2026 HR Rewards: Mastering AI, Pay Transparency & Compensation

[00:00:00] Mallory Hendry: Hello everyone and welcome. I'm Mallory Hendry, Content Specialist Manager with Canadian HR Reporter. Thank you for joining us for today's webinar, 2026 HR Rewards, Mastering AI, Pay Transparency and Compensation. Between new pay equity laws and AI-driven change, the Canadian workforce is evolving rapidly and HR is being reshaped alongside it. Today we're joined by Mercer Canada's Jayna Koria and Stefano Biscotti. They'll take you through compensation projections and practical strategies to give you an edge in this shifting market. At the end of the presentation, our panelists will participate in a question and answer period. So be sure to type any questions you may have into the Q&A box within the webinar software. I'll turn things over to Jayna now to begin the presentation. Take it away, Jayna.

[00:01:00] Jayna Koria: Great. Thank you, Mallory. So hello and welcome to everyone on the call to our future forward signature event, Redefining Rewards Through Innovation and Transparency. We're so delighted that you're able to join us today and we look forward to an engaging session with you. But first, let me introduce myself and Stefano who will be your other speaker for today. My name is Jayna Koria. I'm a partner in our career business in Toronto and the National Pay Equity Compliance Lead for Canada. And joining me today is Stefano Biscotti, a principal in our career business in Ottawa. Stefano will provide an economic update that will then set the stage for showcasing the latest results from our compensation planning survey. I will then come back to cover some of Mercer's latest thinking on the AI revolution. But just before we start, some house rules for today's session. A few do's and don'ts for the session today. Please do not share competitively sensitive information, such as employee compensation or benefits levels. Please do not discuss planned reductions in compensation or benefits. Totally okay to discuss concepts and ideas for how to acquire and retain talent. And it's okay for you to take what you learn from our surveys and this event to make independent decisions. So without further ado, let me pass it over to Stefano.

[00:02:45] Stefano Biscotti: Hi all, and thanks, Jayna. So as part of the introduction, I think we should have said, and Stefano's not an economist, but I will do my best to provide some of the economic context. So thanks for making the time, everybody. Let's get started with the first section. And I will manage these slides. Janet, can I ask you to maybe change slide for me to the next one? It's not connecting for me. Thank you. And so as we delve into the economic outlook for Canada. As of early September, it really is important to set, as it sets the tone for some of the comp projections that will come into the next section that we'll be sharing with you. All right. So as you see from the graphs here, we will be sharing quite a bit of data with you. Following an initially muted reaction, even in Canada, trade tensions ramped up over the winter, as you all know. Markets saw a bit of a turbulent start to April with the Liberation Day tariff announcements that led to a pretty steep sell-off of things, as you see in the middle of that graph. The markets have since recovered all of the drawdowns and more, as investors have shrugged off some of the trade and geopolitical risks, with markets now nearing an all-time high. As we've seen this past week, however, things may yet change with some of the announcements. So more to come on that. And as we look at the graph, interestingly, the S&P TSX in Canada, the MSCI EAFE index, as well as the MSCI Emerging Markets Index, all outperformed the US market so far this year in Canadian dollar terms. As they say, however, Bay Street is not Main Street. The real economy is showing clear signs of a slowdown for Canadians as exports and business investments have pulled back a bit. The slowdown has, however, impacted Canadians in different ways. While those in stable situations seeing growing balances in their investment accounts have been less affected, others working in impacted either sectors or communities have had to tighten their belts a bit, as we've seen in some of the manufacturing areas, for example. Here we're seeing that unemployment is on the rise. Unemployment rate rose by 0.2% to 7.1% in August. As the economy shed around 66,000 jobs, the unemployment rate is now up 0.5% since the beginning of the year. The hardest hit is youth unemployment, ages 15 to 24, which has risen significantly since the beginning of the year, hitting 14.5 percent. Sorry. 14.1% in August, leading to an increased attention to the challenges facing younger Canadians, which we all worry about.

