Make an Impact on Frontline Worker Safety

00:00 

Hi everyone. Welcome to today’s safety and health webcast. 

00:09 

We’ll start the presentation in about one minute. Thank you so much for joining us.  

00:20 

Hello everyone. 

00:39 

Thank you so much once again for joining us, just to let you know we’ll start the presentation in about 30 seconds.  Hello everyone and welcome to today’s Safety Magazine webcast, Frontline Impact, Engaging EHS Teams in Advancing Safety with Practical AI, sponsored by Benchmark Gensuite. The sound Ferguson, my associate and editor at Safety Health magazine and co-host the on the Safe Side podcast, and I’ll be moderating today’s event.  

Thank you once again for joining us. Before we get started, there are a few housekeeping items as a disclaimer, the views of today’s speaker and organization are their own and do not necessarily reflect those of the National Safety Council or Safety and Health magazine. Any mention of a commercial enterprise product or publication does not mean the Council or the magazine endorses those items. After today’s presentation, we’ll conduct a question and answer session with our speaker. If you have a question, click the Q and A button at the bottom of your screen, type your question and press the send button. We welcome your questions at any time during today’s event, you don’t have to wait for the Q and A to begin. We might not get to every question, but the good news is unanswered questions will be forwarded to today’s sponsor. Also after this presentation, you will be asked to complete a brief evaluation survey, and I’ll tell you more about that a little bit later. And just to let you know, this webcast will be archived so you can access it after today’s live event. To view this webcast and all of our past webcast, please visit Safety and Health magazine.com events, or you may also receive a link in our post event email. 

02:27 

With that, let’s introduce today’s speaker. With us today is Donavan Hornsby, Chief Market Strategy Officer at Benchmark Gensuite. Donavan has dedicated the past 20 years of his career to advancing EHS and sustainability principles and best practices in the industry at Benchmark Gensuite, an industry leading digital platform for EHS and sustainability programs. Donavan provides strategic directions for global business and market development as well as product leadership and innovation. And in addition to organizational leadership responsibilities, he’s an active thought leader and member of cross industry efforts to advance and promote best practices within the EHS, sustainability, and ESG industries. Donavan, whenever you’re ready, go ahead and take it.  

Thanks, Alan, appreciate it. Hopefully you can hear me all right. 

Welcome everybody. Appreciate the opportunity. Alan, thank you, and thank you to the NSC organization. I certainly admire the great work that you all do as a greater team. I’ve been involved with your efforts, some of the initiatives around work to zero and MSD, prevention and elimination, and certainly appreciate the opportunity to join folks today and share with you all a little bit of a view to frontline impact, as we called it here, and some of the work that we’ve been doing with our community around technology to help advance the safety practice and programs within your organizations. I imagine some of you on the phone right now may be familiar with us. What I’d like to do for those that may not be is to give you a little bit of background on us and then launch into some of the themes and discussion items I had planned to share with you today. Just a heads up too, I’m based in South Carolina near the coast, and much like others in the South Carolina and North Carolina and Tennessee areas, we’ve been experiencing some intermittent service interruptions and such. So, if for whatever reason, my internet drops during this this hour here, I’m going to rejoin by my phone. So just give me a couple of minutes, I’ll ask Alan to fill the space with some questions and Q and A and such, but hopefully won’t have to worry about that. But just in case, if I go silent, it’ll only be for a couple minutes before I’m able to rejoin.   

So just a little bit of background for those of you that maybe may not be familiar with us. As Alan alluded to there, I’ve been working in the EHS and sustainability space now for the greater part of my professional career, 20 plus years, and a lot of that time has been spent working with organizations like yours to help advance what you’re trying to do from an employee, safety, health and safety, environmental stewardship and sustainability standpoint, and the way that we do that really is by partnering with folks like yourselves to, as we say, operationalize EHS and sustainability within your your programs and activities there, and we do that through a best practice based software, enterprise software solution, complimented by some various technologies, some of which I’m going to get into today here.  

