Transcripts
Welcome, Unboxing Logistics family.
Speaker:It is so great to see you as always.
Speaker:I love our Unboxing Logistics community.
Speaker:You are all some of the smartest, brightest, hardworking people in the
Speaker:logistics and supply chain industry, and it is such a pleasure to be with you.
Speaker:As always, you know I'm your host of Unboxing Logistics,
Speaker:Lori Boyer of EasyPost.
Speaker:Okay, family.
Speaker:We're gonna be talking AI.
Speaker:You know, we talk AI every other second.
Speaker:You hear AI coming outta your ears, AI coming outta your nose.
Speaker:But there's also a reason that it's, and that's 'cause it's big, it's
Speaker:huge, and it is disruptive and making massive changes in the industry.
Speaker:Well, on the flip side, being used only in specific places where it's working.
Speaker:So we've brought someone in.
Speaker:We've got Dana Moffatt here from Acumatica.
Speaker:We are gonna be talking about AI in operations.
Speaker:Dana, will you introduce yourself?
Speaker:Give our little audience here a little background of who
Speaker:you are and where you work.
Speaker:Sure.
Speaker:Thank you Lori.
Speaker:I'm a product manager for distribution integrations at Acumatica.
Speaker:And a little bit about my background.
Speaker:I'm a product builder at heart.
Speaker:I love the creative process of software development.
Speaker:I work closely with our team at Acumatica to gather business
Speaker:requirements, articulate what we need to build, why we need to build
Speaker:it, and who we're building it for.
Speaker:I've spent my career solutioning for complex distribution and healthcare
Speaker:supply chain, and I've been with Acumatica for almost five years now.
Speaker:I live in Montreal, Canada.
Speaker:I love that.
Speaker:I heard you say process.
Speaker:Yeah, I was that the giveaway?
Speaker:Love it.
Speaker:Love it.
Speaker:That is fantastic.
Speaker:So Dana, I would love to hear, you said you've been at Acumatica five years.
Speaker:Also fun that you're in healthcare.
Speaker:I was in healthcare in a past life as well, so that's really cool.
Speaker:Two complex industries.
Speaker:Who is somebody that you kind of admire from this industry, or even
Speaker:just in your professional career?
Speaker:Can you share somebody who you admire?
Speaker:I think the person that I admire most is Ali Janney, our former
Speaker:Chief Product Officer at Acumatica.
Speaker:He's just retiring now after 15 years of being with Acumatica, and what I
Speaker:admire most about Ali is that he has this customer centric product design focus.
Speaker:So we are always solving real world problems for our customers.
Speaker:He encouraged us to get out in the field, visit our customers so that
Speaker:we could see and hear their stories.
Speaker:Conduct user research and bring back those learnings to our
Speaker:development teams in Acumatica.
Speaker:So helping us to understand those customer opportunities and challenges
Speaker:is really the key to building great product that our customers love.
Speaker:And we discovered as we were doing this that our customers really
Speaker:loved to be part of that process.
Speaker:They like providing us feedback.
Speaker:They like showing us what they do, how they do it.
Speaker:We can understand them better and build better capabilities in our
Speaker:ERP, which is an enter enterprise resource planning product.
Speaker:Ali also championed our Acumatica Community.
Speaker:It's a virtual meeting place where our customers and partners collaborate
Speaker:on product questions and new ideas.
Speaker:So that's what I really valued about Ali is that product
Speaker:leadership and me and mentorship.
Speaker:And I just really like to thank Ali for all that he's given to
Speaker:our product team over the years.
Speaker:Shout out to all the Alis out there.
Speaker:It is, every one of you pretty much watching or listening wherever
Speaker:you are likely have customers, and being customer centric and looking
Speaker:at customer problems, you should never be the hero to everyone else.
Speaker:You are looking at the customer, figuring out ways that they can
Speaker:be the heroes in their own life.
Speaker:Your product should always revolve, whether it's shipping,
Speaker:whether you're a, you know, retailer, whether you're ecommerce.