[00:06:10] Stefano Biscotti: Growth in total wages paid also slowed materially in the second quarter to 0.2% quarter over quarter. And a weakening labour market combined with elevated core inflation suggests that there are opposing pressures for further cuts to come as the Bank of Canada's overnight policy rate sits at 2.5%, with the recent change in September, which is still within the neutral range rate that they provide, which falls between 2.25% and 3.25%. In the U.S., the labor markets most recently also showed signs of slowing, with the latest job reports falling short of expectations. In August, the Fed was increasingly expected to start cutting rates on their end, despite facing pressures from the U.S. president to lower borrowing costs more quickly. The expectations of falling rates has provided support to the stock markets, however, and again, with the recent announcements and latest news in terms of government shutdowns in the US this week, monitoring, we'll continue to see what the impacts are for both Canada and the US. The next piece of the puzzle, of course, is to gauge how slowing growth and rising unemployment have influenced inflation. One would normally expect a slowing economy to slow inflation as demand for goods and services also slow. And the headline inflation did slow to 1.7% in July from 1.9% in June. But it rose back to 1.9% in August, so still below the Bank of Canada's 2% target rate. Falling gas prices have had the biggest impact on the slowdown in headline CPI, with prices falling around 16.1% year-over-year in July as a result of the removal of the carbon tax earlier this year. CPI, however, rose 2.5% year-over-year in July, excluding the impact of gas. We are seeing a similar up-and-down trend happening in August and September, and of course food prices remain a challenge. With Canadians paying 27.1% more for food purchased in stores July 2025 when you compare that to July 2020. So there's a pretty steep cost of food prices that have changed. And shelter continues to be a significant driver of inflation, contributing to the cost of living pressures that are rising. The bank's preferred core indicators when they talk about CPI median and CPI trim registered at 3.1% and 3%. At September on the higher end of the bank's target range, which falls typically 1% to 3%. So both of those numbers edging the upper end of the range there. This elevated core inflation may pressure the Bank of Canada to keep rates on a near-term hold, balancing inflation risks against a slowing economy and rising unemployment. And of course, the Bank of Canada is monitoring that closely in terms of the speed at which costs increases are passed on to the consumer. And how inflation expectations might evolve from that. All of this in the context that these do have business decisions that all of you I'm sure are eager to listen to as we get into the compensation planning as well. So how does this translate to the interest rate outlook? Labor demand dynamics and inflation measures are primary drivers at the front end of the Canadian rate curves for the next several months. The Bank of Canada is adopting a more cautious approach to monetary policy, as we've seen, as the range of potential outcomes for both inflation and economic growth depends critically on the U.S. trade policy, which is still highly unpredictable.

[00:11:00] Stefano Biscotti: The current policy stance is viewed as neither restrictive nor accommodative. Sorry. But markets are anticipating at least another potential rate cut in 2025, and they're too possible with the scheduled rate reviews remaining for the year. That possibility will lead to a possibility that Canada's policy rate may fall to the lower end of the Bank of Canada's neutral zone, which is 2.25, and that neutral zone being 2.25 to 3.25%. So we're sitting at 2.5 at the moment. The Bank of Canada will also be concerned about providing support for a slowing economy with rising unemployment and the risks associated to continued trade disruptions as we're seeing. And the Bank of Canada will also need to balance those objectives against the risks of re-accelerating inflation too quickly. So these are factors that will continue to introduce uncertainty in our outlook for businesses looking ahead in terms of making both investments and cost management decisions. That fall you know the rest of this year and into uh the new year so before we delve into the details of compensation projections i did want to share one more economic related uh chart to help set some of the context uh for us i will uh start here and so In our compensation planning survey that was conducted in July, we did ask participants about the external economic environment potential's impact on their compensation decisions in 2026. When you're looking at the pie chart and you're adding the 49% to the 20%, basically two-thirds of Canadian organizations said their economic environment will have a moderate to significant impact on compensation decisions for the upcoming year. So I'm actually a bit surprised by some of the projections that I'll be sharing on the next slides to come. Before going to the projections on comp, we also asked organizations what they were prioritizing or deprioritizing for the upcoming year in light of the economic environment. And specifically, organizations expect certain things to increase in importance, with the top three being, as you see on the right-hand side of your screen, skill and talent development, market competitiveness, compensation changes. And of the things that are becoming less priority, but nonetheless still priority, hiring was mentioned the most, but it's only 16% of the respondents that said hiring. So key focuses being the skill development and skills readiness for what is to come. I think that is the priorities and themes that we're seeing emerging for the upcoming year.

[00:14:30] Stefano Biscotti: So let's get into the projections and the numbers. I know everybody is typically eager to see some of these things. So based on the data we collected in July, Mercer projects that the average total increase budget next year will be about 3.2% across Canada. All of the total increase values are in green on this graph, and the merit increase budgets are in blue. The projected merit-only increase will be about 2.9% across the country as projected for next year. So what does exactly the 3.2% mean? So after years of rapid growth, specifically if you're looking at the graph here between the years 2022 and 2023, where you had higher budgets and higher growth, things are tapering off. And so there's a more cautious mindset. With the broader economic landscape that we were just talking about, marked by the uncertainty and the inflation potential, organizations are definitely re-evaluating their spending, making sure that every compensation dollar counts. Employers are still prioritizing strategic talent investments, as we saw, focusing on rewarding key skills, retention, and future ready capabilities. This shift reflects a move from reactive compensation adjustments, post-pandemic or through pandemic, to more deliberate targeted strategies that align with both long-term business objectives and people strategies. And while the total increase projection is generally holding steady with last year, a lot of total rewards teams we anticipate are going to be a bit like ducks this year, you know, cool calm collected above water and paddling furiously underwater to make sure that every dollar in compensation counts to make sure again that you're attracting, retaining and developing. As a reminder, the 3.2% total increase budget that we're showcasing here includes merit increases, as well as adjustments for promotions, the cost of living adjustments across the board increases, off-cycle increases. So that 3.2% is really your all-in compensation budget projection for the year. All of our data, of course, represents non-unionized employees. 2% also includes organizations that are not planning to have any increased cycle next year. At this point, based on the data that we collected in July, 90% of organizations that have responded are planning to have an increase cycle in the next year. 3% of Canadian organizations aren't planning an increase for the upcoming year and another 7% just weren't unsure yet. We did have great participation in terms of the data being reported with 516 organizations providing data in July. And the report was released mid-August, a few weeks earlier than we normally would. So kudos to the team for doing the hard work to respond to client requests to have the data sooner. Please give it to us sooner. The participant profile also represented 15 different industries ranging broadly in terms of organization size, both in terms of headcount and revenue.

