Hi everyone, we are so glad to be with you today to talk about AI in the world of work

management. This is something that is really interesting. We often think of AI in the sense of

generative AI and content creation, but there's huge benefit and application in bringing the

capabilities of AI into the way we enable work each and every day. So Scott and I are really

excited to talk to you about that. We're going to share some theory. We're going to talk about

practice and practical applications, because Scott is using many of these capabilities in his day to

day work today. But I wanted to start with some introductions so you know who we are. I'm Corey

Wolf, I'm a principal product marketing manager at Adobe. I've been in the marketing space for more

than 30 years. Sometimes I hate to admit that, but it's true. I've been with Adobe for nine years. And

a fun fact is that I am a work front boomerang. I was with work front before they were acquired. I

came to Adobe and when Word Front was acquired as a key linchpin to the Adobe portfolio,

I made sure I could get back on this team because I'm really passionate about the product. I think

it has such a relevant value proposition. Eliminating work chaos is something I'm keenly

interested in doing, as I'm sure all of you are as well. So I'm excited to be here with you today, and

even more excited to have Scott Maus joining me. And I'd like to give him a moment to introduce

himself. Thank you Corey. So I'm Scott Morse, as you mentioned, and I work for

ThyssenKrupp system Engineering. So we build assembly lines for automation for many industries.

So we work front more in a operations and manufacturing aspect than marketing. So we have a

lot of great use cases and AI has really helped us. We're going to cover some of that, but I've

been in operations and manufacturing for over 25 years. A work front sysadmin for six years. And

right now I'm leading our AI and our robotic processing initiatives within our companies. We

have several actions going on within our company that we're taking part in and trying to improve

our workflow, and Adobe is one of those. I have partnered up with many of the Adobe AI engineers

in exploring some ways in which we can make AI do more things for us. So it's been exciting to work

behind the scenes and trying to build things up that may be coming in the future. Thank you, Scott.

And I just want to reinforce that last point he made. Scott is on a first name basis with the AI

engineers at Adobe that are developing and refining the capabilities we're going to talk

about today. And as we've been preparing for this presentation, it's been really fun for me to see

the depth of his knowledge and how he's sometimes aware of things even before I am. So it is a real

privilege to have him here sharing both his knowledge about Adobe's plans and his expertise

as a practitioner using them. So this is our agenda. We're going to talk about AI's

role in the future of work management. Then we'll cover some work front AI features that are

currently available, and that you can all go try out immediately after this session. We'll tease

some upcoming work front AI features that we're very excited about. And then before we hit Q&A,

Scott and I have each curated a list of tips and tricks that we think are going to help you on

your journey to AI proficiency. So let's start with how AI is

transforming the work management landscape. Like I said earlier, I think we're all very familiar with

generative AI, but when you think about AI as a way to automate tasks, to to

enhance processes, to optimize the way we get things done, the potential is just limitless. And

so we're seeing huge interest in AI driven transformation in marketing organizations and

beyond. So this is really unlocking a new era of marketing productivity. And I think this stat is

very interesting. In our 2025 Digital Trends report, we found that more than half of senior

executives who are using AI report significant improvements in team efficiency. And this is

remarkable because AI is a relatively new technology. I've seen many transformative

technologies in my time as a product marketer, but nothing that approaches the scope and the scale

and the breathtaking speed of AI. And so what we're finding is that teams are feeling

urgency to get on the bandwagon, to start using it, to begin to understand how it's going to improve

their speed and scale, because without it, teams will struggle to keep up. And we hope this session

is going to help you in that quest to get ahead of the curve and to do some really great things

with AI that will make you more efficient than ever. So one thing we get asked quite often is

when should you invite AI to the table? We all know that that AI has application in many, many

places, but there's also a fear that it can do everything, that it can take over. Every process

and task that humans are accustomed to doing that simply isn't true. We really view AI as an

augmentation of human capability, and something that helps automate away the repetitive or time

consuming work that takes away from strategic pursuits. So that's the first thing. If you have

tasks that are repetitive, that are time consuming, that are laborious, that are preventing your

people from doing what they do best, that's a perfect time to bring AI to the table. The second

use case is when a task is particularly data heavy. AI is brilliant at mining data,

at collating and collecting information from many different sources, and synthesizing it so it can

be actioned upon. And that's the second case where you should absolutely not hesitate in bringing AI

to the table. The third use case is when you have a need or a task, or a process

that is rule based, but still requires some flexibility, in other words, some contextual

relevancy. AI is definitely capable of this, of applying the rules, but looking at a little bit of

nuance and context to ensure that the right result is achieved. And then finally, when you're

bottlenecked by human capacity and I think this is something every single one of you is probably

nodding your head at. We are getting more and more pressure to generate more and more output.

