3122: How Panasonic Connect Is Empowering Mission-Critical Workforces with AI

[00:00:04] How can technology revolutionise the way mission-critical industries operate, from law enforcement to utilities and so many other different industries out there?

[00:00:16] Because I think as expectations of today's tech-savvy workforce continue to evolve, the need for advanced, efficient tools has never been more pressing.

[00:00:26] And in today's episode of the Tech Talks Daily Podcast, I'm going to be joined by Dominic Passadante, Vice President of Mobility at Panasonic Connect North America.

[00:00:38] And together, we're going to explore how AI and cutting-edge technology are transforming essential industries.

[00:00:46] And my guest today, he's going to be sharing real-world examples of how tools like Panasonic's AI-enabled Toughbooks

[00:00:53] are helping industries streamline workflows, improve responsiveness and enhance worker safety.

[00:01:00] From reducing the administrative burden for first responders to optimising utility operations and even analysing weather patterns to prevent wildfires,

[00:01:11] these innovations are reshaping what's possible in mission-critical environments.

[00:01:17] And anybody that listens to this show on a regular basis will tell you this is the kind of stuff that I absolutely love.

[00:01:22] Getting myself and everybody listening thinking differently about all these far-reaching areas that technology is impacting.

[00:01:29] And we'll also address the broader implications of AI in the workforce, including the role in bridging staffing gaps,

[00:01:36] meeting the rising expectation of tech-savvy employees.

[00:01:40] But most importantly, how AI is complementing human expertise rather than replacing it.

[00:01:47] And hopefully, we can dispel some common misconceptions and myths about integration of advanced technologies in these essential fields.

[00:01:57] So, could technology be the key to solving your industry's most pressing challenges?

[00:02:02] Let's get Dominic on now to uncover the future of mission-critical workforces and their evolving relationship with AI and innovation.

[00:02:12] Can you tell everyone listening a little about who you are and what you do?

[00:02:16] So, my name is Dominic Castananti.

[00:02:18] I'm the Vice President and General Manager for the Mobility Solutions Division at Panasonic Connect.

[00:02:23] And really, our mission is to deliver and create communication solutions that enable our clients to keep connectivity,

[00:02:32] but really in the most challenging environments and conditions.

[00:02:36] And by that, I mean extreme heat, extreme cold, wind, dust, high vibration environments, if you think of a police truck.

[00:02:46] So, it's really for mobile workers that are out in the field, kind of not in that office environment.

[00:02:51] That's who our customer is.

[00:02:53] We've been delivering solutions for 28 years.

[00:02:56] This is when the first Toughbook was launched.

[00:02:59] And we've been excited to support that industry ever since.

[00:03:02] And it's my pleasure to be with you here today.

[00:03:06] It's a pleasure to have you join me.

[00:03:08] And every day on this podcast, I try and get people thinking differently about areas that technology is transforming,

[00:03:14] that we don't automatically associate with technology.

[00:03:17] And when you mention words like heat and wind, it's almost the enemy of technology as well, which makes it extra special.

[00:03:23] So, there's a lot of hype around AI at the moment.

[00:03:27] And I'm curious, from everything that you're seeing, how do you see technology, particularly AI,

[00:03:32] maybe reshaping the operations of mission-critical workforces and industries like law enforcement, utilities, agriculture,

[00:03:41] areas that you don't traditionally associate with tech?

[00:03:44] Yeah.

[00:03:44] So, I would just start off saying AI has been around for a while,

[00:03:47] but it's truly having a much more significant impact reshaping operations across all industries.

[00:03:55] You mentioned a few law enforcement utilities, but really, when you look at all the verticals that we support,

[00:04:01] AI is part of that operational scheme.

[00:04:05] And I know it's on the radar for all the IT professionals that we're working with.

[00:04:11] When I think of mission-critical industries, and by mission-critical, I'm relying mostly public safety, police, fire, EMS, utility workers.

[00:04:22] They're having AI really process data in a much faster, more efficient manner than they ever have before.

[00:04:32] If we just think of some of the wildfires that have taken place in Hawaii, New York, California,

[00:04:38] and how AI is being used in different imagery to understand the weather patterns,

[00:04:45] so firemen can react in a more efficient manner.

[00:04:50] But really, AI is being adopted really throughout all the different organizations.

[00:04:56] So, it truly is reshaping the landscape and the way all these different verticals are interacting with each other.

[00:05:06] If I just think of law enforcement for a moment, departments have always had large volumes of data to analyze,

[00:05:14] and it's always been very time-consuming.

[00:05:17] If I think through how videos, body-worn cameras, and all that amount of data that's now coming into a police agency,

[00:05:25] and someone has to review that footage, it takes hours and hours to do that.

[00:05:30] AI has now given the police departments and agencies tools that they can go through that data at a much faster rate.

[00:05:42] Also, for social media.

[00:05:43] When I think back, when I started my career, there was no social media, right?

[00:05:48] Social media back then was calling into a party line, and you can have eight people talking at once.

[00:05:53] We thought that was really exciting.

[00:05:55] So, now with all the different social media that's out there, that's just another area where law enforcement agencies have to really monitor.

[00:06:06] And again, AI is helping with all of that.

