RAW FILE
Disability:IN Virtual Inclusion Works Meeting 2025
Session 1:
Artificial Intelligence:  AI is here!  Use of AI in 
Supporting Disabled Employees
Thursday, February 27, 2025
10:30 a.m. EST.

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This text, document, or file is based on live transcription.  Communication Access Realtime Translation (CART), captioning, and/or live transcription are provided in order to facilitate communication accessibility and may not be a totally verbatim record of the proceedings.  This text, document, or file is not to be distributed or used in any way that may violate copyright law. 
>> Recording in Progress.
>> ASHLEY KINGSTON: I'm starting now.  Hold on.  Disabilities@Work.
>> JEFF WISSEL: Artificial Intelligence:  AI is Here! Use of AI in Supporting Employees with Disabilities, is our title of our session today.  My name is Jeff Wissel, and I'm the Chief Accessibility Officer here at Disability:IN.  In my role, I consult with our corporate partners on enterprise accessibility for digital, mobile, physical space, and procurement accessibility initiatives.
I'm a white male in my late 50s.  I am legally blind with a degenerative eye disease, and I just got my first seeing eye guide dog, Gabe, in January.
We have a great panel today.  And we have amazing panelists.  We have Federica Terrenzio, who is Senior Director of Disabilities@Work at Salesforce.
We have Darren Rowan, Senior Director of accessibility at Eli Lilly.
And we have Matt Evans, head of EX product science at Qualtrics.
But first a few housekeeping items.  All attendee microphones are muted.  Please use the QA functionality if you need to communicate with our Disability:IN staff and our panelists.
You may need to reboot your computer or log out and log back into the session to resolve any technical issues.
CART.  English captions are available on screen.  Captioning in additional languages is available through the StreamText link which was provided in the meeting materials.
Asking questions.  Please submit your questions through the QA functionality throughout our presentation today.  And live Q&A will take place in the last 15 minutes of our time together.  We will answer as many questions as possible.  But, of course, we may not be able to get through all of them.  And the good news is that all sessions today are being recorded and will be shared later.
Now, to get on with our show.  This session will focus on how AI is being deployed at our panelist companies.  We are going to learn several ways how AI is supporting employees with disabilities.  And we are going to learn about some ways, tangible ways to overcome some of the challenges that are involved with deploying AI, artificial intelligence, at major corporations.
Now, for our panelists, we would love to have you each introduce yourselves and comment a little bit on what is the current thinking around AI and how it relates to accessibility and disability inclusion in your organizations.
Let's go in order of Federica, Darren and Matt.
So, Federica, over to you.
>> FEDERICA TERRENZIO: Hello.  Hello, everyone.  I'm Federica Terrenzio.  I'm a Senior Director of Salesforce leading Disabilities@Work within the Office of Accessibility.  I'm a blond woman wearing glasses.
At Salesforce, my team's mission is to create an environment where colleagues with disabilities, neurodiverse can thrive.  With that team, we try to design implementations of equitable and accessible process across the entire lifestyles, and we develop and manage innovative solutions, accessibility solutions to unlock productivity and performance, and I'm excited to be here and looking forward to great discussions. 
>> JEFF WISSEL: Thanks, Federica.  Darren.
>> DARREN ROWAN: I lead digital accessibility at Eli Lilly and company.  I'm a white man, based in the UK, I am British, and my pronouns are he/him.
I guess, Eli Lilly, like many organizations, AI has become ubiquitous, it's everywhere, there's a huge push on broad engagement around the topic and looking at it as how we can innovate around AI as much as how we can help it with our productivity.
In terms of what that means from a digital accessibility perspective, I think that we look at this in two ways really.  Is one, what are the solutions and the things we need to think about with regards to the employees that have disabilities.
And the second way of looking at it is around the solutions that we provide to our employees.  We want to create better solutions and more accessible experiences for both our employees and customers.
I can talk more about some of those solutions, but as we think about employees, essentially, you know, that goes from anything from the assistive technology that is more specialized, let's say, but also the common things that become more commonplace, like Copilot, for example, and how that is really benefiting people with disabilities.
And then when it comes to the enabling solutions, we are talking around things that are automation type tools, only for those that are in very technical roles, but development opportunities that we are bringing forward with our own in‑house AI innovation teams to really think about solutions that will help remediate some of the issues that we have today, like PDF, for example,.
So, I can talk more about some of those as we get further into the conversation.
>> JEFF WISSEL: Outstanding.  Thanks, Darren.