Whatever your industry, whatever department you work in, we are all being asked to do more than is

than we are humanly capable of doing. And that's why we need AI to come in and help in the areas

where it is best suited to do the work, and we can continue to do the things that humans are

uniquely capable of doing. Now, this is a list of some work front AI features that are currently

available in the product. Smart filters, catch me up summarization and as a non numbers

person, my personal favorite formula generation. But instead of talking about them generically, I

want to have Scott talk to you and show you how he is using them in his work at ThyssenKrupp

today. Thank you Corey. So as I mentioned, we use our work front instance to run

our entire operation. So that means every department from the beginning to the end

manufacturing health and safety. So we have a lot of tasks. Some of our projects have tasks upwards

to 200 for each project within a program. And we can go into greater detail on that. But this is

about AI. So let's talk about that. So AI helps us very quickly summarize where we're going and what

we're doing within a day. So in this first one we constantly have this debate within work front on

whether we use the homepage or priorities. But we have found that priorities really helps us out

due to the AI features that have been built into the priorities. First of all, in filters, you can

see here we have a filter screen pulled up in which we can use AI to do some kind of natural

language filters if you want, but also there's some suggested filters that are shown here on the

screen. So if you're looking for a task or a project, you can simply type it in. Or if you want

it to summarize certain things, you can do that here. But then the next feature, which is really

nice, is Catch Me Up. So if you've been away for a few days, or if you need to kind of figure out

what you've done over the last few days, you can use the Catch Me Up feature. So you just simply

click on it. A window opens up, which is our AI window, and you can type Catch Me Up. You can

summarize the last 24 hours, the last day or the last seven days. So if we take a look and we click

on the last few days, we can see that it goes through each of the different projects that are

shown in the screen to the left, and kind of gives you an update of what's going on in those

projects within the last seven days. So if we look at the next one, there's actually a little bit of

activity, more so than the other two. But here we have there was two new comments on the project,

and it gives you a link that you can quickly link. Click the link and get to it. So it's a great

feature to summarize your work really quickly. If you have a lot of tasks or projects that you're

participating on. So the next feature is summarizing, which again will also show you a

different way in summarizing, but with the AI assistant, if you have a project or a program that

has many projects underneath it, or a project that has many tasks it can very easily summarize. This

screen is showing us here that we're summarizing a program, and it will just give us a high level

view of what's going on within that program. If you click again, we can kind of see all the

information that it provides us when we say summarize this program. If we go to the next

screen, we're going to see a project. So now let's summarize a project. And as I mentioned our

projects. And you can kind of see by some of the task numbers there that our projects have about

200 tasks. So it's a lot of information that a project manager will have to go through to kind

of see where the project is heading. If we hit summarize the project, we see something very

similar. Then when we summarize the program and we get a little bit more information, though about

how each task is progressing or those that are late, some comments that were made, but it gives a

project manager a very high level view of how that project is performing. This has been very

helpful with our project managers as they start to get ready for project reviews with our

executive team. Another area of AI that's really exciting for us that helps us as sysadmins is

formula generation. So sometimes only a formula generation can really get you tied up, as they're

not always the same. And you might get one thing wrong or a little comma in the wrong place. Here

in this example we use date diff, so we just ask for it to create a formula for the difference in

the date and the generate of the formula for us. So we were able to put it in. Now let's say you do

something a little more difficult and you maybe forgot something. And you see in the bottom you

get the little red box that says this is an invalid custom expression, and you're looking and

you just can't figure it out. So you can use AI to say, rewrite the formula to remove the invalid

custom expression, which we've done. And now we've got a new expression or a corrected expression

which now works. So AI has helped us quite a bit in speeding along our custom fields when we're

trying to do some of these formulas. So now let's talk a little bit about prompting.