So hopefully that’s a helpful little bit of background and context for who we are. And as you can see on the right-hand side of the screen there, our bread and butter is in EHS and sustainability at the top of the wheel there. But we are helping folks in other functional disciplines, like quality, supply chain, risk, product stewardship, and most recently, helping folks address issues like CSRD and other types of ESG disclosures, voluntary or otherwise. And so happy to spend a little bit of time digging into a little bit of this with a focus on frontline worker and how we’ve been working with our community over the past few years to help apply some advanced technologies, including AI, to do that. So that’s a little bit of background on us.  

06:26 

I thought I’d start today, I was actually just at Tennessee Congress in Orlando a few weeks back. I guess it’s been two or three weeks at this point, but I, like some of you that may have attended that and or may have attended safety seminars and sessions over the years, I attended a session where speakers had kicked off things with a conversation around blue line, black line. Many of you that have been working in safety space are familiar with this concept, where really the goal and the challenge has always been to address the gap that is inherently there between the expectations that we have as corporate leadership, as an organization, and what actually happens on the shop floor in the field, both from an operational standpoint, but also from a safety standpoint, obviously, and it’s finishing sitting in on these conversations over the years, this is a concept that’s been around for a long time. 

07:18 

What I’d like to share with you today is that I think we have, probably more than we ever have in the past, a great opportunity to close that gap. And when I say close that gap, you know, I think sometimes when people talk about blue line, black line, we often spend a lot of time figuring out ways that we can actually influence the blue line, which is, as you can see, my graph here, is really the performance there with respect to, you know, the expectation, or, you know, work as imagined or as expected there on the shop floor and in the field. And I think sometimes what we run into or forget, perhaps, is that oftentimes closing of the gap requires us to influence the black line as well, and so that’s one of the things I’d like to talk about today and talk about that through the lens of process improvement and technology to help close that gap. So that’s the basis for the conversation today.  

What’s kind of been working in the background here, as I’ve kind of titled here, some of the kind of recent trends and shifts that we’ve seen both from a regulatory standpoint as well as a market standpoint, and then how technology has become to influence that is really the basis for, I think, what is a huge opportunity for us to start kind of changing the direction of what we’ve been doing for the past couple of decades. Now, I think we’ve obviously as an industry, as a group of EHS professionals, have greatly influenced the performance, safety performance of our companies and organizations and our teams. But there are still some challenges that all of us face there, whether it’s closing that gap between expectations and reality on the floor or with when you talk about things like significant incidents and fatalities and such, these are still issues that plague us and haunt us and really the reason why NSC, through their work to zero initiative and other organizations have been working deliberately and aggressively to identify things like new technologies and help us get at that, because it still continues to haunt us in many ways. 

09:27 

The other thing that obviously has been around for a long time, this is nothing new, but you know, we certainly have seen this over the past few years, is this gap in terms of resources and talents 

representing EHS and safety specifically within our operations there. 

09:46 

And so, any way that we can accelerate folks learning and experience in order to, you know, take, but I’ll talk a little bit later, you know, the 30 year career of a safety veteran being able to take that insight and that experience, and embed that into the operations of the company, and also enhance the experience of our younger folks that are coming into the space. The more that we can do there, the better our processes are, and operational changes can continue to grow in complexity. 

10:20 

One interesting thing that we’re also seeing is supply chain, whether it’s through regulatory activity coming out of Europe and in other regions like CSRD, supply chain, whether you’re talking about suppliers within your value chain or contractors that may be coming on site reform, a lot of the expectations for performance are being pushed to those groups. No longer are we focused within the four walls of our operation, but we’re having to spend a lot more time within the value chain, as well as with our contractor communities.  Where we have shifted some of the operational burden from our direct employees to those folks in those populations, it increases, obviously the risks and our ability to influence is also challenged. And so, for these reasons and many others, we’ve been looking at and continuing to work at technologies that can help address this more directly. 