[00:19:00] Stefano Biscotti: And so from here, I'll get into a bit more details as we go through the industry view. So on this graph, we have also segmented the 2026 increased budgets by industry, with the same blue bars being the merit increases and the green bars being the total increases. The detail here is you can see as you can see is high tech and insurance lead the way with the highest total increase budgets projected at 3.5 percent followed by crown corporations who are also above the national projection at 3.4 percent and then you'll see consumer goods and banking financial services at 3.3 percent being contemplated and again these are early projections to that end. the variation when you're looking across the board by industry from lowest to highest projections is only a 0.4 percent so things are relatively stable across the country so there's not a huge variability uh throughout industries i'm not surprised by insurance leading the pack however they did so last year as well and if you think about all of the uh the wildfires and the elements issues that they're they're dealing with it's an exciting and busy time for them for sure High tech tends to flop around a little bit in terms of being either at the highest or lowest end of increases year over year, but it's fairly stable at 3.5 compared to where it was last year, which I think was hovering around 3.4, 3.5 as well. And with the latest projected austerity focused federal budget, time will tell with what the potential impacts will be when it comes to government and non-quasi-government spending as it relates to what was projected earlier in the summer to what will actually materialize as real impacts and budgets as they finalize between now and the end of the year. As we get into a little bit more details, I just want to take a bit of a deeper dive into the data. And here's how the total increased budgets are actually distributed by respondents. So the chart looks at the actual values provided by each participant for total increase budgets. As you look towards the middle of the graphed box, or the dashed box, this is where the bulk of our data is located. Nearly two-thirds of responses are at a total budget increase of 3% or 3.5%. And again, this is projected with refinements and updates to come in the coming weeks. When we also looked at the 4% or more, they only make up just 17% of our sample size. At this time last year, just to give you a bit of sense of the differences and how things are morphing, roughly a third of companies were planning an increase of 4% or more. So we're definitely seeing a bit of a shift in retrenchment. And two years ago, that number was actually 50% of respondents. So you can see that things are after tightening up. It's really important for me to reiterate this a few times. This is really a highlight that these are really early thinking from Canadian organizations and we need to remember that our data was collected in July and already a lot has changed or is evolved. So as we look at the information At the point where we did collect the data, 90% of survey respondents were in the preliminary phase of setting their budgets for the next year. So if you look at the graph on the left, 90% of those were at the preliminary estimate stage. Of those that were at the preliminary estimate stage, you can see that they were fairly conservative. When you move over to the right-hand side of the slide where they were projecting a total budget for a total... compensation at 3.2%. We caveat this with it being preliminary because it's a nice way for us to say we're really happy and thrilled that organizations are taking their planning seriously, they're completing surveys like the one that Mercer conducted as well as many others, joining us for events like this one, like this webinar to really hone in and start thinking about what their upcoming year will look like. Not surprisingly, when you look at those that are projecting what salaries might be, there's going to be some fine tuning. There is a small minority of companies that also reported that their increased budget had already been approved by leadership. So these are the pink bars on the right hand side. But it's a really small sample size. When looking at the data for these companies with approved budgets, it's not that they generally have higher projections. It's just that they have fewer of them that budgets under 3%. So, you know, when you're looking at a total projection for that group at 3.5, remember, it's a small sample size and there's not a lot of variability, which is a common theme in the data that we're seeing and reporting to date. And of course, As I get to this next slide, once you also get a chance to digest some of the numbers we're sharing with you today and start refining your own projections, Mercer will be out with an update to our survey collection and we will, as we normally do every year, reach out with a new invitation mid-October or so to get your latest thinking on what is planned for the upcoming year. So here we're getting into salary structure adjustments. So we also want to provide you with information around how our organization's planning and where are they from a salary structure perspective.