Speaker:Look to your customer, see what needs they have and work to address those needs.
Speaker:Don't just try to fit a round peg in a square hole.
Speaker:So I love that, Dana.
Speaker:That's fantastic.
Speaker:And shout out again to Ali Okay, let's dive in.
Speaker:I wanna talk AI.
Speaker:I am a super big AI nerd, Dana.
Speaker:I love AI.
Speaker:I love all the excitement that comes with it.
Speaker:Everyone here knows when they hear me, I love to talk AI.
Speaker:But let's start.
Speaker:Everyone basically is being like, okay, yeah.
Speaker:What are you doing for ai?
Speaker:What's your AI strategy?
Speaker:What's going on?
Speaker:From what you're seeing, you know, what do you feel like is
Speaker:really going on in the industry?
Speaker:How much of this is actually progress?
Speaker:How much are people just like, everyone else has an AI strategy.
Speaker:I need an AI strategy too.
Speaker:I'll just make one up.
Speaker:You know what, where is kind of the flavor of the industry
Speaker:that you're getting right now?
Speaker:Well, from what I'm seeing with many of our customers a lot of them
Speaker:have already been experimenting and exploring AI, and they've been doing
Speaker:it for a while now, either personally on their own or in their businesses.
Speaker:I visited customers that have been experimenting with these AI
Speaker:technology technologies to solve specific challenges like automation.
Speaker:So they were trying to automate manual processes in order to maintain headcount
Speaker:and get more done in the business without having to have more people added on.
Speaker:And then they would realign their people to focus on higher value work.
Speaker:So that is real progress.
Speaker:They were already looking for ways to leverage AI to
Speaker:solve real business problems.
Speaker:Then they came to us with ideas and challenges for us to
Speaker:incorporate it into Acumatica ERP.
Speaker:So I see that they really do have focus, but they weren't looking
Speaker:to solve every problem with AI.
Speaker:Only those that made sense for them at that time.
Speaker:So it wasn't seen as an answer to every question or problem.
Speaker:Although we should ask ourselves before we do anything, can AI help
Speaker:me or short, shortcut this for me?
Speaker:And in Acumatica, our approach is really pragmatic.
Speaker:I would say it's focused on our customer needs and not just AI for the sake of AI.
Speaker:And I think that's important.
Speaker:Although granted, if your competitors are exploring and already using
Speaker:AI, that's a competitive advantage.
Speaker:So if it helps 'em automate, gain, operational efficiencies, you don't
Speaker:wanna fall behind and you don't wanna be late to adopt that technology.
Speaker:So in that sense, there is that pressure I would say, Lori, not to fall behind.
Speaker:And I think that's what's great about Acumatica and our EasyPost
Speaker:teams, is that we collaborate closely with each other and our customers.
Speaker:And that includes our AI initiatives.
Speaker:So both of our products are already leveraging these AI technologies as
Speaker:part of our joint solution feature set.
Speaker:That's what we do best.
Speaker:So that frees up our customers to focus on the business of running their business.
Speaker:That's fantastic.
Speaker:There was a couple of really key things I thought you said in there,
Speaker:Dana, that I wanted to repeat.
Speaker:I loved how you mentioned that it's not to solve everything right now, right?
Speaker:Like, look for specific problems you have.
Speaker:I hear that again and again.
Speaker:I've interviewed so many AI experts and that is a key element there.
Speaker:You need to have a problem that you're gonna try to fix and not just try to
Speaker:grab AI and put it in anywhere that maybe you didn't even know you had a problem.
Speaker:But I also loved how you talked about it being a differentiator
Speaker:and that there is that real risk of falling behind if people take off.
Speaker:Where are you seeing it actually work right now?
Speaker:This is probably the question I get more than anything else.
Speaker:You know, we have a lot of disparate systems out there.
Speaker:You go in the warehouse, people may have 20 different technologies they're using.
Speaker:They don't connect well.
Speaker:The numbers don't cross over well.
Speaker:And, and it is a little bit of a struggle right now.
Speaker:So what, what are you seeing?