11:19 

You know, AI, I’m not going to, this is not intending to be an AI educational session at all. I think everybody’s been following what’s been happening over the past couple of years now with AI and in particular Gen AI.  Some of you may have already been have experimented with things like Chat GPT and others to perhaps write better emails, or perhaps do a little bit research on how you can address certain aspects of your programs.  Kind of digging into the wealth of knowledge that sits out there and some of these large learning models or databases and such. 

11:51 

And you know, certainly, I think we have a tremendous opportunity. I spoke at some the NSC events over the past year, at the future of EHS, and have in the past about some of the work that we’ve been doing over the past five or six years around AI, and it’s been interesting to see how that’s progressed. And I think, you know, AI is a pretty massive topic, pretty, pretty broad in terms of the different types of technologies.  

And so today, I’m going to talk a little bit about applied AI. I think the challenge that we always have with AI is that I think some folks become paralyzed by the concept and thinking this is such an advanced thing, you know, I’m just trying to get the basic building blocks in place in terms of my safety program or sustainability program and my sites. I don’t have the bandwidth to be thinking about things like AI that seem like this kind of newfangled shiny object, and it’s not necessarily practical. The reality is that AI is very practical, and I’d like to share with you a few examples of that today, starting with some things that I think folks can embed into existing processes that you have all the way up to some things that perhaps are a little bit shinier object, little bit more sophisticated but are certainly accessible to anybody.  

I think that’s one of the messages that I want folks to take away from this, is that some of these technologies that I’ll talk about today are not the purview of just large, sophisticated organizations with a ton of resources. We have organizations within our community that are quite small, that are starting to apply some of these technologies, so it is available to everyone, any type of organization, no matter the majority of your program level, sophistication or lack thereof or resources, is there, and I’m here to share with you some of the examples of that. 

13:46 

So, at this point, I wanted to launch a quick poll question, just to get folks kind of engaged and warmed up here. So, if you can take a look at that, and we’ll just give a minute here for folks to respond, and then take a look at the results, and then we’ll continue on. I think we might have a little mismatch between our poll question that we screen here in my PowerPoint deck, versus what’s actually displayed online here. But if you can go ahead and address the one you see there within your poll question, that’d be great. 

14:39 

And we have results back. Very interesting. So, the question was, how’s your organization’s investment in AI for EHS changing in the next 12 months? 

14:48 

Still, some folks that are trying to figure things out. Not surprisingly, there are some folks that are still on the sidelines, I’ll say, waiting to kind of see how this plays out. But for those that have started to make a move. The investment is growing, and I think that’s pretty consistent with what we’ve seen within our community, for sure.   

15:00 

Continuing on, so, a little bit of additional background. So, you know, obviously, we’re going to talk, as I alluded to there, about some advanced technologies and some very simple, practical examples or applications of those advanced technologies. But I think it’s important for you all to understand a little bit more about the context for our solutions and the technology and how we’re coming from this and how these technologies complement it. And so, if you think about just typical workflows, processes within you know many of your EHS operations, you obviously have things like incident management workflows where folks are, you may have out there supervisors that are logging incidents or events, or you may have folks out there that are logging good catches or concerns or observations that then flow through some type of workflow.  

Whether or not you digitize that or not, it’s following some type of workflow. And that’s the type of thing that we have been doing for many years now, where folks are logging incidents and observations and concerns or good catches, and it flows through, and it brings in folks from other functional disciplines, like maintenance, for example, to address issues and carry out and follow up on action items, all of that flowing into, ultimately, some type of analytics or reporting or insights that you can then, hopefully take and then understand where you need to spend your time. So very simple, typical, kind of standard process.  

The other thing at the top of your, top left of your screen there, that I wanted to talk about is a little bit of context for what I’m going to share next, and that is perhaps a deeper level of frontline engagement. So when we talk about frontline engagement and frontline workers and such a lot of times when we’re talking about safety programs that might stop at your supervisors. It may not engage folks that are out there actually getting the work done, working, you know, in field service, providing, you know, maintenance or performing some type of activity on the shop floor and in the field there.  