[00:24:40] Stefano Biscotti: Which is when we look at the right hand side of the graph, on average salary structures are expected to increase based on the information that's been provided by 2.7% next year. At this point 51% or about half of the companies that have reported are planning to move their salary structures upwards with another 39% of companies undecided yet if they're going to make any salary structure adjustments or not. Historically, the salary structure adjustment and the total increased budget have been about a percent apart, so 1% apart, which if you take that 1%, it's really what allows organizations to move their staff through their salary bands increase that your competent copper ratios uh relatively to to to structures and address any internal equity issues. Since COVID, however, we're seeing a narrowing between those two numbers, between the total increased budget and the salary adjustment budget. So as we look at the pink part of the graph towards the right, you'll notice that only 0.5% difference exists between what is contemplated as the total budget and salary structure movement. This is the tightest that we've seen these two numbers in a really long time. So as a result, there really isn't a lot of employee movement possible or increase in their respective salary positioning to go around. Organizations do need to listen to employees to identify valuable benefits and enable that targeted investment of dollars to make sure that they're attracting, retaining and motivating key talent for the year to come. As organizations also need to cater to key messages. Sorry. to what employees need to hear as well and that ties into some of the transparency work that we'll be sharing with you. So remember that those that are motivated and understand will want to know how sorry can we go back two slides, Jaina. Yeah, perfect. So employees will be mainly concerned by what is available to me of that 0.5% pink margin that is sitting on top of the 2.7 structural change. And so that becomes an important message because there will be some employees who much prefer a more peanut butter type of approach where you're spreading budgets across. but for others who are motivated by performance and that direct tie-in between performance and reward, that margin is important. very big. So key messages will be important. And a couple of more pieces of info to share with you from a structure perspective, I just want to give you a bit more industry cuts. So from a Crown Corporation perspective, what's been shared with us is we're expecting salary structure potentially to move 2%. High tech is 2.7% with insurance at 2%. And all of those numbers also include the organizations that are reported no adjustments as of yet. All right, so on to the next slide. Thanks so much. So we've shared quite a few data points and reference points for compensation planning, but as you think about your respective organizational messaging, it's critical to keep pay transparency in mind. In an era of increased pay transparency, not every organization needs to be, nor can be, at the highest payer level in the market. When organizations are transparent about their philosophies and comp philosophies and expectations, employees are known to be more committed and engaged. So if you think of what organizations or industries you're competing with, where in the marketplace you're competing in terms of your positioning, these are all key elements in communications to keep in mind as you plan for communications with your internal staff and external potential staff. Across Canada, 59% of Canadian organizations are compliance-driven on pay transparency. They comply with provincial pay transparency laws, but don't necessarily have plans to broaden transparency beyond what is required. Alternatively, about a third of the Canadian organizations are either already sharing pay ranges, both internally and externally, or are planning to do so. They are going beyond what is legally required at the moment. There's a small subset. You can see a 4% are unsure there. There is a small subset of companies, being 4%, that don't know what their approach will be just yet. From what we're seeing, they are organizations that operate in provinces that don't currently have pay transparency legislation in place, so they haven't had to decide whether they will be driven by either compliance or strategy. Of course, generational preferences may play a part in the types of talents that they attract or are able to attract as they think towards the near future in and their people strategy plan. In Ontario, there will be play transparency legislation coming in in January. So we've asked the same question over the past four years about whether organizations share pay ranges on external job postings. The labels on the graph are quite lengthy. We've shortened them for simplicity and reading. ease of the slide but let me give you a bit of the descriptors for each of the selected options. The first option being complies is defined as complies with all provincial legislation and we do not share salary ranges where we don't have to. The second option which is the explore sharing more is defined as we comply with provincial legislation where required but we're looking at sharing our ranges more broadly. The third is basically defined as we share our ranges across all of our job postings in Canada. And finally, the last bucket being we just don't know what we're doing just yet. As we look at this graph and we look at the first four blue bars from the left-hand side under comply from summer of 2022 to today, we can see that the approach to pay transparency has generally been pretty steady. Overall, half of the companies comply, another 20-ish. percent are exploring sharing more, 10 percent are sharing nationally already, and about five percent don't know. What's a little bit more exciting for us in terms of, you know, looking at data is the green bars. In light of the pay transparency legislation coming into effect in Ontario on Jan 1, we also asked organizations what they were, they project their approach will be, and we're seeing some interesting shifts here, so compared to prior years. There's almost a doubling of companies that plan to share their ranges nationally and there's a lot more that don't know and you can see the second option the exploring sharing more has dropped because people are actually putting into place their processes for sharing. This tracks to what we've seen and we've been discussing with our clients over the past few months. For many employers, particularly those with large Ontario-based populations, many are still deciding whether they are ready to rip off that bandage or not. As one of our colleagues likes to say, pay transparency is a bit of a bamboozle. You think it's about posting your ranges relative to jobs, and whether or not your talent acquisition teams will or won't be able to hire with these ranges. But in all actuality, posting the ranges is probably the easiest part of what needs to be done. It's the ramifications of current employees or to current employees that is actually the biggest part of pay transparency work. If you think about it, there is absolutely a need to make sure that your internal house is in order before you start delivering messages to both broader internal staff and externally. Once you get over that hurdle of whether you're sharing or not sharing SATA ranges on job postings, the next big questions that we often get asked at Mercer is, well, what do I share? As you can see from the screen here, the approach of what is actually posted on range is quite diverse across Canada. with national market-based pay structures, geo-adjusted market-based pay structures, and subsection of the market being the three most common approaches, and making up about a third of, sorry, two-thirds of the sample size of respondents. I do want to stress, however, that there's no right answer to this question in terms of what you share, as long as it's a legitimate bona fide value that you're posting and you're building around it. With pay transparency compliance, As I said, it is a small part and it's really about the employee experience. And I just want to belabor the point a little. For example, if you're posting ranges that are higher than where your existing employees might be sitting on the salary range, they likely will have questions. Why am I positioned here on the salary range when you're posting such a broad range? And the other piece of the work that's super critical in being able to manage all of that will be, are your managers and team leaders able and prepared to to have those tough discussions. to make sure that you know there's a clear message and and people aren't uh you know negative negatively impacted by just the mere posting of of ranges and how they determine their internal worth or value to the organization all right um I'm going to go back a slide, I apologize. So with the upcoming pay transparency legislation, you can post a dollar value. For example, you can post jobs that have $20 an hour, as the data posted or shared, or a salary range on external job posting. So the salary range can't be wider than $50,000, so that's important. And this is really to prevent some of the things that we saw in terms of organizations being sneaky by posting really crazy ranges, where we saw ranges going from $50,000 to half a million dollars and somewhere in between, thou shalt be paid. So to avoid that, your range maximums must be within a $50,000 spread. When you're looking at the graph and the responses that we got, however, two thirds of Ontario companies plan to post a salary range on their job postings. versus a fixed value. And of these firms, the pie chart shows the range style that they intend to generally post. So for the lucky 20% that you see in the pink slice of respondents, their salary ranges are not wider than 50K already, so they can post their full range without any complications or further negative consequences. For other firms, the third don't know how they intend to calculate the salary ranges that they will be posting. And it's only you know, we'll say early October. So there is time to continue this dialogue. And I'm sure that we can all figure out what to do and how to do it together. In the meantime, I'm doing a bit of a time check. There is a lot changing in the work world. Technology is also changing. There are potentials. And I'm excited to pass the mic back to Jayna, who's going to give us a little bit more on AI and the impact to the total rewards function.