When we use AI, prompting is the key to getting the answers that you want, And some of us have

experienced this with other software programs. But the art to getting the answer that you want the

first time is to understand how to ask the question. So some of the key basics in prompting

is start with what you want. What are you object or formula or something like that that you're

going after. So simply put it in the beginning. I want a formula and then give some details about

what you want. So identify two fields or maybe another object. And then also if you give AI the

expected result, then it can check itself to see if maybe it's getting the right result or not. And

if not, it allows you to rephrase or ask additional questions to potentially refine your

list. What's key is prompting may seem technical, but it's an art, and one of the best examples

that we have for that is to share your artwork as if you were to draw a picture or something of

that nature. In our company, we have a bulletin board in which we share prompting examples so

that others don't have to try to create and get the same result as maybe their neighbor did. Here

are some examples of some prompts to share with you. So create a formula that shows or help me

find who is subscribed to my project. Generate text multiple username into initial report. These

are actual examples off of our bulletin board that we have shared with our colleagues within

our company. Now I'm going to turn it over to Cari to talk about AI agents. Thank you so much, Scott. I

just think this is golden information from someone who is really ahead of the curve, who is

using AI in context. You were able to see Scott's actual project, his actual

programs, and the way AI is coming into play to make he and his team even more efficient

than they they already were. So, Scott, thank you. Really appreciate you being willing to to share.

Um, yes. We wanted to talk a little bit about agents. This is something you're probably hearing

a lot about. There is generative AI capability, and there are AI agents which

are essentially collections of skills. You could think of it as a collection of skills or

intelligent operators that are capable of helping you to interpret your goals,

create and take action on plans, and even work independently in addition to alongside

you and your team and agents can can follow a spectrum so it ranges from the

low end, which includes things like single step responses or activity that is specifically

directed by humans, and that is grounded in more generic or publicly available data all the

way to high AI agent capabilities that do multi-step reasoning, that can

take autonomous activity within boundaries that you set, and that are grounded in your own

proprietary data or contextually relevant information that you have fed into the system. So

this is a really interesting way that you're going to see a lot of of organizations, including

Adobe, bring AI capabilities to market. And so we'll be releasing the

workflow optimization agent, which is going to include the skills that have particular

relevancy for work management and automating and optimizing processes. So one of

these is smart Sort. I wanted to give you a quick look at what this means. It's essentially an

intelligent way of prioritizing your task list or your to do list. As a user today, that's typically

done based on due date, which is a very good default. It's something that that makes sense for

a lot of people. But again, there's a lot of intelligence in the work front system that can

add to that ranking and make it a lot more nuanced and useful. For example, in

in this case, the tasks have been reordered based on things like, um, tasks that

are blocking someone else from completing an important task, or tasks that will require an

approval process that might add a few days to the the expected time frame, depending on how

quickly the reviewer can respond. Maybe this is a project with very high

priority, or your focus is high on this particular project. You're in the zone, and it just makes

sense to do a few more of these tasks while you're at it. This is a really, really key way of

getting the most productivity out of each and every person on your team, and helping them see

how much they're adding to the organization's success and business goals. The next capability is

Project Health. And Scott alluded to this. When you are wondering how a project is doing, it's very

easy just to look at the the system and say, well, everything seems on track. But I think what we

have learned is that on track doesn't necessarily tell the whole story. So this capability, this

project Health advisor, is capable of giving you a score, a Project health score, which you can see

here based on the schedule, the scope and the budget or the resources. So if you're finding that

the project is not where you want it to be, you can drill into those three areas and see, hey, the

schedule looks particularly at risk here. Let's find out what's going on. And it will tell you

things like, um, several tasks have been moved out, so they were underestimated to begin with,

or a lot of tasks have been added to this project after it was created. So maybe it wasn't. It wasn't

scoped properly. The really beautiful thing is that in addition to telling you what's going on

with the project, it gives you the ability to take action. For example, if a schedule is

is at risk because a person is over allocated, instead of having to go into the resource

management portion of work front and and find someone else to reassign the task to this project

health advisor is going to make a recommendation and give you the opportunity to activate it right

there in the AI assistant panel. So really, really powerful stuff. The next area

for workflow optimization is review and approval. And I think we all know this has become kind of

the new bottleneck as generative AI increases the amount of content that that can be created

by creative organizations and marketing teams, review and approval becomes the next bottleneck.