Speaker:What, what activities is it really working for?
Speaker:So where I think it's really working well right now and where people are
Speaker:getting a lot of value is using AI as for the purposes of anomaly detection.
Speaker:An anomaly detection is like is like having another pair of
Speaker:eyes at the back of your head.
Speaker:So you have AI looking for adverse trends or situations to call your attention
Speaker:to so you can act and course correct.
Speaker:And I give you a perfect example from Acumatica.
Speaker:Our solution has something called margin anomaly detection.
Speaker:So it helps you to detect if you're in danger of not meeting your margin goals.
Speaker:So in an era of rising costs where margins are already thin, and that's
Speaker:holds true for a lot of our shippers.
Speaker:It can call out situations for you to act on.
Speaker:So I think that's really helpful.
Speaker:I would say another great idea that we're working on is collaborating with EasyPost.
Speaker:So we're wanting to bring AI enabled rate shop capabilities
Speaker:to our customers in the future.
Speaker:So I think that will have a very real impact in the future as we collaborate
Speaker:together on that capability.
Speaker:I love it.
Speaker:So anomaly detection, massive.
Speaker:Really, really big.
Speaker:We have so much, so much data in this industry, so having tool that
Speaker:doesn't get tired and doesn't let things glaze by, really, really great.
Speaker:I love how you mentioned EasyPost, Acumatica and other companies out there.
Speaker:So if you are working, you know I mentioned earlier in a warehouse
Speaker:maybe have 20 technologies.
Speaker:A lot of companies are developing AI things within maybe solutions
Speaker:you're already using out there.
Speaker:So it could be you need to be looking into the vendors and the
Speaker:partners you're working with.
Speaker:They could have some things available that you're not even aware of.
Speaker:I know it's hard to keep up with that, but rate shopping.
Speaker:I wanna back you up on that one.
Speaker:There is, to me that is one of the best use cases to be able to just
Speaker:quickly look through and figure out.
Speaker:That's been kind of a, a bear for a lot of people for a long time.
Speaker:But figuring out which carrier is gonna be most reliable in which lanes
Speaker:and at which times and at which costs, and that is an easy no-brainer for me.
Speaker:Dana, on the flip side, where do you feel like maybe we're a
Speaker:little overhyped versus what our capabilities really are right now?
Speaker:I think there's a lot of hype out there about AI as the answer to
Speaker:every situation or problem, and that it's going to replace humans.
Speaker:AI's not doing my laundry yet, Dana.
Speaker:It's not.
Speaker:No, I, I hear you Lori, and you know, I wish I could do things like that.
Speaker:But I mean, in our day-to-day workplace I think there's concern
Speaker:or worry about that and, and maybe there's a lot of hype behind that.
Speaker:You know, I have to admit, I was a little bit skeptical at first when we started
Speaker:to use AI tools as a product manager.
Speaker:I started to use an AI assistant.
Speaker:And, and I saw, while she's not really replacing me, she's helping
Speaker:me to summarize meetings, conduct research, accelerate my day-to-day.
Speaker:I don't really see her as a threat, but she's a helper, a tool that makes
Speaker:me more productive and efficient.
Speaker:And I think that's the same for, you know, our listeners today.
Speaker:If we focus on AI as a helper or an assistant that we can leverage
Speaker:to get more done and not see it as the, the answer or the solution
Speaker:for everything or, or as a threat I think it could be very helpful and
Speaker:it could really be a competitive advantage for a lot of our customers.
Speaker:Yeah, you're pointing out something here that's kind of quietly not always spoken.
Speaker:Sometimes, people are afraid to implement AI because we're afraid to be replaced.
Speaker:And we hear about it in a general sense, like, oh, it may re,
Speaker:you know, replace workforce.
Speaker:But on a personal level, sometimes we feel like we need
Speaker:to prove that I am more valuable.
Speaker:And it's exactly like Dana said, once you jump in and start using AI, you
Speaker:realize this is not yet at the point where it's really working without me.