[00:06:10] So, I would say it's not just automating repetitive tasks.

[00:06:15] It's really enabling smarter, data-driven type decision-making, right?

[00:06:22] To enhance productivity, reduce errors, allow workers to really focus more on their job versus the administrative aspects of their role.

[00:06:32] So, that's kind of where I see AI reshaping operations for some of the more mission-critical agencies.

[00:06:41] Wow, incredibly cool what you're doing here.

[00:06:44] Yeah, and I've always got flashbacks from my youth talking about those party lines now.

[00:06:48] Long forgot about them.

[00:06:50] I'm showing my age.

[00:06:51] I'm showing my age, Neil.

[00:06:53] You and me both, my friend.

[00:06:54] Well, I do think it is important that you are shining this light on mission-critical workforces as well.

[00:07:00] And before you came on the podcast, I was doing a little research, and one of the things that came up was with the majority of first responders are actually expressing dissatisfaction with their current data reporting processes.

[00:07:12] What specific technological advancements are you seeing that could maybe help streamline these workflows and reduce overtime and all those gripes that they have?

[00:07:22] Because tech could solve a pretty big problem here, I would imagine.

[00:07:24] It's funny, when we work with HR and recruiting, and it's amazing how the requirements have really changed over the last decade.

[00:07:33] It used to be people were interested in what are the benefits, how many hours, what's my pay?

[00:07:38] Now we see more applicants asking about what technology is deployed across your company.

[00:07:45] And we're seeing that through our clients as well, right?

[00:07:50] So one of their dissatisfaction with many responders is data reporting is a significant issue, not having the latest technology to do their jobs.

[00:08:01] So when you think of when the iPhone was launched, I don't know the exact date, I think it's about 20 years or so ago, the generation in the workforce has been brought up with iPhones and tablets and they're very application savvy.

[00:08:17] So I think more mobile workers are requiring technology that doesn't just streamline some of the administrative data reporting aspects of their role, but is really able to integrate into their workflow to make it seamless, to make it feel natural.

[00:08:33] So you're not going out of your way to use the technology that's being deployed.

[00:08:42] So when I think of area of improvement, first responders still reply on manual processes for recording incident details.

[00:08:52] Could be very time consuming, could be prone to errors, but AI has tools now.

[00:08:58] Speech-to-text technology is just one example where you could very easily fill out a report.

[00:09:04] That report could be populated in the certain fields that are required.

[00:09:09] And now that law enforcement professional is really focused on making sure that that report captures the essence of the incident and not so much focused on the typing and the grammar and the spelling, right?

[00:09:25] So when you look at real-time sharing of data, analytic platforms, departments and agencies can sometimes be very siloed.

[00:09:34] So we're also seeing where AI is breaking down that boundary, giving more information to the officer.

[00:09:41] So when they respond, when they pull up to a domestic dispute occurrence at someone's house, they have more information at their fingertips.

[00:09:53] The other area where we see it, just in mobile computing itself, having a device where you're no longer tethered to your vehicle, that you can get out of your car, still be connected, still have connectivity to all your applications, all your data.

[00:10:09] And that's taken in the form of tablets, computers, but a lot of different hardware type devices.

[00:10:15] But those apps are really important for today's, call it modern worker, in that data is just coming at us from all different angles.

[00:10:25] And sometimes you have data overload.

[00:10:28] So it's just really important to be able to not just capture that data, but also act on it.

[00:10:34] And AI has given us tools to do just that, Neil.

[00:10:38] It's really transforming the way first responders work, utility workers work.

[00:10:44] Less time in the office, less time in their vehicle, less time in doing paperwork, more time focusing on their critical tasks,

[00:10:53] being out in the field and really delivering on those security and services that they're chartered to deliver to the public citizens.

[00:11:04] And if we were to assume in another problem and big challenge like staffing challenges in the essential industries

[00:11:11] and always impacting the mission critical workforce as well, how are you at Panasonic Connect helping there?

[00:11:19] And what role do you see AI and other advanced technologies playing in helping to ease and address some of these issues?

[00:11:26] Yeah.

[00:11:27] Yeah.

[00:11:27] So I would say Panasonic Connect is really addressing a good portion of those staffing challenges

[00:11:33] in the essential industries that we're talking about here today.

[00:11:37] But really by deploying these AI-driven solutions, and we do that through a variety of ways.

[00:11:43] First off, our rugged devices.

[00:11:46] And again, Panasonic launched the first rugged notebook about 28 years ago in 1996.

[00:11:53] And we've been making innovative developments ever since, whether it be through connectivity, applications, ruggedness.

[00:12:00] But now we're making sure that all of our tough books are AI-enabled, making sure they have enough processing power,

[00:12:08] the speed to perform vast amount of data analytics and calculations very quickly.

[00:12:16] And we work very closely with Intel as our chip provider, just to make sure that our product roadmap,

[00:12:24] as we're developing our roadmap based on specific customer feedback,

[00:12:30] making sure that that lines up with their chipset development.

[00:12:34] So when we launch a product, we're launching the most technology-savvy equipment,

[00:12:42] hardware to support all these different software and application solutions.

[00:12:48] Another area where we're making a difference is automating routine tasks where we can enhance productivity.

