Upskilling for an Automated Future 

SD: Welcome to the Enabling Automation podcast series, Season 4: AI and Automation Shaping the Future Responsibly. The podcast where we bring together experts from across the ATS group of companies to explore how automation is transforming our business. My name is Sarita Dankner. I’m the Associate General Counsel and Corporate Secretary at ATS Corporation, a global leader in automation solutions. I’ve spent over 20 years in legal and compliance roles across public and purpose driven organizations, leading legal strategy, commercial governance and risk programs, with a focus on enabling responsible growth that aligns opportunity, innovation and technology with governance and ethics. Today’s podcast is titled: Upskilling for an Automated Future – Preparing People, Not Replacing Them. And it’s a conversation that hits close to home for a lot of people. Leaders, employees, new grads, and even parents too. We’re talking about the future of the workforce in the age of AI. What does that actually look like on the ground, and how do we prepare people for an automated future, both from an employer and an employee perspective. My guests today are Simon Roberts, President of Packaging and Food Technology at ATS, and Kamila Schmitt, Vice President of Human Resources for Packaging and Food Technology. Simon and Kamila, thank you so much for joining us.

KS: Thanks for having us.

SR: Thank you very much.

SD: I want to start with a big picture question. We’ve all seen the headlines about AI is coming for our jobs. What I’m reading paints a more nuanced picture. AI is changing how work gets done, often by taking over the more repetitive entry level tasks, not necessarily eliminating the need for people, but reshaping career paths. One article described it as, quote, the bottom rung of the career ladder breaking, entry level work in areas like tech, law and customer service is being automated. Things like basic coding and debugging, document review and front line chat bot interactions, and at the same time, recent data from the Federal Reserve Bank of New York shows that unemployment for recent college graduates has been roughly 30% higher since late 2022 than for workers overall, which is closer to 18%. So you’ve got this perfect storm, the softening macro environment, trade and tariff uncertainty, and AI reshaping early career work all at once. So, Simon, maybe I’ll start with you and then, of course, open it up to Kamila as well. What are your thoughts on that idea of the bottom rung breaking? Where is AI already removing work or reshaping work for your teams?

SR: Yeah, I think, you know, AI presents an opportunity from a career perspective to be almost like a companion technology. It gives the opportunity, I think, as you mentioned earlier, to take away some of the mundane tasks to take away some of the repetitive efforts within some of our current processes and really position individuals, you know, to move along the value chain to where they can impact value, where they can impact outcomes for the customers. So, you know, I see it very much as it’s definitely complementary, it’s a companion as I refer to that is ultimately going to be an accelerator, right? It gives us the opportunity for individuals in terms of how they share knowledge, how we collaborate in organizations. Right? And it could be argued for some it kind of levels the playing field, right. It gives them access to information, have access to, you know, working with others and different parts of a process or different parts of an organization that maybe normally they would have been constrained or limited from doing so. So for me, I think if you look at that from a career, like you said, a career ladder, I think it can be complementary. It’s a companion technology and it’s an opportunity to really accelerate how you know, individuals think of their career. I think what it also means is it’s not necessarily going to be a straight line anymore. It’s going to be an opportunity to learn and a more broader scope to engage in more far reaching topics that maybe, you know, individuals would have been limited to do so before because of being maybe confined to some of the activities that are clearly important in the way we look at the process today. But they can be replaced with a level of automation and, you know, kind of AI capability that really, removes some of that task, but at the same time improves the outcome for all of the stakeholders.

SD: Thanks, Simon. What do you think, Kamila? Are there specific tasks that you’re seeing disappear or be transformed? What are your thoughts on this?