[00:33:00] Jayna Koria: Great. Thank you, Stefano. Um. So we're going to kind of switch gears here. And there are a lot of numbers that we just went through. And I know it's a really busy time for compensation planning for most total rewards professionals. So hopefully that gave you some food for thought and some things to think about. But we're going to kind of switch gears. So let's get candid. Things are changing rapidly around you. The role that you held probably just even a year ago may already look different or may no longer even exist. AI and automation are reshaping the landscape. And the key question is, isn't whether your role will evolve, but how quickly we as total professionals can adapt. Jobs are honestly transforming almost overnight. External factors such as AI, automation, shifting talent pools and digital transformation require us to rethink how work is getting done. And at the same time, internal pressures are to do more with less, to flex the talent that you already have, and to grow the business while managing costs are more prominent than ever. So today, we're going to explore how Mercer can support you on this journey of transforming the rewards function into what we would like to call a strategic asset, a rewards revolution, let's say. So we've all heard that AI can unlock productivity. But our studies show that progress is proving to be slow for many. Although 96% of CEOs see AI as an opportunity, only a very small percentage, less than 7% of total awards leaders have seen a significant impact on their processes. And although many organizations seem to be investing heavily in HR technology, progress in automating those HR tasks still remains quite low. And over 80% of employers say they are redesigning work to increase productivity, but less than a quarter say they have made considerable progress to date. So overall, while this shows there's a lot of optimism about AI's potential, there's still work to be done to fully realize its benefits in the workplace. But before we continue, let's just level set on some of the terminology that I'm going to be using today. What is automation? What is AI? And some term that you've probably already been hearing, generative AI, which I'm going to refer to as Gen AI from now on. Automation involves using technology to perform repetitive tasks automatically, often following predefined rules without the need for any kind of learning or adaptation. Now AI refers to machines designed to mimic human intelligence such as understanding language, recognizing patterns and making decisions based on data. AI can adapt and improve over time through learning. An example of this could be customer service interactions. Automation could be an AI scripted chat bot that responds with predefined answers to common questions such as, what are your store hours? Or how do I reset my password? It follows a set of rules without really fully understanding the context. AI, on the other hand, an advanced AI-powered virtual assistant can understand natural language, interpret complex queries, and provide personalized context-aware responses. For example, it can handle nuanced customer complaints or suggest tailored solutions based on previous interactions. So while automation can handle routine tasks efficiently, AI can tackle those more complex decision-based processes that require understanding and reasoning. Gen AI is a subset of AI focused on creating new content, such as text, images, audio, or even video, that resembles human-created data. It uses advanced models to generate realistic and coherent outputs based on the patterns learned from large data sets. For example, generative AI can produce human-like text responses or create new artwork. Examples in our daily life of AI can be like Google Maps or Waze to help you understand kind of real-life traffic and suggest... alternate solutions. Chatbots and virtual assistants like ChatGPT can generate human-like responses to questions or conversations. So while AI broadly encompasses systems that mimic human intelligence, Gen AI specifically refers to models that produce new original content. The focus of today, however, is not how AI will transform your industry or your organization, but we're making it a little bit more personal. We want to talk about how we can leverage AI to support the rewards function. I see a hand up. I don't know if... We're taking questions right now or why the hand is up? Okay, maybe. All right, I'm going to move on if everything's okay.