And it's more important than ever when you're relying on AI to create content, you need to

ensure that content is meeting your brand guidelines and is suitable for activation. So in

this case, what you can do is upload your brand guidelines into the system and then create a

reviewer just like you would a person that essentially encompasses those brand standards, you

can then assign that brand reviewer to review a piece of content it will go through

and compare everything it knows about the imagery guidelines. It will make comments, it will

say it needs work. It will tell you. In this case, for example, we like active imagery, not passive

imagery. So we need the designer to go back and take another crap. Again, this is not intended to

replace humans role in review and approval, but rather to ensure that some of those basics like

logo placement and image guidelines are where they should be. Before you have people take time

to review a piece of content. Our customers are really, really excited about this capability. The

next thing that I wanted to talk to you about is AI powered briefs. Now we all hate

duplicate data entry. There's nothing worse than being asked to enter data that you've already

created in other systems or in other formats before. In this case, you're you're going to

be using information that you've already documented to. Create a brief to kick off a

project so you can upload a PDF or a PowerPoint or a word document. It is going to compare

the information in that document to the custom fields in your brief, and it will populate

everything that it can find a match for and give you a chance to review that information. So again,

a very quick way of automating automating away the mundane. Kicking off a project quickly,

ensuring accuracy and eliminating the time lag and the error that can be introduced when you're

asking people to duplicate information that already exists. So these are some some teasers. We

wanted to make sure you're aware of things that you can be looking forward to in the very near

future with work front, but with that, I wanted to invite Scott to share his top three tips. I know

there's a lot of information here. We wanted to just kind of round up the three things each of us

think you should be focused on in doing right now as you as you exit this session. So, Scott, over to

you. Sure. Thank you. So again, as I mentioned in my or earlier, my presentation, understanding AI

prompting, mastering the skill of how to ask the questions and share your artwork will help you be

very successful in using the AI keywords when using prompting will help you and also again

gets you to the artwork of prompting. If you go to Experience League, they've already given a few

ideas of what keywords to use when you do the prompting. The last thing is AI feedback. So

AI is only as good as the feedback that we give it. If you've seen throughout these demos that

there was a thumbs up or a feedback button, give it it's thumbs up or thumbs down and give the

feedback. The AI engineers truly use that feedback to continually improve AI and teach it where it

did things right and did things wrong to get better results. This AI is learning every day. It's

new to the work environment and so it still has a lot to learn. And you're part of that learning

opportunity by providing its feedback. That is so true. Scott, we we sometimes talk about AI

as a child that needs to be raised, that needs to be nurtured, that needs to be taught. And so the

more you use it, the smarter it gets and the more it will be capable of helping you. I should say

too, in our tips you'll see some underlying content. These are links that will populate, so you

are able to access that information so you can look in the chat for those those links. Here are

my three tips. First of all, there is an Adobe AI writer that is required to use all that basic

AI features. This is a document that your organization needs to sign, and your legal or IT

team might need a bit of a heads up, or they might need a bit of runway to complete their due

diligence. So what we find is that it's really great if work front users are

asking their work front admin. Have we signed the AI writer? And if not to give a little nudge to

make sure that process gets underway, you don't want to have all the interest and all the need to

use these capabilities and be be delayed because that writer hasn't yet been signed. So the sooner

you get that started, the better. To help you do that, there is an AI security fact sheet that

Adobe has produced, and then a Harvard Business Review piece on the unique way that Adobe

approaches AI security and risk that you can share again with your IT team or your legal

organization just to help build confidence in all of the care and thought that has been put into

the way Adobe as a whole is approaching AI. And then my final tip is to implement AI with

workflows that you have already optimized, that are clean, that are working the way you want them

to. If you overlay AI on a broken process, you're just inviting more chaos. So our

recommendation is to clean house and then add the the new decorations or the new furnishings.

That's definitely the way to go. And our final recommendation is to just get on the AI bike.

This this image is really familiar. We've all seen kids that are in such a hurry to get where

they're going that they're running alongside their bike instead of hopping on, taking the time

to get on and pedal and and trust that they will get where they need to go more quickly that way.