KS: Yeah, I think the task piece is key. To me, with AI, it’s generally addressing the task and not the job itself. So I think oftentimes we’ll see the job itself change, but not the entirety of it. So as Simon had said about, you know, the different enablement that we’ll see within AI as a bit of a copilot or, a partner, I think is the way to look at it. The comment about kind of that first rung of the ladder being broken, I think that would maybe depend on how you look at it. I do think that maybe positions that are quite repetitive and don’t maybe require as much human emotion and activity and sort of creativity, I think is probably where we might see the most change. But I think there are a lot of entry level positions that certainly require that level of capability. And to me, especially for the audience, as I understand it, for this podcast, you know, a lot of the newer in their career, individuals in automation. I think if anything, this is an opportunity as opposed to a deal breaker.

SD: So I think the data is actually supporting exactly what you both are saying in order to balance the concern that people are raising around job loss with some of the data that I think gives a more hopeful picture than that, and again, is supported by what you’ve just said. So I want to build on that. I read that the World Economic Forum’s Future of Jobs analysis suggested that while some jobs will be displaced by automation, we’re also going to see a significant number of new roles emerge. One projection pointed out around 170 million roles created and about 92 million displaced globally by 2030. So that’s a net increase equivalent to about 78 million, or roughly 7% of today’s jobs. And the trend that it’s talking about is exactly, again, what you’ve said, clerical, repetitive, administrative jobs will shrink and roles in robotics, automation, engineering, data and analytics will grow. So, Kamila, are you already seeing that shift in your world, that decline in more routine roles and growth  in the more technical or analytical ones?

KS: Yeah, I think, similar to what I said earlier about sort of that task based taking a look at the tasks as opposed to the job holistically, perhaps, I think will ultimately lead to the removal, maybe of some of those jobs. I think that what’s important is going to be being dynamic in the work that we do. So as those tasks are removed and as a result, perhaps new opportunities arise for individuals in those roles to learn new skills and to move on and do something different. So I think Simon said it earlier that, that career ladder may no longer look the same anymore. It might not be up and down now, might be more of a horizontal shift if you will, into different, opportunities. So certainly we are seeing, I think, a reduction of some of the more processes that are easier to automate. But what I’m not seeing and in fact, if anything there’s going to be an increase for, is then having the ability as people to be the ones that are doing the thinking and the creativity and really helping to drive our strategy moving forward and allowing that space to do so because the repetitive tasks are removed.

SD: That’s interesting. I read that some people might frame it that we’re shifting from a knowledge economy to more of a relationship economy, which I think is what Kamila, you might be referring to, where the differentiators are the skills that make us human. And this author framed it as the five C’s: Curiosity, Compassion, Creativity, Courage and Communication. Does that align with what you’re thinking? What are the skills that are going to matter most in an automated future? Are they these human centric ones? Which do you think will matter the most?

Absolutely, I would agree. I think our ability to connect meaningfully with others is going to be kind of that differentiator. And I also think that we can use AI as a tool to help us get started. But I think where we’re going to thrive is that ability to scrutinize what AI presents to us and what comes out of that. And I think that will be really important. So from a relationship standpoint, AI is not going to be able to replicate, you know, our imagination and our ability to empathize and our judgment. So I absolutely think that that is very important. And if anything, that’s probably where maybe some of the newer generation coming into the workforce will actually need some training is around some of those softer skills only because they’re growing up in a technology first world right now.

SD: Yeah. So that’s where I was going to go next is how do we actually help to develop those skills inside of an organization?

SR: I think, you know, as you think of new entrants come into a into any business, I think the role of the leader in terms of, you know, the onboarding plan from day one and, you know, providing clarity in terms of the role, the scope and expectations. But as that business will differ from business to business. Right. And the AI journey will be at a different stage of maturity. You know, there’s the opportunity, I think, for a leader to find the right blend and mix of the technical skills and the softer skills with each of the roles that they bring people on. Right. And even thinking about that as they look to recruit people and onboard them into the team. So, as a leaders kind of considering to expand their team and bring people into the organization, there’s an opportunity to think about what does the future team look like? You know, if I’m on a journey and I’m through AI and I’m removing a level of the repetitive task and I’m able to collaborate more, the roles of the leader are going to fundamentally change right the way not only do they nurture and navigate the team through that journey, but the way they bring new entrants, new team members into that team. And I think what’s going to be key for the leader in that sense is particularly in a team environment, is how you create collaboration, how you remove some of that task that we’re referring to, some of that repetitive, but create the right blend now that teams and individuals can engage in problem solving and innovation that, you know, ultimately gets them excited and ultimately then creates that virtuous cycle right where they want to be doing more AI, because now they’re starting to really find the scope and the depths of their true talent, you know, their ambition. And that gives them an opportunity to also that impact, you know, the business and the results and ultimately the customer. So for me, you know, the leadership role is key in how we kind of not just navigate, you know, bringing people into the career, but how that team ultimately moves forward in that journey with AI and how AI ultimately accelerates, exposing the full potential of that team. Right. By removing some of that repetitive task, enhancing the ability for the team to collaborate, manage knowledge and how they innovate and problem solve.