Speaker:Now, maybe five years, we'll see what happens, but right now it really
Speaker:needs that human guidance, but it is an incredible assistant who doesn't
Speaker:care if you get mad at it and who you know is gonna be working 24/7 for you.
Speaker:And really can help with a lot of that kind of busy work.
Speaker:I think that's critical, Dana, don't you think especially with labor challenges
Speaker:have been massive in our industry forever.
Speaker:And in a way this really helps bridge some of those gaps.
Speaker:Rather than replacing, it helps, you know, alleviate some of those pains.
Speaker:Have you felt like that as well?
Speaker:Yes.
Speaker:I mean, I've heard that especially during COVID when, you know, a lot
Speaker:of workforce kind of contracted, if you will, and warehouses had to
Speaker:do, make, do with less employees.
Speaker:So there's challenges in, in getting workforce into the
Speaker:warehouse, into the shipping desk.
Speaker:And if you have tools that can really help the people that are
Speaker:there you can do more with less.
Speaker:I think that's a win.
Speaker:But I think that's an important point is AI is not here to replace
Speaker:people, but the people weren't there.
Speaker:There is a contraction in the workforce.
Speaker:We have these very real struggles.
Speaker:It could be a really important tool for our customers to leverage to
Speaker:make up for the shortfall in labor.
Speaker:Absolutely.
Speaker:And you know, that's actually a global trend.
Speaker:I was recently reading this really interesting article about how China's
Speaker:big focus on AI is not necessarily to try to get ahead, but to fill in
Speaker:the fact that they have such an aging workforce with their one child policy
Speaker:that had, and they really just needed to help assist with human labor.
Speaker:In a way, I think that's true for us across the board that there
Speaker:are tons of opportunities with AI.
Speaker:Don't be scared of it.
Speaker:Don't hold off learning how to use it really well, just because of that.
Speaker:Okay.
Speaker:So we do hear Dana of a lot of companies who may invest in AI and then it
Speaker:doesn't go well, people don't implement.
Speaker:I'm curious to hear your thoughts on maybe why sometimes AI doesn't
Speaker:deliver or you know, are there red flags that people should look for?
Speaker:I'm like, maybe I shouldn't invest now or in this way, you know?
Speaker:What, what tips do you have around, I guess, trying to make sure when you
Speaker:invest in AI that you do get good ROI?
Speaker:Yeah.
Speaker:I think you, you have to have clear objectives and goals and that you're
Speaker:gonna be measuring key results.
Speaker:Like any strategy, I think you need to go know, going in what
Speaker:you want to accomplish and why.
Speaker:And if you don't have those clear objectives and, and you're leveraging
Speaker:AI in situations where it doesn't make sense, that could cause you
Speaker:to question your investment in AI.
Speaker:So I think it's really important that you, that you know your why.
Speaker:Why do we think AI is the answer for this particular problem or challenge?
Speaker:How will we know that AI ha has helped us transform or achieve our objectives?
Speaker:And how do we measure success or failure?
Speaker:Then benchmark that against pre AI.
Speaker:So another challenge, what you kind of touched on is aligning your
Speaker:employees as well and motivating them to use these AI technologies.
Speaker:So there's this element of change management that I think is, it's
Speaker:always a critical success fact factor.
Speaker:As and, and that go, that's hold true for ERP implementations and, and I'm
Speaker:sure for EasyPost implementations as well.
Speaker:Having a product champion is always an important ingredient.
Speaker:So champions lead the way, they advocate for the new way of doing things.
Speaker:They'll highlight the benefits of using AI and it'll help your employees
Speaker:grow and focus on more meaningful and value added work, I think.
Speaker:Okay.
Speaker:I love that you mentioned change management here.
Speaker:So we have some interesting trends around AI.
Speaker:A couple of things.
Speaker:I think it's like 95% of employees are using AI even on their own, what we
Speaker:often call shadow AI, where people are using AI tools that weren't official.
Speaker:Even though, you know, only 27% or something of logistics companies have
Speaker:some official AI programs in there.