[00:38:00] Mallory Hendry: Yeah, I'll just say, Jayna, if they want to ask a question, they can put it into the Q&A box. And when we get to that time, we can we can read it there.

[00:38:10] Jayna Koria: Perfect. So in March this year, we conducted a survey on the effectiveness of HR and the total rewards function. And in particular, we asked about investments organizations are making or considering to enhance the efficiency and effectiveness of their total rewards teams. Now, I'm going to take you kind of to the lower portion of this slide. So the purple and the green means that, you know, investments have already been made or they're planning them within the next 12 months. And the purple and the pink are really, hey, we don't know what we're doing. We're not really planning anything. So you can see in the lower three bars are this seems to be considerable actions or planned investments being made on things such as enhanced data analytics, program harmonization or simplification, and automation. But what's really noteworthy is that kind of third bar from the top, where you can see in the bold purple and pink that notably 70% of organizations were unsure or had no plans to utilize AI to improve process execution within total rewards. As mentioned earlier, AI seems to be knowingly or unknowingly around us, in our personal lives from personal recommendations on streaming services like Netflix, voice assistants such as Siri or Alexa, or if you're like me, online shopping platforms that make you buy things that you didn't realize you needed. But in our professional lives, Sorry, in our professional lives, it sometimes is popping up with chatbots in the workplace to provide instant support for typical kind of employee questions about HR policies or IT issues, or typically even in banking for detection systems, monitoring transactions. The question is, why does progress on the use of AI in our daily lives as total rewards professionals seem to be so low? Well, let's discuss some items on the next page. Some of the things that we're hearing is fine. We know AI costs a lot. So let's skip that. But some of the other things that we're hearing that why most companies are still struggling around kind of incorporating AI into total rewards functions. One is honestly understanding the technology. Many companies struggle to fully understand what Gen AI is and how it works. potentially leading some unrealistic expectations or potential misuse of the technology. So it's important for companies to invest time and resources into understanding the technology before they go around trying to implement something. The second one, and I think one of probably the biggest ones from a data reward, total reward perspective is the data quality and quantity. Now without large volumes of quality, H- Quality data, Gen AI can't produce high quality results. So generative AI models are trained on vast amounts of data and the quality and the quantity of this data directly impacts the performance of the model. So companies often underestimate the amount of high quality data needed to train these models effectively and investments will be needed in keeping your data clean and accurate. Thirdly, there's the ethical and legal considerations. You may need to kind of work with your risk and compliance teams to steer clear of those types of issues or any kind of copyright infringement. For example, we know Gen AI can create new content that seems human-like, which raises a whole host of ethical and legal issues. For example, if Gen AI creates a piece of content and infringes on someone's copyright, who's legally responsible? So companies have to struggle and navigate those complex issues. And lastly, bias in AI and large language models. AI models can unintentionally perpetuate and amplify existing biases in your data that are trained on leading to AI outputs that can be biased or discriminatory. So it kind of goes with the second part here is that you need a lot of high quality and quantity of data. So but even with guardrails in place from developers, some tools can still perpetuate these biases requiring the need to keep humans in the loop to catch and resolve those issues.