And so, in many ways, we haven’t necessarily gotten to the true front line. And, you know, obviously, when we talk about things like closing the gap between expectations that we may have and the actual performance and actual work being done, in some cases, we may not be getting close enough to the work, and that’s really the message here, part of the message here. And so how do we get that? And some of you may have, and certainly in cases where you have field service operations or perhaps construction project type work that you’re doing there, you may have some folks that are doing, you know, tailgate talks.  

17:55 

You may have pre startup, you know, job pre startup, safety type reviews. These are the types of things I’m talking about here that I’ll talk a little bit more about, about getting closer to the front line and really looking at ways that we can embed safety and what’s in actually the work being done there, again, not as not safety as a separate exercise, but safety as an embedded part of the work that we do. So, with that as little bit of context, wanted to share with you, kind of my first introduction into some of the technology that we’ve been working on.  

18:29 

So, for many, many years, we have been investing in mobile technology.  And I mean, this goes back, I’m dating myself. It goes back to the days of Pocket PC. If any of you are old enough to remember that you know it goes back a very long time. And those were the early days of mobile use, and obviously, over the years, mobile became ubiquitous, and it’s everywhere now. But the reality is, as many of you know, and maybe you’re facing this within your own organizations, there are still folks that aren’t using mobile to do things like carrying out observations, or providing folks an easy way to log good catches or concerns, and you’re still perhaps waiting to go back to computer or a kiosk to log that in, and not necessarily capturing that at the point of action. 

19:16 

And even in those cases, I would say that we still have been challenged. Some of you that maybe have tried, you know, launching mobile within your organization to help fully digitize some of these processes and simplify them. I don’t think we fully crack the nut in terms of simplification, because there’s reasons why folks still choose not to do it, and they wait at the end of the day to come back and report out on something. And it could be because perhaps the forms that you have within your mobile devices are still too complex. Maybe they’re too small. There are all kinds of reasons from a form factor standpoint and usability standpoint, things that are getting in the way.  

20:00 

Or it could be that the nature of the information that folks are trying to capture, again, is too high level, too complex, you know, too much, perhaps. And there are still opportunities, in many ways, to simplify that. And so this, this is the first thing I want to share with you, is some of the work that we’ve been doing over the years, and certainly, most recently, to really look at greatly simplifying that so that what you’re doing on the front line is truly reflective of the work, and actually embedding safety considerations into the actual work that’s being done.  

So when you have folks that are getting ready to start a job, and they’re looking at that job and kind of going through the work instruction and doing that kind of pre job review there that the safety considerations are just embedded in the nature of that work, and that’s the type of simplification and embedded safety approach that I think we all need to get to, but still is lacking in many organizations from what I’ve seen. So, without a little bit of background, I wanted to maybe start launching into a little bit more around AI. And so, we have been, over the past few years, looking at and approaching AI from three perspectives, as you see on the screen here.  

One is front line. How do we engage folks more effectively?  How do we capture information that’s better quality, more robust, something that’s more useful for us downstream as we look to make decisions and perform analytics and things like that. Because that’s oftentimes, you know, one of the big issues we have.  

But then also, how do we present information to folks on the front line that’s helpful in their job, insightful? How do we present them with, you know, real time, micro learning, for example, so that they’re not trying to remember something they learned a month ago or before they went on the job. Or they can actually use it, utilize it right there on the spot, at the point of action.  

The second middle piece of it is, how do we take information that may be available to us and start performing some diagnostics, some analysis on that using AI.  