Speaker:One of the challenges with AI is maybe if you've got people who have been
Speaker:using tools on their own, getting them to switch over to the official
Speaker:tools that you are implementing.
Speaker:You know, for instance, I had on my own used a bunch of, you know, ChatGPT
Speaker:things and then our company kind of switched over to Claude and that was
Speaker:a little bit of a challenge for me.
Speaker:So I think you are absolutely right.
Speaker:Get those champions out there.
Speaker:Get people.
Speaker:It's not just necessarily adopting new AI.
Speaker:It can be switching from tools that they have been using even on the
Speaker:down low, that shadow AI over to tools that make sense because it's
Speaker:got your entire background in there.
Speaker:You know, when we get shipping specific, you get Acumatica, you get
Speaker:EasyPost, you get other tools that are based on your shipping data.
Speaker:That's always gonna be better information.
Speaker:And so you want to convince people to kind of switch up their
Speaker:processes, move over, get alignment.
Speaker:If you don't get alignment, if you don't get input.
Speaker:There's a good chance that it's, that will flop.
Speaker:Yeah, totally agree.
Speaker:And, and like you say, you don't wanna go it alone.
Speaker:There may be a, a product out there like EasyPost or, or Acumatica,
Speaker:that have already solved the problem that you're looking to solve.
Speaker:So you know, you don't have to start from square one or we reinvent the wheel.
Speaker:You can leverage that work that they've already done because they've
Speaker:already invested a lot of time and resources and money in evolving
Speaker:these features for you that maybe you can just leverage out of the box.
Speaker:Or as you mentioned, Dana, that you said, you know, when you were talking
Speaker:about Ali and loving to get customers involved in sharing, reach out to some
Speaker:of the vendors you work with, reach out to the different companies and say, hey,
Speaker:this would be a really cool AI idea.
Speaker:Are you doing this?
Speaker:Maybe it's on the roadmap.
Speaker:Maybe it's something that you can help with.
Speaker:Exactly.
Speaker:I think communication is key and collaboration is key, especially with
Speaker:customers because you, you are the subject matter experts of your domain
Speaker:and you can bring us those use cases.
Speaker:If we don't have something that is an AI capability now that covers a use
Speaker:case that you're wanting to be covered, bring that to, bring that to us.
Speaker:So we invite our customers to bring us these use cases to collaborate on
Speaker:our community and we will often have interviews with our customers or go visit
Speaker:them to get these requirements and bring them to life in our product because we
Speaker:wanna deliver capabilities that bring value to them, that solve real problems.
Speaker:So it really is this, we need you as much as you need us.
Speaker:Yeah, completely, completely agree here.
Speaker:And on, on a similar note, look at your workforce as well.
Speaker:Like where Dana mentioned, you know, we're trying to get that change management,
Speaker:go to them and say, what areas do you see where we could use a little more ai?
Speaker:Where do you think that there are opportunities?
Speaker:And then maybe reach out.
Speaker:And it could be that there are those people that you're already working with
Speaker:or, or maybe you need to get a new tool.
Speaker:So let's, let's talk Dana, about layering in maybe AI.
Speaker:Do you feel like, are there certain things that they need to have in place
Speaker:operationally before they start adding ai?
Speaker:So I think it's really important to know your processes to have
Speaker:standard operating procedures or to have clearly defined frameworks.
Speaker:So that AI can be really leveraged to the best of its ability.
Speaker:So if your procedures or workflows, they're constantly changing, or
Speaker:your processes vary by team or customer, no standardization, it's
Speaker:hard for AI to learn from patterns because you don't have patterns.
Speaker:And if humans can't explain the process clearly, well then AI can't fix that.
Speaker:I think that's a good call out.
Speaker:So I think that's really something important to think
Speaker:about when you're layering in AI.
Speaker:I think also thinking about your use cases.
Speaker:So you may have something that is cool, but it's a low impact use case
Speaker:'cause you haven't tied it to your objectives and your key results.
Speaker:So they're gonna fail to show you that return on investment.