So we encourage everyone to get on the bike to start your AI journey, to begin learning, to

experiment, to see where you are, finding particular value, to help the system get smart, and

to roll it out in ways that make sense for your Organization and as a final call to action. There

are a couple of things that Scott and I talked about that we think would be most beneficial. As

you as you, um, finish this session and look to take advantage of the things we've talked about.

The first is to click on the AI assistant button in work front. This is going to open up that panel

in the right rail and give you access to summarization and formula generation and all

of the things that Scott showed you earlier. The second thing is to try out the catch me up button.

It's just such a simple way of seeing what the system can tell you, whether you've been out of

the office or not. See what it can tell you about what's happening with the project. And at a glance,

bird's eye view is so valuable. So those are two things you can go click on right after this

session. Try it out, get on that bike. And so with that, we're really happy to have shared some

information. We hope it was helpful. And now we would love to take your questions and see what

you would like to know more about.

Oh my gosh. Corey Scott, my head spinning. There's so much information that you guys shared. Thank

you both for being here. This is a really great meaty topic, and we're so happy to have been able

to share some time with the group. We're really looking forward to hearing your questions and

helping you explore this topic a lot more. All right. Well, the the chat is on fire. There are. It

took a minute to get you guys warmed up, I have to say. But once the questions started coming in

there's so many. So we're going to do our best to get to as many as we can. Keep typing them in. If

you haven't asked your question, um, Scott, I'm going to take the first one for you. There's a

question that says can catch me up. Also summarize custom fields and forms. Or is that only native

fields? Yeah, that's a great question. And catch me up. We're only looking at the native fields within

word front. It still hasn't gone to the custom fields quite yet, but just keep that in mind.

There's a lot of development going on, but it's really focused on the native fields at the moment.

Got it. That makes that makes sense. Uh, I'm going to keep it moving. Corey, I have one for you. That

came in pretty early on, and this one is do you have to have the AI assistant for all these

examples? That's a really great question too, because the AI assistant is something that is

native in all current work front packages. So that's going to include things like the formula

generation, the summarization, the catch me up and the access to documentation and

project history. So if you're on a current package that is going to be available to you as part of

the AI assistant, what is coming is the workflow optimization agent, and that's

where you're going to get capabilities like the AI reviewer, Project Health, and some of those

other coming features that I showcased later in the presentation. That's all very

exciting. Thanks, Corey. Uh, Scott, this one's for you. We're getting technical. I know you're ready for

it. So, uh, this question came in. That said, if you ask the AI for a formula, that's not possible. Does

does it alert you that it's not possible? Or does it output a formula that simply has no function?

This is a common problem from ChatGPT, for example. Yeah, the AI system is continually learning. So if

you type in a formula, it depends on the object that you're in and whether it's going to

understand what you're trying to do or not. If it gets confused, it will simply tell you, I don't

know. I can't help you, but it can generate a formula that it thinks, knows what knows what you

want. And then when you put it in your custom field or wherever you're popping your formula in,

it'll tell you it's an invalid formula. So you could start to get into a little bit of a circle

with it. But for the most part, it's pretty well tuned in to the formulas and where they are

within the objects. but again, remember to always give it feedback. Thumbs up, thumbs down and reply.

Because that's how the engineers try to eliminate some of these problems within the AI assistant.

That's actually a really good point. That feedback not just for the AI, but just the feedback for the

engineering teams that are working on it too. That's that's a great reminder. Um, speaking of

learning, Carrie, I'm going to send this one to you. Um, this question says, is there a way to feed the

AI industry? And more importantly, oh, sorry. Is there a way to feed the AI industry and more

importantly, company specific information? Not the AI industry, but your own industry and company

specific information to give the AI more context of the information it has access to and work

front. For example, this type of info would be maybe the roles in your company and what each

role is responsible for. That is a really great question and something I see us moving into more

fully over time. Right now, the AI capabilities are largely mining intelligence that's

already in the work front system based on project history, based on the data that that has been

captured from historical projects and things like that. Um, the one area where we are

definitely working from information that you can you can supply to the system is the