[00:12:54] So we have AI-powered devices that are helping field workers in the utility field really analyze their data at a faster rate.

[00:13:07] For law enforcement, when you have law enforcement officers out in the field,

[00:13:13] we want to make sure they're connected with their devices that provide real-time data.

[00:13:18] Situational awareness, for instance, is really critical, not just for the safety of citizens,

[00:13:23] but also for officer safety as well.

[00:13:27] And where we see field workers, and field workers is a broad category,

[00:13:33] but where we see a critical role in improving workforce efficiency is around sensors and monitoring equipment.

[00:13:42] So where we can predict if there's an unsafe situation with an officer.

[00:13:47] So as an example, if there's monitoring equipment and we see that their heart rate is increasing,

[00:13:54] or through camera technology, we can see if their eyes are starting to get droopy,

[00:13:58] maybe they're overworked, they're getting tired.

[00:14:01] So we try to do a lot in the world of predictive analytics,

[00:14:05] trying to predict a situation before it becomes a problem.

[00:14:12] And then lastly, really in the training.

[00:14:15] All these new applications, new technology require training.

[00:14:19] We don't ever see that it's going to replace the human interaction,

[00:14:25] but we do see that it's going to augment it.

[00:14:27] So there could be staffing shortages or other ways to optimize the existing workforce.

[00:14:37] So by training the workforce on new solutions and how best to use this technology

[00:14:44] to complement what they do and not really to replace what they do.

[00:14:48] And just to bring to life everything that you're talking about here,

[00:14:51] are you able to share maybe a few real-world examples where advanced tech has significantly

[00:14:57] improved efficiency and indeed outcomes for mission-critical workforces?

[00:15:02] And you don't have to mention any names here,

[00:15:04] but I was thinking it would really help listeners understand the kind of value

[00:15:06] and ultimately ROI on tech projects that you're delivering here.

[00:15:10] Yeah, so there are definitely a few that come to mind.

[00:15:14] We do case studies with a lot of our customers when we deploy something that might be unique

[00:15:20] or different or cutting edge.

[00:15:22] We'll work with our clients to produce a case study to get that out to the public.

[00:15:27] And that's not just for Panasonic's benefit.

[00:15:30] It's really for the benefit for the industries that we support.

[00:15:34] But we have a few examples where we're working with mining companies in Canada.

[00:15:39] They're using our devices so when they go down in mine shafts,

[00:15:42] they get a better layout of the environment that can detect if there's any type of negative

[00:15:48] structural concerns.

[00:15:51] We've worked with different utility companies,

[00:15:55] really focused on making sure that the Toughbooks are helping them define

[00:16:00] if there's an issue with the power grid and can detect if there's any leaks

[00:16:06] or any water leaks in any of the infrastructure.

[00:16:10] So our Toughbooks are deployed for that in real world situations.

[00:16:17] That's where we really, really focus a lot of our effort on is looking at those rugged environments,

[00:16:26] harsh environments, and working with the industry experts and giving them tools that they need

[00:16:33] to do their jobs in the most efficient manner.

[00:16:36] If I think of some other examples in the utility sector, we talked a little bit about sensors, power lines.

[00:16:45] When you think of critical infrastructure, how do you protect it?

[00:16:48] How do you secure it?

[00:16:50] You definitely don't want to wait for an incident to occur and then respond.

[00:16:54] So as much as we can get out and do proactive maintenance, preventative care for that critical infrastructure that we have,

[00:17:05] that's where we really focus a lot of our effort on law enforcement as well, data analytics, real-time decision-making tools.

[00:17:15] So the more we can empower people out in the field, give them the tools they need to not to go back to the office,

[00:17:22] not to kind of transmit information to a home office, a command center, and then have someone else relay back to them what situational awareness,

[00:17:34] that's really what we're focused on.

[00:17:36] So to provide that to today's workforce is really important to us and really part of our main fundamental initiatives.

[00:17:47] And I think today's workforce is more tech-savvy than ever, and they have rising expectations for workplace technology.

[00:17:55] And Gen Z, for example, they cannot remember a time before the iPhone existed,

[00:18:00] and these digital natives are just used to having the best tech at their fingertips,

[00:18:04] but then find themselves entering a workplace for the first time.

[00:18:07] It feels like going back in time almost.

[00:18:09] How can organizations ensure that they meet these demands and ultimately attract and retain talent?

[00:18:16] You really hit it. We touched a little bit on it earlier.

[00:18:19] Today's workforce is more tech-savvy than ever, right?

[00:18:23] And I'll just keep increasing.

[00:18:25] Three, four, five years from now, we'll talk about where we are today,

[00:18:28] and we'll be amazed, right?

[00:18:32] So when we look at, especially the younger generation,

[00:18:35] they have clearly rising expectations, right, for the tools that they want to work with.

[00:18:41] And in order to really attract and retain that talent,

[00:18:45] organizations are going to have to meet those demands by investing in the right technology

[00:18:49] to foster those efficient, flexible work environments.

[00:18:53] Mobile workers now rely on that technology to do their day-to-day job.

[00:18:59] Like, you get very frustrated right when technology doesn't work,

[00:19:02] and you have to go back to paper and pencil or whatever the previous method was.