SD: Absolutely agree, Simon and Kamila, I think you’re also going to add some of your thoughts on that point, and especially around maybe those skills that aren’t so typically taught or developed within an organization, those more human centric ones?

KS: Yeah, I think interestingly enough, there’s some organizations out there now that are actually training sort of new individuals coming into the workforce on some of the softer skills. So really focusing more on effective communication and collaboration and sort of that soft skills around relationship building within the organization that you’re in. Sort of around networking, things of that nature that perhaps, newer individuals to the career are just not as familiar with or used to because they have been, again, working in that technology first type of environment. The one other thing I wanted to maybe add to, you know, I thought Simon brought up a really good point around leadership and collaboration and ensuring that the way that leaders upskill their employees is collaborative. So I do think it’s important that as we introduce AI into the organization, that we are focusing on sort of group efforts to do that. So even things like prompt-a-thons or a time set aside to essentially try the different tools and understand what they do and sort of a group effort to, to learn and understand, I think is very valuable. And then the one other thing I would perhaps add is I read this online as sort of, an interesting way to help individuals coming into the organization really use AI as a tool to support. And part of that soft skill around reasoning is, is to essentially provide opportunities to these employees to say, what would you do in this situation? Then what would AI do in this situation? And then ultimately, what has the senior leader done in this situation and start to compare those different patterns, to start to learn how to make those decisions and how to scrutinize, different aspects of AI.

SR: To Kamila’s point there. Right. Again, going back to the role of the leader in any part of the organization, I think the way we frame AI, right, needs to be kind of more positively stated. You know, we have the opportunity to kind of position it as an enabler, right? Something that can actually improve job satisfaction, career development, and, you know, as you go through that journey, celebrate the successes, sharing the learnings. Right. It’s a good way to, you know, maintain that positive frame around from a people point of view, from a culture point of view, from an organizational point of view, you know, the many upsides of what this can do in terms of the kind of positive impact it ultimately enables.

SD: Absolutely. You know, we’re already seeing some very interesting examples in education as well. American universities, good school of business is embedding AI across the curriculum and training faculty on AI tools. Carnegie Mellon has launched an undergraduate AI program that is explicitly focused on the beneficial and useful AI, not just technical capability. And there are community colleges all through the U.S that are developing systems like Miami-Dade, Houston and Maricopa. They’ve formed AI education consortia, aligned with industry partners like Intel and Microsoft to democratize access to AI skills. So what can employers learn from these models? And is there anything that a business like ours could do to build a reskilling program like that within our organization?

KS: I think one of the things that we’re already doing certainly within ATS, but I think other organizations are and will just become more important, is mapping the skills required for future careers and for future jobs, as opposed to looking at the job titles. So I think one of the things that we do well in parts of our organization is sometimes there isn’t a perfect fit for somebody in a role, and I think as we start to evolve with AI, there’s new opportunities that arise for individuals to take on more, differentiated jobs. And I think being open to what those are going to look like, that it might no longer be a certain title or certain profile of role. It’s going to look different. And so I think being open to finding opportunities for individuals to step into these types of positions, like off the top of my head, I can think of a handful of individuals already that have sort of responsibility for different things within the organization that, again, doesn’t necessarily fit into to a perfect box. And I think we just need to be prepared for that. And again, I would say focus more on the skills than the job itself. And what is that going to require for the future?