AI reviewer because it's based on your brand guidelines. So in that case, you do ingest your

brand guidelines into the system so that it has the information that's tailored to you, that it

needs to make sure that that preflight check is accurate and is going to catch anything that's

important for your own brand standards. That's super helpful. I there's a lot of these questions

about kind of what what it's learning and kind of how we're how we're continuing to interact with

the with the AI. I think there's a there's another question here. This one, Scott, this one is kind of

similar. It's about learning from previous projects, but it's more specific about if you have

to set up the priorities. So the question is, does the agent learn from all previous projects, or do

you have to set up these priorities? That's also a very good question. The AI is constantly

learning in the engineers. So as I said earlier, I'm fortunate enough to work with a lot of the

engineers not only at Adobe but in other products in the AI is constantly learning and they're

watching what's going on in the interaction. So again, I can't stress enough the feedback, but it

is learning your projects and things that you've done previously to help you start to grow and

develop the AI assistant. But keep in mind it's the AI assistant on the Adobe platform. It's not

specific to your company or to your data that's within your system. Got it. Yeah,

I feel like a lot of the questions are kind of falling into the two buckets right now of kind of

the, the how the AI is still learning and then the other ones. There's a lot still for you around

kind of what's available. And someone did just ask a question about. Can you remind us what are the

two features that we can use right away? And does that writer still need to be completed for those?

Yes. The the Catch Me Up feature is available right now, and everything that's included in the

AI assistant, which includes the formula generation, the project summarization, the ability

to kind of ask natural language questions to to gather information about projects,

issues, tasks and to access experience league documentation. So those are available

today. And you do the best practices always to have the AI writer signed,

because it's absolutely a requirement for some of the the workflow optimization agent capabilities

that are coming, like Project health, like the AI reviewer, like being able to use an

existing document to populate a brief or a request. So my recommendation would be even. Even

though you're going to be able to access some of those basic features without the AI writer, please

make it a priority to get it going in your organization. Like I said, sometimes that can take

some time and it involves other functional groups. And I think the sooner you get that going, the

sooner you can take advantage of the more advanced goodness that's coming. Yeah. Just one

thing to add to that too. On top of the writers, you also have to be in the unified experience. So

those that haven't converted to the unified experience will not be able to get to the AI

quite yet, because again, it's sitting on an Adobe platform. And so it needs to be able to

communicate through the unified experience. So that's another key point. On top of the rider. That

really is important. And and Kristen, maybe I'll just jump in and and add on to that a little bit.

I think a lot of people are wondering how how do I get access to these features beyond signing the

AI rider? Um, you need to be on Adobe's identity management system. The vast

majority of our work front customers have already been through that process. You also need to be on

Unified Shell, which is sort of like a unified product navigation for Adobe Solutions,

and that is a requirement for these advanced AI features. You need to you also need

to have signed the writer like we've reiterated but can't reiterate enough. And then for the AI

reviewer, you also need to be on unified approvals. And I think that might be what you

you also were referring to. Scott. So you need to be on unified approvals. If you are not or you

don't know, you can check with your sales rep. It's a very simple process to turn you on. So we have

made it as easy as possible to get you going on these new features. And this AI reviewer

just went into open beta last week, so you can take advantage of it right now. If you just make

sure those four prerequisites have been met. There's a lot of goodness. I know that some people

have said, well, we'll wait. We'll do it a little bit later. But truly, I think the the bulk of

customers are now kind of it's been a few years since Work Front has been acquired, and we're now

seeing a lot of folks over on, on Unified Shell over on Adobe IMS. So thank you for those that

have done that. And there is a session in today's skill exchange, by the way, on unified review and

approval. So if you're wondering what that is as well stick around. There's a session on that today.

Um, Corey, this is a bit of a follow up to that kind of what you were just talking about of, you

know, you know, we've got the IT writer signed. This question is about sandbox asset access. Once the

rider is signed, can can it only be turned on in the state? Oh, I think they're saying can they turn

it on in their sandbox first just to test it there before pushing it to production? No, we're

we're feeling comfortable with it in production. It is an open beta. So we we have a few things

we're still kind of finalizing, but it's very solid. We think that the best thing is to get

users using it. Again with AI, adoption is is the key to realizing value, getting people using it,

providing that feedback, making sure that the system is learning as you're using it. So we're

looking and we think it's to your benefit to open the aperture a little wider, given that it's AI.