And then lastly, and this is ultimately what many of you perhaps are responsible for, is how do we start informing decision making better, informing decision making through the use of AI? And this is probably where some of you have started, maybe dabbling in the use of AI is taking some of your information and trying to derive insights from it that maybe weren’t possible without AI, because either the volume of information is that great, or perhaps you know, your perspective on it is biased in some way as an organization, and you need somebody to come at it and look at it through a different lens, if you will. So, these are the kind of three areas that have been guiding our AI strategy.  

22:51 

So, at this point, before I jump into some demos and demonstrations here, we’re going to launch another poll question.  And so the poll question is, which of the following AI use cases would be the most valuable to your EHS program, and select all that apply. And so, we’ll give time here for folks to respond, and then we’ll see the results pop up. And apologies, I have this mismatch between my slides and what’s actually being launched in the polls here, but hopefully you’re able to see the poll question itself.  

23:40 

And here’s our results. So, the question again was, which of the following AI use cases will be the most valuable to EHS programs, and hopefully some of you have started playing around with some of these use cases, but it’s quite evenly split. Looks like our front runner is applying automatic updates to regulatory contents. Close second is prompting users to improve inputs, and I’m going to share with you an example of that, and we have a few others, AI powered video analysis. I’ll share with you an example of that, and some trending and charting. So, it’s great, great to see that we have some folks kind of working evenly balanced across all these use cases. 

24:29 

All right, so for my first demonstration here, I’m sharing with you again, this is really getting at the question of, how can we improve the quality of information that we’re capturing on the front line from folks. And you know, one thing that we’ve been doing, and again, this is an example of a very simple approach. AI ironically, when we first started working with AI was probably about six years ago in this way, and we, and I’ll share with you an example of this here in a few minutes, we started working on pieces, so potentially significant incidents, fatalities, and we did some work there, analysis, work that I’ll share with you later, only to realize later, through that work that you know really a lot of this hinges on getting good information, good description, descriptive, narrative type information on the front line so that the work we do downstream is more impactful and more insightful.  

And so, this is kind of we kind of recalibrated in terms of our focus on trying to improve the quality of the information that we’re capturing on the front line. So, this is an example of this, and I’m just going to kind of let this run through here. So, this is an example of a form here, an input form where folks can log a good catch or something like a near miss or concern that maybe they have observed out there on the shop floor and in the field. And so, what you see happening right now is we are applying some AI to assess the quality of those inputs, and now we’re utilizing some Gen AI to help influence and improve the quality of that input so it’s much more descriptive that you see here in that example, and suddenly, now we go from a not so great description of what happened and what we observed to something that was certainly much more useful. And so super simple application of this. You may have used similar things like this and other aspects of your life or professional life here, and this is one example where this is super simple to deploy, and something that you can embed into pretty much anything you do in terms of a digital workflow to help improve information. 

26:54 

And so, my next example is really around a more advanced application of this. And so this is actually some work that we’ve been doing with one of our strategic partners, through 3motion AI, we actually just hosted, I think it was yesterday, a webinar where we had some of our friends from Boston Beer, who are is one of our subscribers and customers within our community, who have been working with us to really improve their ergonomics program there, within their operations. And so, you know, for many years, we’ve had an ergonomics assessment capability within the solution, but a lot of that has hinged on having Ergo experts visit your sites and walk around and observe people in the course of their work and makes those observations and assessments and then share feedback and things like that. And as many of you know, ergonomic experts are not everywhere and they’re certainly not everywhere you need them to be. And you may only have a couple of those folks on staff, and they certainly can’t spend time at every single site or operation that you might have. And so how do we address that?   

And so really, that’s kind of like the genesis for some of the work that 3motion AI has done out there, and certainly the basis for our partnership. So, what we’ve done here is embedded 3motion AI’s video analytics capability analyzing folks in the course of their work and providing feedback and assessing that work in real time, if you will. And so, they have both a real time capability as well as kind of a, you know, near real time capability that we’ve embedded into our ergonomics assessment solution here. And so, I’m going to let this kind of play through and just provide a little bit of narrative this as it goes through. 