[00:19:08] But employees want to work with tools that are current,

[00:19:13] that are current up-to-date, cutting edge,

[00:19:15] and that's a lot of where AI-powered analytics comes into play today.

[00:19:20] And again, we talked about AI being around us and in our everyday lives,

[00:19:26] but bringing it now to the workplace is almost a requirement.

[00:19:32] And if you want to focus on the flexibility and the remote capabilities of workers today,

[00:19:39] you're right.

[00:19:39] I mean, COVID-19 changed the landscape.

[00:19:43] COVID just would have lasted a couple of months.

[00:19:45] People would have went back to the office, back to office business as usual.

[00:19:50] But it didn't last a couple of months, as we all know.

[00:19:53] It lasted a couple of years.

[00:19:54] And people adapted.

[00:19:56] They converted bedrooms to offices.

[00:19:58] They converted basements to offices.

[00:20:00] So that hybrid work, remote work environment is really around for a while.

[00:20:06] And even though there's a lot of companies out there,

[00:20:08] some companies trying to bring their workers back,

[00:20:12] a Monday through Friday 9 to 5 office job,

[00:20:15] I think, is going to be really, really challenging.

[00:20:18] So when you look at the importance of having technology for people to work remotely,

[00:20:23] to be able to collaborate with each other,

[00:20:25] those are all critical aspects that all companies are considering.

[00:20:32] So not just within Panasonic, we're faced with those challenges,

[00:20:35] but also our clients are.

[00:20:38] So cloud-based solutions,

[00:20:41] video conferencing tools that are being used,

[00:20:43] more collaborative platforms that are being rolled out

[00:20:47] from a lot of different companies.

[00:20:49] Those are just some of the examples of how I see technology really integrating itself

[00:20:57] beyond just focused on the business,

[00:21:00] but more focused on the employees aspect of it.

[00:21:05] More training, upskilling opportunities.

[00:21:08] When you think through,

[00:21:10] a lot of companies have training initiatives.

[00:21:13] Might be around management,

[00:21:14] might be around different focus,

[00:21:16] but a lot of those training initiatives are now focused around technology

[00:21:20] and how to use technology in the workplace.

[00:21:22] How do you collaborate?

[00:21:24] How do you manage a team of individuals

[00:21:27] that are scattered across the U.S.?

[00:21:29] Can't go in the office anymore.

[00:21:31] You can't have a team meeting.

[00:21:33] A lot of that office FaceTime

[00:21:36] is now being replaced

[00:21:38] with a video conferencing type tool.

[00:21:40] So technology is evolving.

[00:21:44] It will continue to evolve.

[00:21:46] But I think by embracing

[00:21:47] and integrating the latest technologies

[00:21:50] and ensuring that they meet the needs

[00:21:52] and expectations of the workforce,

[00:21:55] organizations can not only attract top talent,

[00:21:58] but also keep them engaged

[00:22:00] because no one wants high turnover.

[00:22:03] High turnover for a company is expensive,

[00:22:06] so you want to be able to keep and retain your top talent.

[00:22:10] And beyond increasing efficiency,

[00:22:13] I'm curious,

[00:22:13] are there any other big roles

[00:22:15] or significant roles that technology could play

[00:22:18] in improving the quality of service provided

[00:22:21] by mission-critical industries

[00:22:23] and those services that they provide to their communities?

[00:22:26] Any other big roles you see tech playing here?

[00:22:29] Yeah, definitely quality of service

[00:22:32] is front and center.

[00:22:33] When you think of,

[00:22:35] again,

[00:22:35] improved decision-making

[00:22:36] and responsiveness.

[00:22:39] So if you're an emerging response

[00:22:41] and you can react seconds sooner,

[00:22:44] they talk about seconds matter

[00:22:46] and seconds is the difference between life and death

[00:22:48] in the public safety industry.

[00:22:51] So AI can really help patterns.

[00:22:54] They can help look through

[00:22:56] are there certain predictive

[00:22:58] or analytics that could be helped

[00:23:01] to improve the quality of service

[00:23:03] that first responders are giving to their community?

[00:23:07] Are there high crime areas

[00:23:09] during certain hours of the night?

[00:23:11] During,

[00:23:12] if they're holding events,

[00:23:14] concerts or different events.

[00:23:15] So by having all of that data

[00:23:18] at their fingertips,

[00:23:20] they can staff it more appropriately

[00:23:21] to ensure they have more officers

[00:23:24] patrolling the areas

[00:23:25] that are prone to high crimes

[00:23:26] during situations.

[00:23:28] And it also really helps enhance

[00:23:30] the overall customer experience.

[00:23:33] When you think about the utility business,

[00:23:36] again,

[00:23:36] going back to smart grids,

[00:23:38] how do you analyze information

[00:23:42] at a faster rate

[00:23:43] that is going to result

[00:23:44] in fewer service disruptions?

[00:23:46] So if there's a power outage,

[00:23:48] if there's a storm

[00:23:50] and the power goes out,

[00:23:51] how do you analyze that grid

[00:23:53] at a faster rate

[00:23:53] to bring the power back on?

[00:23:55] How do you restore water?

[00:23:57] How do you get the public

[00:24:00] kind of back to their previous standards?