That's fair. Yeah. Uh, Scott, I've got two questions coming your way, both a little bit more technical.

One is about fusion. Uh, I, we I know you've done a little bit with fusion, and so this one is how is

the AI assistant working with fusion technology to enhance automation in workflows? Great question.

And we are in fusion and we use this quite a bit. Uh, it's not as mature as in work front. I think

work front is a little bit further along in the assistant. Uh, it does kind of help you navigate

through, you know, some of the modules a little bit, but it's still learning. I think it's, um, if you

look at what grade level it is, it might be entering middle school at this point. And it's

learning opportunity where work front might be entering its freshman year in college, so to speak.

Uh, but again, we use it. We keep giving it the feedback because we want it to grow to help some

of our more inexperienced fusion developers within our company. That's great.

Corey, there's one follow up question for you on that last question that someone said, what is

unified experience? How do we know if we're on it? This tells me this person may or may not be there

work for an admin. So what would you recommend to know if they are on or what is unified experience?

Yeah, sure. The the unified approvals experience. Um, as many of you may know today,

you can do approvals in two ways. You can do them on on documents, or you can do them on

generated proofs. We have unified that experience. So it's really one path. It's based on

Documents, and that is where we're building all future functionality, including

enhancements to the viewer, including connection with frame IO. So you want to be on that,

that unified document approvals. And again, it's just a toggle we turn on in the background so you

can talk to your account rep if you want to know if you're experiencing that. But if you're

generating proofs in work front proof, chances are you are not. And you'll want to look into that. And

that is exactly what the next session is going to be talking about. So not to tease what's coming up

next, but if you are asking that question and wanting to learn more. Micah Bozak is speaking

right after this session, and she's going to be talking about that, that unified approvals

experience. All right. It's got one more technical one for you. And that is, um, the question around,

can AI generate a report for a portfolio and all the projects under it? AI at this point is

not generating Reports. It's simply helping you get to experience league formulas, maybe looking

at project Health. AI is strictly object focused at the moment and not generative, so it's

answering questions that you can interrogate data or interrogate information, but it's not

generating at the moment. But I know a lot of people ask me, can project health look at at

higher order categories like programs and portfolios? And the answer is yes, because those

are objects like like Scott said. So projects, portfolios and programs can all leverage the

project health advisor that we showed you. That's a great follow up. All right. We are almost at

time. We have time for one more question. I'm going to do a speed round. This is for both of you. I'll

have Corey go first and then Scott. And this is just around your own personal use of AI. I'm

curious to know what are your most used prompts week to week? What are you using AI for yourself.

Okay, I'm going to answer this quickly, but in two parts. Um, inside of work front. I hate to admit it,

but the most common question is show me the projects that have executive visibility so I can

triage and prioritize on that on that basis. Um, just in terms of AI in general, because I think

we're all experimenting and using it in all aspects of our lives. Um, the, the marketing team

and myself have really been using it to prep for customer calls. So when we have a customer call, we

can say we're covering the work front roadmap. This is the organization, and it's going to go

mind a bunch of useful details that help us make that presentation as relevant and non generic as

possible. And it's been going really well. Awesome for us. I'm going to answer this in two parts as

well from a sysadmin. We use it a lot for the formulas. So in our business we have a lot of

custom fields and a custom calculations that we have to do. And since we've had the AI, it has

saved us an immense amount of time because now we don't even worry about trying to put the formulas

together. We ask AI very specifically based on the custom fields or the fields that we want to

calculate, and it generates a formula for us. And then the last item in the project management side,

our projects have many, many, many different projects underneath its portfolio. And they'll

interrogate and ask how the project performance is going. I love it. Thank you both so much. I it's

it's crazy that flew by. We are at time. I know we didn't get to all of the questions. I will tell

you a little bit more about this later, but we do have a user group coming up that we're calling a.

It's a mega user group with a bunch of different chapters. Scott is going to be there answering

additional questions. It's on September 10th. I will tell you a little bit more about that later.

But for now, Corey Scott, thank you for being here. Thank you for sharing all of these tips and

tricks with us today. My pleasure. It's been great to be here. Thanks for having us.