Speaker:So that would be, I think, chasing AI for the sake of having AI.
Speaker:So I really look to see is it solving these real world problems
Speaker:that bring value to the business?
Speaker:Okay.
Speaker:I love that you said that because honestly, some of the best use
Speaker:cases for AI are not very sexy.
Speaker:You know, it's like we wanna go for the glitter that this sometimes
Speaker:backroom accounting, so really boring stuff is beautiful use case for AI.
Speaker:So don't get caught up all in the glitter and glam of some of these.
Speaker:You had an amazing demo, but is it actually gonna bring you ROI Look
Speaker:at what your actual use cases are.
Speaker:That was spot on Dana.
Speaker:I love that.
Speaker:Okay.
Speaker:If somebody's gonna be getting started, do you have recommendations?
Speaker:What would be the first steps you would take to try to, you know,
Speaker:add in AI or if you already have some AI, and you're wanting to
Speaker:expand, you know, is that different?
Speaker:Do you follow the same steps?
Speaker:What?
Speaker:What are your recommendations?
Speaker:I think it's really important to look at your data and make sure that you've
Speaker:got good data, because I want you to remember that, that when you're
Speaker:training AI on bad data or that data hasn't been corrected it's gonna
Speaker:use that to inform your decision.
Speaker:So this could result in you incorporating bad data into these
Speaker:models and perhaps lead you to make less than ideal decisions and may cause
Speaker:you to think that AI is failing me.
Speaker:So remember, AI can inherit bias from historical data and it can reinforce
Speaker:bad patterns if you don't monitor it.
Speaker:So I think monitoring it is really important and, and, and, and remembering,
Speaker:well, what are we training the AI on?
Speaker:So really, I would say try to, as much as possible, clean up your data
Speaker:before you start leveraging that AI.
Speaker:It's a matter of, you know, garbage in, garbage out.
Speaker:So let's make sure that we take out the garbage and, and, and, and
Speaker:have clean data before we start.
Speaker:So I think that's really important to look at, at that and also to
Speaker:look at, well, what, what source of things are we training this model on?
Speaker:So what to look at, what not to look at.
Speaker:So remember I said, you know, humans are still needed.
Speaker:So you're right.
Speaker:I heard you say that.
Speaker:We are the guide, right?
Speaker:So we tell it what to look at and what we're interested in.
Speaker:So that guiding exercise is still important.
Speaker:So that's important before you start to really kind of think it
Speaker:through and make sure that you're starting with the best data possible.
Speaker:Yeah, absolutely.
Speaker:I've heard it from a million times, your AI is only gonna be as good as your data,
Speaker:both the data it's trained on, like Dana said, and the data that you share with it.
Speaker:So even making sure that you're working from a single source of
Speaker:truth, you know that you're not having different numbers in different
Speaker:areas that different teams are using.
Speaker:All of that is a, a big thing.
Speaker:Love that.
Speaker:That is exactly perfect.
Speaker:What if you're adding more AI, do you have any tips around that?
Speaker:So let's say that you've added AI maybe in an area, but you're
Speaker:thinking you could do more.
Speaker:Do you think of expanding from that one area?
Speaker:Do you add in different systems?
Speaker:I, I know there's not necessarily a perfect answer for this, but
Speaker:I'm just curious what you think.
Speaker:Yeah.
Speaker:So again, I think you have to look at well, what's my why?
Speaker:So if I'm expanding the workflow, is that workflow well understood?
Speaker:Is it something that has patterns?
Speaker:It could be well articulated that AI can learn off of?
Speaker:So I think that's really important.
Speaker:I think also that when you tackle AI, you don't want to
Speaker:treat it as one lump sum project.
Speaker:Tackling projects as smaller pieces and measuring the results and the outcomes
Speaker:and, and recognizing that it's okay to make mistakes and to have failures
Speaker:because those are opportunities to learn.
Speaker:You're learning.
Speaker:This is all new to us, right?
Speaker:And that experimentation and exploration, I think it's very important.