SR: Yeah, and to build on that, I think, you know, any organization obviously recognizes the value of its employees. And certainly within when we look at the values within ATS and we think of people, process, performance, you know, there’s a clear focus in terms of how we want to engage our workforce, how we want to invest in our workforce. Right. So when we think of you know, AI, you know, how should we think of that in terms of actually unlocking some of that potential that today is constrained? Right. And we’ve spoken about a number of examples of use cases. How we can do that. I think maybe more strategically we can think about, you know, how does this ultimately impact all design? Right. The roles we have today and the roles we have in the future within our kind of organizational structures will fundamentally change as AI really takes root and actually takes away some of the non value added and gives the opportunity for the teams to be truly engaged and drive some of that kind of creativity, that problem solving, that innovation. So I think strategically we can look at how roles will change, as Kamila was mentioning, but how the organization can change with a clear intent to unlock that, you know, that hidden potential that you know any organization has. And certainly as ATS, one when we think of people as part of our core values, you know, it’s an opportunity to accelerate, you know, that advantage that we can create both in terms of, you know, shareholder value, but also customer value.

SD: If we’re talking about skills and tasks and jobs and learning and bottom rungs of the career ladder. One of the big questions I’ve heard from people leaders is that if AI is now doing the basic tasks, how will juniors learn? Those grads just coming in to the workforce? Historically, we gained proficiency and we learned judgment by first doing those more foundational and routine parts of the job. Kamila, is that a concern? You were talking about redesigning roles and jobs. Is that part of what we need to think about to make sure that these new entrants to the workforce are walking before they run? With AI as perhaps a support rather than a replacement to earlier in the game. I think that we have the opportunity to look at things maybe a little bit differently. And what I mean is, as people are entering the organization, knowing that AI is a big topic of conversation right now, I think one of the opportunities that we have is to start to think about sort of an AI first culture, if that makes sense. And let me explain what I mean by that. It’s starting to use AI for some of those basic things, like building a presentation or, you know, some of those administrative tasks that perhaps would have we would have sat there spending forever doing ourselves before. Instead, I think we have the opportunity to teach our younger individuals coming into the organization is to say, start with this. But now, how do we think this through, and how do we refine it and how do we progress beyond this? So if anything, it’s a bit of a time saver. And then I think it actually could accelerate that strategic thinking and that muscle that if anything has historically come with time in your career, I actually think that it could be an accelerator to that because you’re not wasting time on those little bits. Now you are using your time to scrutinize the work that AI has helped you to come up with, but without losing that human centric aspect.

SD: Simon, anything to add?

SR: Yeah, I understand the basis of the question in terms of, you know, the non AI way of doing things is a good foundation. It’s a good starting point, right, to kind of learn, process and task. But also I think having two young sons, I think they’re probably more technically predisposed to look at easier ways of doing things. So I think the premise that people coming in and learning a process that can be improved, I think will soon be met by, I think, most new entrants joining an organization that will probably be more interested in finding new ways, better ways, AI, assistive ways of actually improving the process. Right? I think they’re more predisposed to challenge the status quo and how we do things right. So whilst I see the value in terms of, you know, that getting a foundation and a set of basics of how we do business today, I think that more predisposed to actually challenge the status quo because of the way they’ve learned, the way they’re kind of exposed to other kind of technology and how that impacted the way they study the way they gained experience, maybe before joining our organization. Right. And I also think from our point of view, ignore the opportunity that, you know, we’re relatively early in our AI journey, so there’s plenty of opportunity for anybody joining our organization to understand that the non automated or non optimized process and kind of technology based way of working, right. So I think we’re always going to have that opportunity to kind of teach the basics and get to a solid foundation. But I think we should also you know as we’re bringing people in, make sure that we can kind of navigate them and help them navigate us to more efficient ways of working and I think it’s potentially an opportunity of improving the way we can actually make roles in our organization become more attractive to new employees.