28:51 

And so, this is our Ergo Evaluator solution here, and you’ll see me click on the video evaluation. And so, what we’re uploading here is just a video of someone unloading some boxes from a box truck onto some rollers there. And as you can see here, the video is analyzing different points, and then what comes out of that is a score. And again, this is, you know, one approach to it, but there’s certainly lots of different ways that you can slice the pie and analysis can be based off of different models and such. But what we’re doing here is generating a summary of that assessments based off this video analysis, and then that’s flowing into an assessment score that follows with some recommendations on where folks perhaps need to be spending some time. And that may be an introduction of some new controls, or, you know, some things that you can do within the process. It might involve some training with folks. But either way, you can only imagine how much quicker this is than to try to have your one Ergo expert spread around the various sites and operations you might have so you’ve essentially taken that and democratized that expertise, to some extent, at least to a point, across your operations, very quickly and easily. 

30:22 

And so that’s leads us into what I kind of touched on, the hint of that a little bit earlier, deeper, more sophisticated looks at risks. And so, as I as I touched on earlier, we started work around potential SIFS and PSIFS about six years ago or so at this point, I think. And a lot of that grew out of as you see in my slide header there, there’s only so much that even our most seasoned safety veterans can draw when they’re looking at huge volumes of data. And I think there’s also this tendency within organizations to look at information based off that experience. And oftentimes, I think we suffer from some blind spots, and that’s really the promise of this whole thing.  

And I think the promise of using some of this type of AI technology to work against these volumes of data, is that it unlocks an ability to not only process huge amounts of information, but also bring in other sources of information. And so one thing that we’ve done here was, we’ve combined information sources that are coming from our subscriber communities, and this might be in the form of observations, good catches, incidents, other types of operational information that you might have flowing in that might be good source of information on the basis for the insights, but then also marrying that up with publicly available information that might come from OSHA, other types of knowledge bases, if you will, that we can incorporate and AI can act on all those volumes of information to start helping you identify and uncover what we’re calling here, hidden risks, risks that may not be obvious to you, or perhaps for a host of reasons, but also, not only the risk, but also precursors to that. So, giving you a little bit of a heads up on things, conditions, behaviors and such that might actually be a precursor to an incident.  

And so, so really, that’s the kind of basis for the work that we’ve been doing here. And so, what I’m going to share with you, and I think this will be my last example on terms of demonstration here, is a look at our Incident Management module here, where we have embedded this, what we call our PSI advisor. So, this is an embedded AI that allows the tool to take a look at information that may be captured. So, let’s say you have a near miss or something like that, that somebody’s reporting in here, being able to run that through our model, and to make a recommendation, first of all, as to whether or not this should be perceived or seen as a potential SIF, and then also providing some basis for that determination. And obviously, through the course of that, then you start gathering some interesting information around precursors and things that will then give you an idea about where you should best spend your time in focus.  

33:36 

Let me kind of let this run here, and I’ll provide a little bit of narrative as this go through. So here we’ve captured a description of the incident and what happened, and we’ll start, you know, doing some quality insights and guidance on the response. Now we’re making a determination based off of the PSI Advisors recommendation on as to whether or not this was a potential serious incident. 

34:02 

And as it’s working through that analysis there, then we provide a basis for that determination. And as you can see here, we’ve done some checking against information that you might have available within your databases, information that we have available across our kind of broader database of information, including publicly available information, and what comes out of that is a much better insight or understanding of risks. And those risks might be hidden risks that maybe may not have been revealed through the course of your analysis, but also a sense of some of the precursors that might lead to this. And so, this is an example of the types of analysis that might come out of that. And so, you know, prior to this type of technology, in this approach, you may have been looking at a list of risks and precursors, but perhaps there wasn’t a great, solid basis for the work that you’re doing. 