[00:24:03] Not just standard of living,

[00:24:05] but how do you restore those services

[00:24:08] back to when the,

[00:24:10] prior to when the incident occurred?

[00:24:12] For increased safety and security,

[00:24:16] technology is helping the ability

[00:24:18] to protect communities, right?

[00:24:20] Improving surveillance,

[00:24:21] crime prevention,

[00:24:23] different response strategies.

[00:24:25] We mentioned a little bit

[00:24:26] about body-worn cameras.

[00:24:29] Now we have drones.

[00:24:30] We have AI-driven facial recognition

[00:24:33] in certain markets

[00:24:34] to help officers make quicker,

[00:24:37] more accurate decisions

[00:24:38] in critical situations.

[00:24:41] The data analytics helps trends

[00:24:44] in criminal activity,

[00:24:45] enabling agencies to focus on areas

[00:24:48] where they need to have

[00:24:50] the greatest need

[00:24:50] for preventing crimes

[00:24:52] before they even happen.

[00:24:55] So ultimately,

[00:24:56] technology empowers

[00:24:57] mission-critical industries

[00:24:59] to not just operate

[00:25:01] more efficiency,

[00:25:02] but really to deliver

[00:25:03] a higher quality

[00:25:05] and a more reliable

[00:25:06] level of service

[00:25:08] to the communities they serve.

[00:25:09] And Neil,

[00:25:10] I would say it fosters

[00:25:11] stronger connections

[00:25:13] between the service providers

[00:25:14] and the public

[00:25:15] and having that connection itself

[00:25:17] can improve outcomes

[00:25:19] and create a more sustainable

[00:25:21] and equitable future

[00:25:22] for everyone.

[00:25:25] And one of the things

[00:25:26] I love doing

[00:25:27] on this podcast

[00:25:28] is busting a few myths

[00:25:29] and misconceptions,

[00:25:31] especially allow my guests

[00:25:32] a little time to remove

[00:25:34] some of the pressure

[00:25:35] of some of those things

[00:25:36] they see that might frustrate them.

[00:25:37] And I'm sure

[00:25:38] that you encounter

[00:25:39] more than a few of these

[00:25:41] in your time.

[00:25:42] So what are some

[00:25:42] of the biggest misconceptions

[00:25:45] and myths about

[00:25:46] integration of AI

[00:25:48] and advanced tech

[00:25:49] in industries

[00:25:49] like construction,

[00:25:51] agriculture

[00:25:51] and law enforcement?

[00:25:53] Now's your moment.

[00:25:54] Let's banish these

[00:25:55] once and for all.

[00:25:56] Anything you can share there?

[00:25:57] Yeah, so look,

[00:25:58] Panasonic is a 100-year-old company

[00:26:00] and their products

[00:26:02] and solutions

[00:26:03] we're offering now

[00:26:04] are obviously not

[00:26:05] what we offered

[00:26:06] 100 years ago.

[00:26:08] Innovation has incurred,

[00:26:10] technology has evolved,

[00:26:12] and I think this is just

[00:26:13] another evolution

[00:26:14] of that technology

[00:26:15] through AI.

[00:26:16] So I don't believe

[00:26:18] that AI will

[00:26:19] replace human jobs.

[00:26:21] I think they will

[00:26:22] complement those jobs.

[00:26:24] I don't believe

[00:26:26] it's going to make

[00:26:27] workers obsolete.

[00:26:28] It could,

[00:26:29] it could though

[00:26:30] if you don't evolve

[00:26:31] with the technology.

[00:26:32] Going back

[00:26:33] and embracing

[00:26:34] the technology,

[00:26:35] understand how

[00:26:36] it can be used.

[00:26:38] I think another

[00:26:39] misconception

[00:26:40] is around

[00:26:41] that AI deployments

[00:26:42] are all the same.

[00:26:44] that how you deploy AI

[00:26:46] in one situation

[00:26:48] or one use case

[00:26:49] or one industry

[00:26:50] is how AI

[00:26:51] gets deployed

[00:26:52] collectively.

[00:26:53] And that's not true.

[00:26:55] I mean,

[00:26:55] AI has to be

[00:26:56] deployed

[00:26:57] to kind of match

[00:26:58] the problem

[00:27:00] that it's trying

[00:27:02] to solve.

[00:27:02] So when you think

[00:27:03] of data security

[00:27:04] and privacy

[00:27:06] require more

[00:27:07] stringent measures,

[00:27:08] that might not

[00:27:09] be the case

[00:27:10] in agriculture

[00:27:11] for instance.

[00:27:12] So I don't think

[00:27:14] AI will replace jobs.

[00:27:16] I think it could

[00:27:17] create more

[00:27:18] opportunities

[00:27:19] for different employees

[00:27:21] to evolve

[00:27:22] over time.

[00:27:24] Other misconception

[00:27:25] is AI

[00:27:26] is very complex

[00:27:28] and expensive

[00:27:30] for small operations.

[00:27:31] That's not true

[00:27:32] either.