KS: If I could just add one thing to that, because it just, made me think of something. Simon, your point about AI being relatively new and so there’s still opportunity for people to come in and sort of learn our non digitized, if you will, organization very valid. But it also made me think that people coming into our organization are going to be potentially more ahead of the curve in terms of the technology that’s out there. And we actually would have quite a bit to learn from those junior people coming in as an organization. And so I think that there’s a piece here of, I guess your to loop back to your earlier question, Sarita, I think we can help junior employees by building their critical thinking as opposed to mechanical skills. But I also think on the flip side of that and juniors coming into our organization have a lot that they can teach us in terms of our processes.

SD: I love that. That’s awesome. Then, you know, conversely, for those that fall into the category of jobs that will shrink or just are wondering, they ask, will AI take my job? Simon, how do you address employee fears about job displacement or skill obsolescence? What do you actually say when someone asks you that question directly?

SR: I think number one change is unsettling for, any type of shift from, you know, a current state to a to a new state. So I think personally, being clear on the why in terms of why we’re introducing in this case, technology, I think number two is, is really trying to listen to understand what the concern is and what it’s based on. More often than not. You know, I think it’s addressable. And I think, you know, it’s trying to get beyond the headlines in terms of what that kind of concern is in terms of, you know, what’s driving the conversation about, you know, the threat or the uncertainty that this creates. But then to start exploring through that conversation, you know, what it could lead to? What’s the opportunity that could be created by taken away? And I think in any conversation somewhat related to this, I think you will always find that employees want to move into more value added roles. They often frustrated by the waste or the non value added or the clunkiness, if you like. So I think you know, addressing that nobody wants to continue to work in an environment where there’s inefficiencies and you know, it’s not optimizing their skills. So you know, really get to I think the crux of their concern and then, you know, really try and create the right conversation about, you know, what ultimately the positive side of it is because they’ve spent probably most of their time and energy concern, worried about what the implication could be. Probably not enough time spent looking at, you know, what it can create, what it can actually create in terms of opportunities, right. And fulfillment, for the individual. I think also as an organization, right. We are a growing organization at ATS. We’re an organization that has ambition. We have ambition to be more competitive in our marketplace. And I think, you know, it’s important that all of us recognize that our journey with AI is not limited to us, our competitors, our suppliers, our customers are going through similar journeys. So as a competitive organization, we also know we need to drive greater organizational effectiveness, greater efficiencies, greater use of our talent. So it’s really trying to thread that conversation, understand the concerns, explore the possibilities, what it could mean, restate it in the fact that there’s something to win for the individual. But there’s a lot to win for the organization, particularly an organization that’s willing to invest in careers, strategic investments in terms of where we want to focus the business going forward. So I think it comes down to having leaders prepared to have those conversations, but also equipped with success stories that, you know, ultimately can kind of balance the concern with the opportunity.

SD: So how do we help employees feel invested in it, not threatened by it? How do we help them feel that this is also, as you said Simon, about them, and not just about the organization and a productivity play?

SR: Yeah, I think there’s a definite link here. I think in terms of individual development plans, you know, when we think of the statement, you know, we are invested in our employees future, invested in their growth and development. We have mechanisms to do that through IDPs and so forth. Right? So, you know, right from there, there’s an opportunity to say, when we look at what’s already been stated as the development, ambition and requirements of each individual, how can we enable that by actually liberating some of their time in their day to day through AI, to actually focus on where they’ve already identified, where they want to grow? To an earlier point in our discussion here, right. The view, I think of where your where you want to take your career, where you want to develop as an individual, will potentially expand as we engage more in AI. Right? I think we will definitely see the opportunity where before, you know, it’s been career development around one set a particular knowledge and the discipline. I think AI could become a gateway to actually start developing and growing and gaining experience in different areas outside of your immediate discipline and where you probably spend, you know, much of your career, right? So and that’s why I think there’s a huge, you know, upside with AI, particularly on knowledge management and the ability to collaborate in an organization of all size, you know, using AI. And then coming back to your question that can only then help the individual think about where do they want to take their career. How can I take some of the kind of non value added repetitive tasks out to basically give me some capacity to, to reinvest in some of the development areas that I’ve already identified or may identify as I kind of continue the journey of more expanded learning.