35:00 

So, this really challenges that, and it’s interesting, because obviously this is a model that we have been working to perform or to perfect and improve over time based off additional information, always with some folks that provide some expertise. Many of you on the phone maybe have worked with this type of technology, and you’re also helping the model to learn by applying your own experience and insights to this. So, this is not something that necessarily sits alone and where you put 100% confidence in but we certainly, I think, reached a level of confidence at around 90% with this, you know, based off of the work that we’ve been doing over the past few years. So, it’s a great start, and I think a lot of promise moving forward. 

35:41 

So, at this point, I’d like to go ahead and open up our last poll question, which will probably not match up with what I have on the screen here, but we can get that last one, and we’ll give folks a minute to respond.  

My apologies. Donavan, it looks like we’re having an issue with launching that poll question there.  

That’s no problem, we can just move on from that. And if we have time during the Q and A, perhaps we can launch it. So really at this point, Alan, Barry, I just wanted to kind of wrap things up for folks. Hopefully this has been helpful to you. 

36:33 

You know, I think when we talk about frontline engagement, frontline worker engagement and impact and things like this, you know, this is not a new concept. I’ve been in the space now for 20 plus years, and many of you that are on the phone perhaps have been as well, perhaps are new to the space, new to the industry. 

36:51 

But this is, you know, it’s so critical. Because, as many of you probably know, I certainly know from my experience, you can have the best processes in the world.  You can have the best programs in the world. You can have the best technology in the world, but unless you can get folks engaged in a meaningful way on the front line and help them do their job more effectively, embed safety is just a natural part of what they do, and not a not an add on, unless you’re able to do those things, all the other things don’t matter.  

You know, really the success of our programs, whether they be safety programs or sustainability programs, really depend on getting good, solid engagements from the front line and being able to help those folks do their jobs more effectively without being in their way.  

And that’s really what this is all about, you know, as we think about these concepts and these challenges that we’ve had for a long time, closing the gap and expectations that we have as an organization, or how work should be performed in the actual reality on the floor and in the field, what I’ve shared with helpful, and look practices for helping you do that.  

I mean, ultimately, I think, as I shared earlier, we have to keep things, make things as simple as we possibly can for folks on the front line, otherwise they’re not going to do it. You’ve seen it many times before. We’ve all seen this movie many times before. And so whether that’s presenting them with a technology that greatly simplifies what they’re doing and doesn’t get in their way in terms of form factor and usability and things like that, but also from the terms of content providing them, perhaps, you know, things like micro learning that they can utilize real time as they’re performing their work and capturing that information in a super simple way that’s not getting in their way. I think we can go a long way to really gap and again, as you see in my kind of bottom line there, that we’re trying to do.  

Let’s get that last poll up there on your screen. You can see our third question here, will your organization prioritize AI solutions that incorporate Gen AI capabilities in the next 12 months?  

39:37 

And we’ve got the possible responses there. Yes, I didn’t realize Gen AI was being leveraged for EHS, no, we’re just focusing on AI and other emerging technologies. We’re not prioritizing any tech solutions the next 12 months or I’m not sure. So, feel free to go ahead and answer which ones apply to you. Appreciate your responses. 

 40:00 

There, and we’ll let that run for just another few seconds here. We’ll let everybody respond, and we’ll see if we have Donavan back on the line here. 

40:34 

Okay, we’re going to end that poll and share the results with you. 

40:40 

And it looks as though our leader is, I’m not sure, 31% and the second one here we have, we’re not prioritizing any talk solutions in the next 12 months. And then again, I didn’t realize Gen AI was being leveraged for EHS, 26% so Alan, I’m going to toss it over to you before we get as I stop this poll.  

41:20 

Thank Donavan for his wonderful presentation first of all, and for sharing his insights with us. And before we start the Q & A, we want to remind everyone of the evaluation survey we’re asking you to complete. This survey will open in a different screen after this webinar, and your input is important because it does help us improve our future webcasts. And once again, if you want to ask a question while we get things sorted, if you could please click the Q and A button at the bottom of your screen, type your question and press the send button.