[00:27:33] So whether you're

[00:27:34] a large organization

[00:27:36] with a multi,

[00:27:37] you know,

[00:27:38] multi-million dollar budget

[00:27:39] or whether you're

[00:27:40] a small mom-and-pop

[00:27:43] type organization

[00:27:44] or company,

[00:27:45] AI could be

[00:27:46] deployed across,

[00:27:48] could scale

[00:27:49] very,

[00:27:50] very easily.

[00:27:51] And the other

[00:27:52] piece I see

[00:27:53] out there

[00:27:54] is that

[00:27:56] there's always

[00:27:56] going to be

[00:27:57] some human

[00:27:57] element

[00:27:58] to AI.

[00:28:00] Misconception

[00:28:00] is that once

[00:28:02] these AI systems

[00:28:03] are set up,

[00:28:03] they're just

[00:28:04] going to

[00:28:04] operate

[00:28:06] autonomously

[00:28:07] without any

[00:28:08] human intervention.

[00:28:09] And in reality,

[00:28:12] so while

[00:28:13] AI is powerful

[00:28:14] and it is

[00:28:15] a powerful tool,

[00:28:17] there's always

[00:28:18] going to be

[00:28:18] an element

[00:28:19] of human oversight

[00:28:20] to ensure

[00:28:21] that the accuracy

[00:28:22] is aligned

[00:28:23] with the

[00:28:24] organizational goals.

[00:28:25] Right?

[00:28:26] So I think

[00:28:26] those are just

[00:28:27] a couple areas.

[00:28:28] It offers

[00:28:29] a tremendous

[00:28:30] potential

[00:28:31] and they're not

[00:28:32] magic solutions

[00:28:33] that I would say

[00:28:34] that solve

[00:28:35] all problems

[00:28:36] without careful

[00:28:37] planning,

[00:28:37] human oversight

[00:28:38] and adaptation

[00:28:40] to those needs.

[00:28:42] But I think

[00:28:42] these are some

[00:28:43] of the misconceptions

[00:28:44] that we'll

[00:28:45] overcome

[00:28:46] as we learn

[00:28:47] and understand

[00:28:48] the technology

[00:28:49] better.

[00:28:50] So many great

[00:28:51] points there

[00:28:51] and I can hear

[00:28:52] people or see

[00:28:53] people around

[00:28:53] the world

[00:28:54] nodding their

[00:28:54] head in agreement

[00:28:55] and equally

[00:28:56] setting off

[00:28:56] a few light bulb

[00:28:57] moments.

[00:28:58] And looking ahead,

[00:28:59] we are literally

[00:29:00] weeks away

[00:29:01] from life

[00:29:01] in 2025.

[00:29:02] So how do you

[00:29:04] envision the role

[00:29:05] of Panasonic

[00:29:06] Connect in further

[00:29:07] driving innovation

[00:29:08] and meeting

[00:29:09] those continuously

[00:29:10] evolving needs

[00:29:11] of essential

[00:29:11] industries,

[00:29:12] not just next

[00:29:13] year but beyond

[00:29:14] that too?

[00:29:15] Yeah,

[00:29:17] innovation is

[00:29:18] part of

[00:29:19] Panasonic's DNA.

[00:29:21] So we're

[00:29:22] confident we're

[00:29:23] going to keep

[00:29:24] driving advancements

[00:29:26] in these mission

[00:29:27] critical industries

[00:29:28] forward.

[00:29:28] because of our

[00:29:30] innovation drive,

[00:29:32] because of our

[00:29:32] legacy,

[00:29:33] we engineer,

[00:29:34] we design,

[00:29:35] we manufacture

[00:29:36] the solutions

[00:29:37] that we deploy.

[00:29:38] We move at

[00:29:39] the speed and

[00:29:40] scale consistent

[00:29:41] to what our

[00:29:42] customers demand

[00:29:42] is.

[00:29:43] We don't try

[00:29:44] to over-architect

[00:29:45] anything,

[00:29:46] we try to deliver

[00:29:47] exactly what

[00:29:48] consumers are

[00:29:49] looking for.

[00:29:50] So innovation

[00:29:51] takes a lot

[00:29:53] of,

[00:29:53] is based

[00:29:54] different based

[00:29:55] on customer

[00:29:56] needs.

[00:29:56] And we really

[00:29:57] pride ourselves

[00:29:58] on the strength

[00:29:59] of a growing

[00:30:00] partner ecosystem.

[00:30:01] So if we're

[00:30:02] not going to be

[00:30:03] the number one

[00:30:04] or number two

[00:30:04] in the particular

[00:30:05] market that we

[00:30:06] operate in,

[00:30:07] we understand

[00:30:07] the need to

[00:30:08] have partners

[00:30:09] and build out

[00:30:10] an ecosystem

[00:30:11] of partners

[00:30:11] that when you

[00:30:13] put all these

[00:30:13] solutions together,

[00:30:14] it really

[00:30:15] complements

[00:30:16] the total

[00:30:17] portfolio.

[00:30:18] So we feel

[00:30:20] Panasonic's

[00:30:21] heritage

[00:30:21] will really

[00:30:23] be a pivotal

[00:30:23] role in

[00:30:24] driving innovation

[00:30:25] across

[00:30:26] various

[00:30:27] industries.

[00:30:28] We feel

[00:30:29] our rugged

[00:30:30] hardware

[00:30:30] is very

[00:30:31] high-quality

[00:30:32] reliable.