Speaker:So as you expand into the business the different areas or opportunities for AI,
Speaker:I think it's important to pause and kind of assess, well, what, what did we get
Speaker:from AI in this particular part of the application or the business challenge
Speaker:that we're solving for before branching out and expanding it in the business?
Speaker:I think that's a worthwhile thing to do is to pause and reflect and then
Speaker:reassess your goals before you branch out and, and determine, well, where is
Speaker:the best bang for our buck, if you will.
Speaker:Where are we getting the most return on investment for this AI
Speaker:capabilities that we're investing in?
Speaker:Really good advice here is to be moderate.
Speaker:You know, it's like, it sounds like you're saying let's move forward,
Speaker:but not so fast that we're just throwing everything in all willy-nilly
Speaker:and don't know what's going on.
Speaker:I also really liked how you said that again, to not be afraid to
Speaker:try things, because even if it messes up, we just learn from it.
Speaker:I always say that mistakes are an opportunity to learn, or I tell my kids
Speaker:like, thank you so much for giving me so many chances to practice patience.
Speaker:You're so good at letting me be patient, but it's true.
Speaker:You know, all of these roadblocks can actually be something that
Speaker:turns into something really great.
Speaker:Do you feel, you know, we're kind of talking on the, a little
Speaker:bit of the challenges side here.
Speaker:Are there things that you think companies kind of believe or, or fundamentally
Speaker:think about AI that maybe is wrong or even that makes their operations worse?
Speaker:Have you seen AI initiatives, I guess, that have just really flopped Any
Speaker:lessons we can get there when we're talking about learning from our mistakes?
Speaker:Yeah, I think the thinking that AI reduces a need for humans or
Speaker:that it can replace humans, so I think that would be a mistake.
Speaker:I think there's still a very strong need for domain expertise and
Speaker:especially in shipping and, and in, in ERP, enterprise resource planning.
Speaker:So we have domain experts in these different functional areas, and they're
Speaker:very important, so AI cannot replace them.
Speaker:These domain experts help to define problems for AI.
Speaker:They interpret its outputs and they validate its results.
Speaker:'Cause remember, AI can hallucinate.
Speaker:We still need the humans.
Speaker:So it's not like we're going to put AI on autopilot, autopilot, I would say.
Speaker:We still need these domain expertise.
Speaker:So if we're thinking that we can just throw AI at any problem
Speaker:and that we can replace human beings, I think that is a mistake.
Speaker:And that's what AI and operations where it can just go wrong.
Speaker:AI can help us sift through all that data, help us to interpret
Speaker:the data and ultimately arrive at better decisions quicker.
Speaker:But I mean, humans are still in the driver's seat.
Speaker:I mean, AI capabilities will evolve.
Speaker:They'll get stronger.
Speaker:But we're the ones that are still driving what we use the AI for and interpreting it
Speaker:as results and identifying critical areas where we can leverage this capability.
Speaker:So I think that's really important, Lori.
Speaker:I 100% agree on that.
Speaker:I had actually recently talking to someone whose company made this very mistake.
Speaker:Really, they got rid of a whole bunch of a department thinking they could
Speaker:switch it with AI, and it was a disaster, and now they're trying to rehire
Speaker:people, bring in temporary workers.
Speaker:We're just not at that spot yet.
Speaker:As you said, it may evolve at some point, but right now there are no AI
Speaker:technologies that I have seen that can fully replace humans in our industry.
Speaker:So be really cautious about that talent and the humans behind
Speaker:it is such a valuable resource.
Speaker:So if we're gonna be cautious somewhere that is really good advice.
Speaker:I'd love to hear we're just about out of time, but I would love to hear
Speaker:from you two things before we go.
Speaker:First, tell us about what Acumatica is doing with AI and maybe just a little
Speaker:bit of overview so people can be excited.
Speaker:And number two, any final advice?
Speaker:If people were gonna walk away today and do one thing, what would you want
Speaker:them to do to embrace AI or, or change the way that they're looking at things?
Speaker:So you'll see from release to release Acumatica is bringing a lot
Speaker:of AI capabilities to our customers.
