universities all over the world, thinking, you know, I’ve got a PhD, you know, I’ve got all this experience, you know, it’ll I’ll I’ll have I’ll have them biting off my arm and I’ll have my choice of which university to go to, right? I got zero response from any of them and I was thoroughly depressed. but I kind of picked myself up and I said I have to change my approach here. And so I started reaching out to my network and somebody knew somebody at a university in Virginia in the US that they were looking for somebody that matched my profile and I ended up going to work there. So I think you’re right. In many in i in many ways, the game hasn’t changed.
Renata Bernarde: No, no.
Jon Whittle: It was always the case that if you just took a Scattergun approach, then you’re not gonna be successful.
Renata Bernarde: But even if you come to me, and I’ve discussed this before on the podcast, Jon, even if you come to me and you say, Renata, I don’t have a network. Don’t kill me now. Don’t kill me now. I don’t have it yet. I cannot I cannot use my network, okay? Then you have to become absolutely excellent at job applications. And becoming absolutely excellent at job applications is a game. You can gamify it. You
Renata Bernarde: don’t need ChatGPT or Claude to do it. You can get a highlighter and highlight the job description, the keywords and all the important things that are there. And then you need to make sure it’s in your cover letter and in your resume. And if it’s not there, you’re not gonna get the job. That’s what we have bottified. That’s what you know the ATS system has. facilitated for recruiters. Recruiters don’t need to use their human eye to search if somebody has an MBA, if they have at least five years of experience in this area, if they have been a finance manager before or project manager before. So you need to include the keywords there for it to be picked up on the other side of the funnel. And before AI, that’s how I used to teach people. In fact, if people buy the Reset Your Career Framework, which is a short course that I have, it’s still there. Because I think it’s important for you to learn to do it manually so you can understand how the applicant tracking system is designed and developed and works anyway. And
Renata Bernarde: I think that this is important knowledge for people applying that yes, you can use your network, you should use your network. and it was really interesting because the first example was a recruiter who couldn’t get a job. And there’s an irony in that. In fact, we have an episode with a recruiter from the UK who lost her job and then was horrified at how she was treated as a candidate and ghosted and never heard back, didn’t get any feedback. It really changed her philosophy of how she was going to work as well and make
Renata Bernarde: sure she humanized her next job and she’s still very active on TikTok, providing excellent advice on her TikTok account. So there was that case and that one requires you to h use your network, yes, but also be very good at applying for jobs in that sort of gamified way. The second candidate was somebody who was in fashion and luxury brands. You cannot apply for jobs without a network.
Jon Whittle: Mm. Yeah, yeah.
Renata Bernarde: I’ve worked with people in that area. I mean, you as an academic, if you don’t have a network, you can’t get a job.
Jon Whittle: Yeah, absolutely not. Yeah.
Renata Bernarde: No. So what did she do? I thought it was brilliant. She basically created some it was brilliant but very hard to do for a lot of people, which is take control of your brand and create your own content. If you
Renata Bernarde: don’t have a network that you can rely on, then you need to start now. And she started using social media. I don’t know what it was, if it was Instagram or TikTok. It wasn’t LinkedIn because for fashion industry, LinkedIn is not really that relevant. But she started creating content and was found by somebody and then got a job. So that exposure is something that people feel really reluctant to do.
Renata Bernarde: You were very active on LinkedIn and you now have a Substack
Jon Whittle: I do.
Renata Bernarde: How do you feel about that? And how do you feel about other people doing it and creating content?