[00:30:33] A lot of

[00:30:33] these software

[00:30:34] have to,

[00:30:34] or all the

[00:30:35] software applications

[00:30:36] have to work

[00:30:37] on something.

[00:30:38] So we

[00:30:39] deliver the

[00:30:40] hardware that

[00:30:40] enables these

[00:30:42] applications to

[00:30:42] work.

[00:30:43] And we just

[00:30:44] feel that

[00:30:45] our role in

[00:30:45] the future

[00:30:46] will be

[00:30:46] to continue

[00:30:47] to innovate

[00:30:48] or look at

[00:30:48] the intersection

[00:30:49] of where

[00:30:50] hardware,

[00:30:51] software solutions,

[00:30:53] cloud-based

[00:30:53] solutions,

[00:30:54] AI,

[00:30:55] IoT,

[00:30:56] where they

[00:30:56] intersect.

[00:30:57] And by

[00:30:58] providing

[00:30:58] these

[00:30:59] technologies

[00:31:01] that improve

[00:31:02] the safety

[00:31:03] and efficiency

[00:31:04] and decision

[00:31:04] making,

[00:31:05] Panasonic will

[00:31:06] really empower

[00:31:07] workers out in

[00:31:08] the workforce.

[00:31:08] And that's

[00:31:09] really what

[00:31:10] we're trying

[00:31:10] to do is

[00:31:11] making sure

[00:31:11] that mobile

[00:31:13] workers have

[00:31:14] the data and

[00:31:14] information they

[00:31:15] need to make

[00:31:16] decisions when

[00:31:18] they're out in

[00:31:18] the workforce

[00:31:18] at the time

[00:31:19] it's critical.

[00:31:21] Well, a big

[00:31:22] thank you to

[00:31:22] you, Dominic,

[00:31:23] for not only

[00:31:24] sharing your

[00:31:24] valuable insights

[00:31:25] and busting a

[00:31:27] few myths but

[00:31:28] also shining a

[00:31:29] light on those

[00:31:29] mission-critical

[00:31:30] workforces and

[00:31:31] the role of

[00:31:32] technology.

[00:31:33] But before I

[00:31:34] let you go,

[00:31:34] I'm going to

[00:31:34] ask you to

[00:31:35] leave one

[00:31:35] final gift to

[00:31:37] everyone listening.

[00:31:37] We have an

[00:31:38] Amazon wish list.

[00:31:39] I ask everyone

[00:31:39] listening, every

[00:31:41] guest, if they

[00:31:42] can leave a book

[00:31:42] that means

[00:31:43] something to

[00:31:43] them or they

[00:31:44] would recommend

[00:31:45] for other

[00:31:45] listeners to

[00:31:46] check out and

[00:31:47] we add it to

[00:31:48] that list.

[00:31:48] So, Dominic,

[00:31:49] what book would

[00:31:50] you like to

[00:31:50] add to that

[00:31:51] list and

[00:31:51] why?

[00:31:52] Well, I tell

[00:31:53] you, a book

[00:31:53] that I've read

[00:31:54] that has stuck

[00:31:55] with me over

[00:31:56] the years and

[00:31:56] I read it a

[00:31:57] while ago and

[00:31:58] I still use it

[00:32:00] and refer to it

[00:32:02] in business

[00:32:03] today.

[00:32:04] It's a book by

[00:32:05] Clayton

[00:32:05] Christensen

[00:32:06] called Innovator's

[00:32:07] Dilemma and

[00:32:09] really what the

[00:32:10] essence of the

[00:32:11] book is talks

[00:32:11] about is how

[00:32:13] companies that

[00:32:15] are in niche

[00:32:16] markets kind

[00:32:16] of create

[00:32:17] industries

[00:32:18] industries, but

[00:32:19] then they are

[00:32:21] so hung up on

[00:32:22] the industry

[00:32:23] that they

[00:32:24] created that

[00:32:25] they no longer

[00:32:26] truly innovate

[00:32:28] around that

[00:32:29] industry.

[00:32:30] It's more like

[00:32:31] sustaining

[00:32:31] innovation versus

[00:32:33] disrupting

[00:32:34] innovation because

[00:32:35] if they disrupt

[00:32:36] innovation, they're

[00:32:37] basically disrupting

[00:32:38] themselves because

[00:32:38] they all own the

[00:32:39] number one market

[00:32:40] share.

[00:32:41] But, Neil, if

[00:32:42] you don't disrupt

[00:32:43] yourself, someone

[00:32:44] else will.

[00:32:46] innovation versus

[00:32:46] the market

[00:32:50] innovation versus

[00:32:51] position is,

[00:32:51] regardless of

[00:32:52] where your

[00:32:53] financials are

[00:32:54] coming from,

[00:32:55] because if you

[00:32:55] don't innovate,

[00:32:56] your competition

[00:32:57] will.

[00:32:58] Absolutely love

[00:32:58] that.

[00:32:59] And I'll get

[00:32:59] that book added

[00:33:00] to our Amazon

[00:33:01] wish list.