[00:43:00] Jayna Koria: But let's move on to a case study. So keeping some of those additional considerations in mind, and let's say we can overcome some of those limitations and struggles, we definitely know the use of AI does allow for transformation. And with transformation comes opportunity. So here's a real life example of a case study. One of the world's most established technology companies recognized that to stay competitive, they needed rewards not just for... performance, but future skills. Historically, their salary reviews process was very time consuming and narrowly focused on performance and market benchmarks. I guess for most of us on this call, that sounds pretty familiar. So they built an AI agent to kind of augment that or change that. Now, this AI agent was able to analyze real-time data to recommend pay increases is. Not just based on performance, but based on development of new skills or future skills. And it even provided a script to help managers have more meaningful conversations about pay and growth. The result, a faster, fairer and more strategic process promoting growth. So the rewards team then shifted from being kind of administrators to enablers of business growth. And this is what we mean by turning your rewards function into a driver of strategic value. But let's be real. This kind of change doesn't happen overnight. While in this case, the client did build the AI agent themselves, they were a technology company, but even before they could start on the build, they needed to ensure the inputs and foundational information being used was available and accurate. to allow for the transformation of such a critical process. So leveraging AI and ensuring we do not succumb to some of the pitfalls we mentioned earlier, honestly, just getting organized is a journey on its own. And for those of you that have been through this, we know it takes time and resources. Continuing with the example of the tech giant, that actually ended up being a two-year journey that Mercer supported. This meant ensuring that jobs were categorized and coded, job descriptions and job valuations were up to date, with consistent salary ranges and individual pay levels that were equitable and bias-free. So as I mentioned, for those of you that have been on this journey, and we've done lots of engagements with clients, this is typically at minimum a six to nine-month. project. And if you're a large organization, it can be years. But without this structure, it's impossible for companies to make sound investment decisions in their human capital, hard to enable career progression, remain competitive and compliant, and control costs and manage workforce agility. So going back to that survey that we conducted in March, on the effectiveness of HR on total rules function. We asked, what are the key activities that typically are completed by the total rewards team within an organization? Now, what the blue is, whether they answered yes to an activity and the purple is no. Now, you probably blinked and you missed that those blue bars changed into pink bars, because I just want to highlight these four items. So regarding kind of where the total rewards function spends a lot of their time. The survey showed us that, you know, over 85%, nearly 90% of organizations spend a lot of their time on market compensation analyses, job evaluation, annual compensation processes, which I'm sure a lot of you are keeping busy with right now, and compensation survey responses. So we can see that leading organizations are really starting to leverage AI for much of that work, potentially saving you hours each month. So this is what we mean by that kind of strategic shift where we can leverage AI. Mercer's research shows that 50% of your job can be automated. Now, that's an opportunity, not a threat. Think about the problems or opportunities you could tackle if you had that extra time. It's all about leveraging automation or AI to focus on higher value tasks and strategic initiatives that can really make a difference for your organization. So I want to kind of discuss an interesting email that we got from a rewards leader recently. They reached out with some personal insights. They themselves had been experimenting with chat GPT to generate compensation analysis. And we're finding the results to be good enough. But what really stood out next was what they said next. They said, I'd much rather to stay within the Mercer ecosystem. And with all the data that you have access to, be able to have a one-stop shop for job descriptions, pricing insights, and so on. So I think they heard us. Because what I want to talk to you about next is some of the things that Mercer is working on with respect to helping AI in your day-to-day jobs.

[00:48:00] Jayna Koria: So I want to introduce the next generation of Mercer's what we call intelligent job solutions. Ignited with AI, delivering output faster. So our once manual job description solutions are now enhanced by AI, removing some of that heavy lift. But what we've learned earlier, without that high volume of high quality data, Gen AI can't produce high quality results. And one of the things that Mercer has is that we have one of the most comprehensive databases in the world. Again, I can't emphasize AI is not going to solve all your problem, but with job matching, job description writing, job evaluation, AI can be that first pass at the work. So oftentimes, like I akin this to not starting with a blank piece of paper. AI can help you get started on that journey with support with job descriptions. So we're going to just show you some of our solutions that we've been working on. So we have AI Ignite job descriptions. And some of the key features is ability to take some of your client information, such as your industry, your location. And with some prompts, you can produce job descriptions that are pretty much high quality and even customized. It has the ability to kind of interact with you and steer some of the outcomes. And it can learn from, you know. As you start doing this more and more, it can learn and it can even use specific custom templates in the future. Now, I will emphasize these are all in testing mode right now. So nothing is actually available. But what I'm trying to do with this discussion is just open your eyes to some of the options that you have. Now, again, Mercer is working on these solutions, but there are some other things that you can probably do right now even. And now another solution that we have is matching your jobs to the surveys. Now this takes a lot of time for many of your organizations that are going kind of through that year-end process where you're having to manually match your jobs to compensation surveys such as MRSA's benchmark database. So what this allows you to do is automate some of that that heavy lifting let's say. It can take things such as your job titles, your job descriptions or a whole bunch of skills and help you provide high quality matches on those survey jobs, survey options that you have. So gone are the days where you're kind of reading through capsules of descriptions, trying to match your description with the survey description. This can help you take that first pass based on just uploading a whole lot of information. And last but not least, one of the other things that we're working on is an automated job grading based on Mercer's IPE system. So Mercer has their own job evaluation solutions, and it can help you with that kind of first pass at trying to help with grading your jobs. So hopefully some of you have been starting to think about these things of how to implement AI into your day-to-day total rules life. But I know as a compensation consultant, when I found out that we were going to get access to some of these tools, I was pretty ecstatic. Because honestly, writing job descriptions and doing job evaluations is not the most interesting start of part of our jobs either. But as I mentioned, and just maybe keeping with the ducks analogy that Stefano had, before you can start any of this stuff, you really need to get your ducks in a row. And again, Mercer can help you with that AI solutions with all these infrastructure of job description, writing, job evaluation, and market benchmarking can help you on your AI journey. We're just getting starting on this. And I'm hoping to hopefully in the next few months be able to provide more of an update or you can get some updates from Mercer on how these AI tools will help you. But what are some of the things that you can do right now? And I think one of the things that we're suggesting to most of our organizations are developing that AI rewards roadmap. So the three things that we're kind of saying right now is identify specific tests and learn use cases for your organization, upskilling your data literacy for your rewards team. And again, making sure that your data is robust and bias free. So again, we're developing some of the tools to help you with that. But in addition, we've got some other complementary tools that you can do. And we'll send, as this deck comes out, there's a couple of other things that we want you to be aware of to help you build your own roadmap on how you can integrate AI into some of your rewards functions. So we have a rewards revolution point of view that you can download on the link there. But I think what's more important is that we actually have a rewards transformation assessment. And this is really a diagnostic. It has a whole bunch of questions and it will help you understand kind of what are your strengths as a total rewards function? What are some of the areas that you could develop in? And it can help you build that roadmap. So those of you that have a phone handy, you can kind of click on that QR code and download these tools right now. Or you can wait for this deck to be sent out and we'll help download some. These are complementary and they're just going to help you with your AI journey. So I hope I was able to kind of open your mind to some options that will help. We've all been asked about how can we implement AI into our jobs. So this gives you some food for thought of how you might want to implement AI into your day-to-day total rewards functions. So that's all I have time for right now. And I'll open the discussion up for some question and answer sessions. Take us forward.