Speaker:So we'll have automation, so I mentioned the anomaly detection, the
Speaker:pair of eyes in the back of your head looking out for you to catch certain
Speaker:situations so you can course correct.
Speaker:So we already have that in our product.
Speaker:AI assistance.
Speaker:So providing you assistance while you're working, for example.
Speaker:So you can ask it questions, it will look through your Acumatica
Speaker:data and provide you answers.
Speaker:I think we're also looking at ways that we can bring our customers
Speaker:into this development cycle.
Speaker:So we do do a lot of outreach to our customers.
Speaker:We visit them we do user research and we involve them in these AI initiatives.
Speaker:So a lot of our AI initiatives that we've developed, it's been with the
Speaker:help of our customers who have been these early adopters, providing us with
Speaker:feedback so that we know that we're solving the right problem for our
Speaker:customers and bringing value to them.
Speaker:So.
Speaker:We follow our own advice.
Speaker:We don't just throw AI at anything.
Speaker:We use it very focused way to solve pragmatic problems for our customers.
Speaker:So we really are concerned about bringing value to them and
Speaker:solving these real world problems.
Speaker:Yeah, I I love that.
Speaker:EasyPost is a really similar mindset.
Speaker:That's why I think we're great partners.
Speaker:But AI is becoming integrated in such a way that it's just part of EasyPost.
Speaker:You know, it's not like this add-on, buy on, oh, and here's a side AI product.
Speaker:And I think that's really how life's gonna be moving forward.
Speaker:You're in your, your platforms, you're in your work, and there's AI helping fuel
Speaker:that and run things in the background so that you can get the answers.
Speaker:I see that as where it's going in the future.
Speaker:So, really cool opportunities.
Speaker:Dana, so, one piece of advice.
Speaker:So I'd say start with one to two high impact, low risk use cases.
Speaker:Make sure that you set those OKRs, which are the objectives and your key results.
Speaker:Look for something that's repetitive, measurable, and already structured.
Speaker:'Cause remember we had talked about that, so we wanna avoid those mistakes.
Speaker:So a good example would be like shipping delays, your ETA prediction, optimize
Speaker:carrier service selection, anomalies, and using AI to assist you in decisions.
Speaker:So that's where I would start.
Speaker:I would clean your data.
Speaker:For that first use case so that that model isn't working with
Speaker:that garbage in, garbage out that we were talking about earlier.
Speaker:And I'd also measure your outcomes and iterate.
Speaker:'Cause remember, you're gonna make mistakes.
Speaker:You're learning, right?
Speaker:And if you're not making mistakes, you're not learning like you had said Lori.
Speaker:So I think that's really important.
Speaker:Celebrate your successes and treat failures as a learning opportunity,
Speaker:not a reason to abandon AI.
Speaker:Yes, I, that is so, so good.
Speaker:Everything is perfect there.
Speaker:Start small.
Speaker:But boy, when those wins start adding up and you're celebrating, it does give
Speaker:you kind of a high and you're excited.
Speaker:Like my eyes have been open to all the crazy new possibilities
Speaker:that there are with AI.
Speaker:And that is the fun, fun part of AI.
Speaker:So Dana, thank you so much for being here.
Speaker:This has been fantastic.
Speaker:What if somebody wants to learn more about Acumatica or if they wanna
Speaker:connect with you, if they have questions about AI, how could they do that?
Speaker:Sure they could go to acumatica.com and learn more about us there.
Speaker:You can also join our Acumatica community.
Speaker:You can be a guest.
Speaker:Sign up as a guest.
Speaker:And you can also reach out to me at dana.moffat@acumatica.com.
Speaker:Perfect.
Speaker:That is fantastic.
Speaker:And community, keep working on it.
Speaker:Don't ignore AI just because it might be a little scary sometimes.
Speaker:Dive in.
Speaker:It is exciting.
Speaker:Thanks again, Dana.
Speaker:Thank you, Lori.
Speaker:Bye-bye.