[00:33:02] And for

[00:33:02] everybody listening

[00:33:03] wanting to find

[00:33:04] out more

[00:33:04] information about

[00:33:05] Panasonic Connect,

[00:33:06] how you might be

[00:33:07] able to help

[00:33:07] talk to your

[00:33:08] team or connect

[00:33:09] with you, etc.,

[00:33:10] anywhere in

[00:33:10] particular you'd

[00:33:11] like to point

[00:33:12] them?

[00:33:12] I would say

[00:33:13] the best source

[00:33:14] of information

[00:33:14] is our company

[00:33:15] website.

[00:33:16] It's Panasonic

[00:33:17] Connect.

[00:33:18] If you just

[00:33:19] Google search

[00:33:20] Panasonic Connect

[00:33:21] Mobility, it'll

[00:33:22] pop up.

[00:33:23] And I'm on

[00:33:24] LinkedIn, so I

[00:33:25] stay pretty active

[00:33:27] on LinkedIn, so

[00:33:28] if anyone wants

[00:33:29] to reach out to

[00:33:30] me via LinkedIn,

[00:33:30] I'll be more

[00:33:31] than happy to

[00:33:32] do that.

[00:33:33] Awesome.

[00:33:34] Well, I'll have

[00:33:34] links to everything

[00:33:35] to make it nice

[00:33:36] and easy for

[00:33:36] everyone listening.

[00:33:37] And we covered

[00:33:38] so much today from

[00:33:39] how mission

[00:33:40] critical workforces

[00:33:41] can meet the

[00:33:42] evolving expectations

[00:33:44] through tech and

[00:33:45] its impact on

[00:33:46] essential industries,

[00:33:47] the role of AI

[00:33:48] and other tech in

[00:33:49] bridging those

[00:33:50] staffing gaps that

[00:33:52] we keep hearing

[00:33:52] about and also

[00:33:53] addressing the

[00:33:54] needs of today's

[00:33:55] tech-savvy

[00:33:55] workforce.

[00:33:56] And not to

[00:33:57] mention that,

[00:33:57] you also brought

[00:33:58] it to life with

[00:33:59] some real-world

[00:34:00] examples of how

[00:34:01] advanced tech is

[00:34:02] positively transforming

[00:34:03] operations across

[00:34:04] multiple industries

[00:34:06] and even had time

[00:34:07] to leave us with a

[00:34:08] cracking book to

[00:34:08] read to.

[00:34:09] Thank you for

[00:34:10] sharing all that

[00:34:11] with me today.

[00:34:11] Thank you,

[00:34:12] Neil.

[00:34:13] You have a great

[00:34:13] day.

[00:34:14] Appreciate it.

[00:34:14] As Dominic

[00:34:15] highlighted today,

[00:34:16] the transformative

[00:34:17] potential of AI

[00:34:18] and advanced

[00:34:19] technology and

[00:34:20] mission-critical

[00:34:21] industries is

[00:34:22] immense.

[00:34:23] Whether that be

[00:34:24] faster data

[00:34:24] processing and

[00:34:25] smarter decision-making

[00:34:26] to improve safety

[00:34:28] and efficiency,

[00:34:29] these tools are

[00:34:30] essentially empowering

[00:34:31] workers to focus on

[00:34:33] what truly matters,

[00:34:35] serving their

[00:34:36] communities.

[00:34:36] And with

[00:34:38] innovations like

[00:34:38] Panasonic's

[00:34:39] Toughbook devices

[00:34:40] and AI-powered

[00:34:41] solutions, the

[00:34:42] future of work in

[00:34:43] these essential

[00:34:44] industries is

[00:34:45] becoming more

[00:34:46] connected, more

[00:34:47] responsive and

[00:34:48] more effective.

[00:34:50] So over to you.

[00:34:51] How do you see

[00:34:52] technology shaping

[00:34:53] the future of

[00:34:53] your industry?

[00:34:55] Are tools like

[00:34:56] AI and rugged

[00:34:57] mobile devices for

[00:34:58] deskless workers the

[00:35:00] answer to improving

[00:35:01] efficiency and

[00:35:02] meeting your

[00:35:03] workforce's

[00:35:04] expectations?

[00:35:04] operations?

[00:35:05] I'd love to hear

[00:35:06] your thoughts on

[00:35:07] the role of

[00:35:08] technology and

[00:35:08] mission-critical

[00:35:09] operations.

[00:35:10] Let's continue

[00:35:10] this conversation.

[00:35:11] Please share your

[00:35:13] insights, your

[00:35:13] ideas, and let's

[00:35:15] explore some of

[00:35:16] those possibilities

[00:35:16] and challenges

[00:35:18] together.

[00:35:20] So techblogwriteroutlook.com,

[00:35:21] LinkedIn, Twitter,

[00:35:23] Instagram, just

[00:35:24] at Neil C.

[00:35:24] Hughes.

[00:35:25] Let me know your

[00:35:25] thoughts.

[00:35:26] But that's it for

[00:35:27] today.

[00:35:27] That went quick,

[00:35:28] didn't it?

[00:35:29] I'll be back again

[00:35:30] tomorrow with another

[00:35:31] guest.

[00:35:31] So I will speak with

[00:35:33] you all then.

[00:35:34] Bye for now.

[00:35:35] Bye for now.

[00:35:35] Bye for now.