SD: Yeah, I completely agree. That’s excellent. Kamila, what do you think?

KS: I think Simon said it well, so I don’t know that I have too much more to add, but I do think, you know, going back to something that I had said earlier around kind of making it a community learning initiative. So your question was around, how do we ensure that this isn’t just an organizational initiative as seen by employees, and that it truly is something that’s going to positively impact them as well? So I think including them in the conversations around, hey, if we could free up some of your time, what would that look like? And then what could you do with that additional time that would actually bring you joy, and that could maybe move the needle on certain projects or programs that you’ve been working through. So I think it’s not something that can be done in a silo. I think it does require their employees input and participation in it and frankly, active participation in it. And I do think that additionally, we Simon had mentioned about employee engagement surveys and development plans. I do think that there’s going to be a piece here of measurability. So how do we then demonstrate to employees that, hey, as a result, you’ve become more productive or we’ve saved you X amount of time having to do these sort of monotonous tasks or, you know, you’ve been able to advance in this area that you just haven’t had the time for. So, like, how do we actually start to measure some of those outcomes and then show employees the impact and the value that they’ve had? And I think on the employee side, not only what I then expect to see, you know, some more positive feedback about their career advancement and overall outlook, but also probably things like work life balance and wellness, things of that nature that I think could be measured as well.

SR: Yeah, maybe just another twist to add, right. I think, you know, we just spoke there about what this means for the individual. Right. But as humans, I think we all enjoy working in a team environment, in a collaborative environment. And, you know, it strikes me that there’s also the phenomenal potential that when we collectively leverage the power of AI to take away some of that repetitive tasks, better organize information and knowledge, etc., it can have a force multiplier effect then in terms of how we collaborate within teams, how we interact within teams, and how, you know, with our interpersonal skills. Ultimately, we drive a very, you know, different outcome as a team as well as individuals, right? We take away some of the barriers that limit us today. That could be language, that could be information, that could be knowledge, it could be data, could be analytics. So you kind of think of unlocking the power of teamwork across different businesses, different regions, different markets. You know, that’s where I think we can really see the human potential.

SD: That’s great. That really is great. Okay. We’ve covered a lot of ground. And if I bring it back to the title of the episode, which was Upskilling for an Automated Future, Preparing People and Not Replacing Them, I’d love to end with a quick lightning round. Either of you please just jump in.

First question, if you could give one piece of advice to employees who are worried about AI, what would it be?

KS: I would say focus on learning AI as opposed to fearing it because it’s out there and coming anyway.

SR: Try it before you deny it.

SD: Very good. Next question. What’s the one piece of advice you’d give to managers who want to responsibly introduce AI into their teams.

SR: Lead by example.

KS: Start small and be transparent.

SD: Very good. Last question. What advice would you give to senior leaders designing the talent strategy for the next 5 to 10 years?

KS: For me, it would be ensure that you’re focusing on things like data fluency and investing in upskilling for the future.

SR: Have a clear goal of what an AI enabled organization looks like. A clear vision. I think that’s going to be key in the change management journey. As you think of making structural changes, start with the why. Have a clear vision of where we’re trying to move to. I think that will remove many of the concerns of the barriers and gets people on board.

SD: Simon, Kamila, thank you both for sharing your insights and examples. It’s clear to me that while AI is reshaping work, we still have a lot of latitude in how we respond, in the skills that we build, in the culture that we create, and the opportunities that we open up for people at every stage of their careers. To our listeners, thanks for joining us for this episode of AI and Automation Shaping the Future Responsibly. In a future episode, we’ll dive more deeply into leading through transformation an executive perspective on AI, automation, and purposeful change. Until then, stay curious, stay responsible, and stay human.