Jon Whittle: Look, I think look I started it some years ago. I was fortunate enough to be given a bit some training in how to build a brand on social media. And I think before that training I had all the misconceptions that a lot of people had, which is I don’t I don’t have time to post on social media, it’s it’s too hard, blah, blah, blah, blah, blah. But that training, very simple training, but it just it just taught me that, it doesn’t have to take a lot of time in your week. so I started there and then I think I’ve kind of leaned into it particularly in the last 12 months actually because since I left my position at CSIRO, my kind of corporate role if you like, now I’m professor again but also got my own consultancy, it’s it’s more important than ever. and one of the things I’ve mainly learned there is that we can we can worry a lot about having the perfect post and not offending anybody. you kind of have to get over that, I think, and just, you know, you we’re we’re all human beings, we’ve all got brains, we’ve all got interesting things to say. And if it’s not interesting, the you’ll you’ll you will soon find out. So now I probably post during the week pretty much every day, which if you told me five years ago I would do that, I’d be like, no way, do I have time for that? I’ve also started running my own Substack blog now, which is that’s a different thing because it’s much longer, right? And I would say my approach to that is very different. So on LinkedIn, I think I am actively trying to grow. following. and I do watch a little bit, you know, which posts succeed and which don’t, but I don’t let that kind of influence me too much. But on my Substack blog, I’m not I’m not really actively trying to grow a following. It was more something I wanted to do for me because I found that I had all this stuff in my head and it was like noise in my head and I just needed to get it out of my head. And I found that writing it down was in a good way to do that. And then, you know, it’s an easy next step just to kind of post that on Substack. Substack. So that’s been quite interesting because I’m still kind of learning how Substack works. I’m not monetizing anything right now. although people do. and it’s pe people kinda find you somehow. I mean it’s I’ve got I’ve only got like seven hundred subscribers now, so it’s it’s not like massive. But it’s interesting that it kinda goes through phases where it really Does I really don’t get any new subscribers for a while and then suddenly it’ll kind of jump for reasons I can’t explain. but again, I’m kind of do I’m I’m doing it for me and I’m I’m enjoying the writing. I do use AI to help me sometimes as well, which has become quite a controversial thing. but yeah, I thoroughly recommend people trying to kind of get over there. Again, probably a bit of imposter syndrome. You know, I don’t have anything interesting to say, but I think we’ve all got interesting things to say.
Renata Bernarde: I agree. I’m a big fan of long form writing to establish reputation and I
Renata Bernarde: you know, really recommend my clients who are establishing themselves as experts in their fields or if they’re learning something and they want to share with others that learning process and being really relatable, I find that posting and writing can be so helpful. so I usually Jon, I usually show your posts to my clients when I think, I
Jon Whittle: well thank you.
Renata Bernarde: can’t do it. I’m not I’m too busy. I’m like, okay, let me show you a couple of people who did it. regularly and do it really well. And your LinkedIn profile is one that I often ask them to review. So I am going to link your LinkedIn profile in the show notes and your Substack. Let’s see if we can get you to bump your subscribers on Substack after this episode. I would love I would love to help you out with that. And tell me what sort of consultancy you’re doing. Wha how are you helping organizations these days?
Jon Whittle: Yeah, so part I mean, it’s an interesting story because I left an executive job at CSIRO last November and it was a conscious decision to leave and it had been something I’d been thinking about for a while. So I had you know, I was I was running a large R&D team there, about a thousand people across the whole of Australia. Really loved the work, really interesting. very much the kind of thing I’ve been doing my whole career. But I found that I was getting invited to go and talk to boards and to C suites to just help them understand this whole AI thing and how to how to apply it properly. And after doing that for a couple of years, it really got me to thinking and it was like, you know, maybe I want to make a bit of a change. And the change I want to make is to help organizations adopt AI because I think still if you look at boards globally, but certainly in Australia, the level of AI literacy is still very, very low. So I found that I enjoyed that kind of work going into boards, running briefings and workshops and that kind of stuff, but I also felt that there was a real need for it. Then I then I had a challenge for myself, which is okay, well how do I do this? You know, do I start my own company and go full time on that? I felt like that was a bit risky, frankly, you know, I’ve my kids are still in primary school. still got a mortgage, et cetera. There’s there’s realities, right? So I ended up and I worked with a career coach, as you know, for about
Jon Whittle: nine months to get to where I got to. But it was kind of a light bulb moment, I would say, when I suddenly thought, huh, what about business schools? Now I’m a computer scientist, my I’m I’m a technical person by background, so business school is not an environment that would normally welcome somebody like me. But it turned out to be a good time for them to do that because business schools are having to reinvent themselves. They’re having to think about how do we teach AI to our MBA students, to our executives, because it’s changing every facet of business. And so it worked out perfectly in the end because I’m focusing on doing AI executive education now at Melbourne Business School. I love doing that, but it’s all I’ve also got the flexibility because it’s a university to have my own Company on the side. So it’s called Goldilocks AI because it’s about getting AI just right, not too much, not too little. and I and
Renata Bernarde: love it.
Jon Whittle: I look, I’ve been again, I’ve been it’s back to networking because I don’t even have a website for the company right now. I keep meaning to produce one. In fact, I remember going into the bank and trying to open a business bank account and they and they said, What’s your website? And I said, I don’t have one, and they looked at me funny as to say, but How do you get clients? You know, I think they thought I was trying to money launder money or something. It was something a bit dodgy.