[00:53:00] Mallory Hendry: Absolutely. Thank you, Dana. We have a few questions here. Stefano, someone is wondering if you have some of those numbers that you were showing us earlier, excluding the salary freezes.

[00:53:20] Stefano Biscotti: Yeah, I'm happy to take that one on. And thanks for the question, everybody. So what we had said was for those that the numbers that we projected, we had 3.2% as the total increased budget, which included those organizations that were contemplating not having a cycle. That when you remove those organizations from the value becomes 3.3%. The merit budget was 2.9, removing those values brings you to 3%. So not a lot of variability. And so this theme of being, you know austere and conservative is following trend on this as well.

[00:54:00] Mallory Hendry: Okay, that's great. Thank you. Jayna, maybe you can take this one. Someone's wondering if most organizations would consider job descriptions to be confidential information. So are there risks in feeding those full descriptions and corresponding titles into a Gen AI platform?

[00:54:20] Jayna Koria: I personally don't think, unless there's specific company information that you're tagging along with your job descriptions I don't personally think they would be considered confidential information. Obviously you want to take your name out of those things, but that's why again you might want to go with a consultant option that has that kind of privacy built in for you. But if you're going to use something like a chat GPT just be careful of what you're feeding in there, make sure it doesn't have anything that can be personally identified to your organization. But generally speaking, I've not heard of a job description being kind of confidential information.

[00:54:50] Mallory Hendry: Makes sense. Thank you. Someone else is asking the AI products that you guys were kind of teasing there. When will they be ready? Or is there some timeline there?

[00:55:00] Jayna Koria: Yeah, no, great question. And like with most things, everything is in the testing phase right now. So it all depends on how testing goes. The latest that we have heard on this is going to be at least the end of the year before anything gets released. We start releasing some of our AI tools, none of the ones that I've shown you today. But if you are a Mercer client already, as part of our, some of the surveys that we already have, there are some AI products being released. But these three that I've shown you right now, and I know they're really utmost interest of so many of our clients, they are going through the testing phase right now. And the latest is kind a Q4. So I would say. I know technically we're kind of getting into Q4 or we're into Q4 right now, but let's just, I would say kind of more near the end of the year.

[00:55:45] Mallory Hendry: All right. And I think we might be able to squeeze in a few more. Stefano, back to you. Are those projections for the U.S. similar to those of Canada?

[00:55:55] Stefano Biscotti: Thanks for the question, Mallory. And so, yeah, not too far off. So comparatively speaking, when we're looking at the merit budget, we in Canada have a national early value of 2.9, whereas the U.S. is 3.1. And from a total budget perspective, we projected based on survey responses 3.2. And by the same token on the U.S., it's 3.5 at the moment. Again, very preliminary numbers that will be refined between now and the end of the year.

[00:56:25] Mallory Hendry: Okay. There's one more here. Can you remind us how the merit and total increase budgets differ?

[00:56:30] Jayna Koria: Right. So your total increased budget includes the merit budget, includes promotional adjustments and any pay equity envelopes that you might set aside to make equity types of adjustments within your organization, whereas your merit budget is really tied to merit increases.

[00:56:45] Mallory Hendry: All right. Okay. Well, I just wanted to say thank you so much to our speakers for sharing their expertise with us today and to everyone in the audience. Audience for being here with us as well. Keep an eye out for more upcoming webinars and enjoy the rest of your day, everyone. Bye.

[00:57:00] Jayna Koria & Stefano Biscotti: Thank you.