Jon Whittle: but because I’ve got a network, I don’t need the website, at least not now. I’ve got people coming to me. and I’m not trying to do volume. I’m trying to do small, kind of high touch work with boards and executive teams and I’ll I’ll do I’ll go in and do some AI strategy work or s help them come up with an AI governance framework or just kind of general education and literacy around AI. So
Jon Whittle: it’ll be it’s it’s it’s be interesting to see whether I want to grow that over time. It’s just it’s just me and I don’t really want staff right now. But you know, ask me again in a couple of years no doubt things will change, you know.
Renata Bernarde: I love that. I’m going to send this part of the episode to all of my clients who want to open a business and the first thing that they want to do is set up their website. And I said, No, no, no, don’t set up your website. Just go and talk to people
Renata Bernarde: first. I’m really against it. You know, I think my own experience was that I put too much effort into ever I’ve always done this. It’s not my first rodeo. I did such a beautiful Thing with my first business in Brazil that I got award awards for design and it was so
Renata Bernarde: beautifully put together. But that doesn’t bring you business, you know, a website and a nice
Jon Whittle: Yeah. No.
Renata Bernarde: logo. What brings you business is your how relatable you are, how connected you are, and you’re doing it the right way. One thing that I always recommend people to do if they are listening to this, and I’ve just redone mine is think about the framework of how you’re going to implement whatever it is that you’re consulting. Right. So designing it visually for you and maybe investing in a graphic designer making it look pretty is just the best thing. I’m I it’s the best investment I have ever done was hire somebody to help me with my YouTube videos. You go watch
Jon Whittle: Well but
Renata Bernarde: my YouTube videos now. They’re awesome.
Jon Whittle: Although you’d be amazed what you can do with AI now. I mean I
Jon Whittle: I because I do have a website that I’ve never published.
Renata Bernarde: Uh-huh.
Jon Whittle: So I created it with AI. but AI
Renata Bernarde: I see.
Jon Whittle: created a logo for me and it’s really
Jon Whittle: I do use that. That’s really nice. It created kind of the color palette and everything.
Renata Bernarde: awesome.
Jon Whittle: I’ve I’ve used AI for video editing as well.
Jon Whittle: It’s it’s it’s actually amazing what it can do with. video editing. You
Jon Whittle: can you can take a twenty minute long video and just say, I want a two minute social media promo, put some background music, find the most
Jon Whittle: interesting parts, put some titles and it does a really amazing job. So I’m
Renata Bernarde: This platform here that we’re using, Riverside, is wonderful. It
Renata Bernarde: it does all the editing for me and then I just review it. It does all of the snippets, the short videos, the captions, gives me idea for titles, for the ki captions for the post. It’s perfect. It’s amazing.
Jon Whittle: The only thing you have to be careful of, I find now, is because my website I created with AI about a year ago, never published it. And at the time people weren’t really using AI for websites. but now everybody is. And they all look the same. because if you use Claude, for example, which a lot of people use, it has a tendency to use the same kind of fonts, the same kind of color palette. and so I see other websites. out there now and like, yep, that was created by Claude. I know exactly. I
Renata Bernarde: Got it.
Jon Whittle: know exact and it can be a turn off and because there’s quite a back it’s quite a backlash
Jon Whittle: developing against AI content, AI slop. So
Jon Whittle: I’m now in two minds about what to do with that website that’s sitting there because it’s do I say, Well actually I’ve got a website, so let’s publish it, or do I say, you know what, I want to spend a bit of time putting my heart and soul into it and doing it properly. because yeah
Renata Bernarde: Yes. It’s interesting you say that because we saw that with writing as well and commenting on LinkedIn and newsletters that we get, especially corporate newsletters, all of a sudden they all had a very similar narrative and they felt similar and I’m like, okay, this is AI, written by AI. But now we’ve
Jon Whittle: Yeah. Yeah.
Renata Bernarde: learnt it and we’re not doing it anymore. Most of us are not doing
Renata Bernarde: it anymore. So it’s interesting that we’re learning, we go through a steep learning curve and we
Renata Bernarde: on the other side of it we kind of figure out how to overcome these sort of issues with using AI. That’s interesting. Jon, thank you so much for coming on the show. show again. I think I might need to get you every year because things will start moving really fast. Every week a little
Jon Whittle: Every week.
Renata Bernarde: a little part of the episode will be with Jon.
Jon Whittle: Little AI update, you know.
Renata Bernarde: No, definitely we’ll be referring people to your Substack and making sure that they’re following you on LinkedIn. And of course, if they want to hire you, we’ll make sure that my clients who are getting those AI jobs and feeling a bit of imposter syndrome, making sure that they reach out to you for support as well. Okay.
Jon Whittle: Absolutely. Thank you for having me.
Renata Bernarde: Thank you, Jon.
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