And Matt, how about yourself?
>> MATT EVANS: Good morning.  And good afternoon.  My name is Matt Evans.  There's my camera.  My name is Matt Evans.  I am a white male.  I live in Pittsburgh, Pennsylvania.  Greatest city in the world.  And my pronouns are he/him.
My role at Qualtrics is I lead what is called our employee experience product science team.  My team is responsible for a number of areas, thought leadership, such as global research efforts, the development of employee listening methodologies, as well as the support of the development of purpose built AI models that in turn help our customers.
In terms of some of the things that we are doing at Qualtrics, I would say that one of the benefits of being a software company is that we get to do quite a bit of internal testing and use with some of those AI tools that we are building with customers.
As a data oriented company, we have several teams that are dedicated to building our AI models.  So, internally for employee use, we have actually built what we call an AI playground.  Now, this is an internal gen AI space that has an interface that's very much like a ChatGPT but within our own internal secure Qualtrics environment.  Some of the benefits of that for employees, with varying abilities is people can distill complex concepts into something that they find more accessible and understandable.  People can check their own language for its accessibility and its appropriateness.  And people can actually build their own AI agents.
One of the cool ways that I have seen this used is that for our customer‑facing folks who are helping our customers build out their own research programs, they can upload best practices for accessibility and our own Qualtrics accessibility standards into a playground and ask that agent to review a survey instrument based on this content and actually advise on improvements.  They could do all of this again within a secure environment so we don't have to worry about sharing proprietary content or customer data with the world.
Then from a customer‑facing standpoint, Qualtrics offers something we call an expert review capability, which is an AI tool in our survey builder that diagnoses a survey, indicates questions that might be inaccessible and gives other recommendations for increased accessibility.
Additionally, we have data interrogation and interpretation tools like Qualtrics Assist, which is an AI tool.  It's a natural language data interrogator.  So that if I'm an individual or if I'm a manager who is looking at graphs and charts within the context of a dashboard, maybe I have difficulty interpreting numbers, maybe I have difficulty interpreting the visualizations, I can simply ask Qualtrics Assist things like, what are my team's biggest strengths, or what segment of my employees need the most attention, and they will get plain spoken narrative answers.  Those are a few of the things that we have cooking at Qualtrics that excite me.
>> JEFF WISSEL: Outstanding, Matt.  Thank you.  And I think what's so great about this panel is I'm sure all of us have been involved in a Qualtrics survey throughout our careers, probably many, many times.  I think everybody is very familiar with Eli Lilly and the pharmaceuticals and so forth.  And whether you use Salesforce in your organization for your client relationship management system, or you have benefited from some of the information Salesforce publicly makes available to help us all win in accessibility, we all have some skin in the game here with our panelists.  So, very excited about this.
What's really great now with the section we are going to go into is each of our panelists has something unique to share as it's related to AI in their organizations.  And let's go in the order of, we will do Matt, Federica, and then Darren.
So, Matt, you mentioned the Qualtrics employee experience survey.  Tell us what that is and then what you have learned about AI and the employees' sentiment towards artificial intelligence.
>> MATT EVANS: Yeah, great question.  I mentioned thought leadership and I mentioned that I work on the employee experience side of the business.  So, each year Qualtrics conducts a global panel study of more than 30,000 employees from all across the world.
What we have learned in that is that, first, employees' sentiment around AI is improving over time.  In 2023, we actually saw that more employees who we were able to reach out to and get their feedback from, were more worried than hopeful or excited about AI.  That was 2023.
In 2024, we actually saw that flip.  49% of employees all up are now hopeful or excited about AI in their workplace, versus just 21% who are worried or very worried, right?  And the other 30% are on the fence.  And that's a significant, what I would say is a change from what we had seen in 2023, right?
Gen AI coming on the market.  People are not completely sure about what this is.  Is this threatening my job?  People are now more hopeful or optimistic overall.
Now let's talk separate from that, let's talk a little bit about people with disabilities.  We asked two questions in our study around people's disability status.  The first of those, one was, do you have a disability?  And of those that responded that they do, we also asked, to what extent does your disability impact you at work?  Not at all, a little, or a lot.
The first thing that we find, which I would say is somewhat encouraging is that people with disabilities who say their disability impacts them quite a bit at work, they are actually more likely to be engaged at work.  When we say engaged, that means people who are psychologically and emotionally invested in their work.  So, people who have a significant disability that impacts them at work a lot, more likely to be engaged.  They are also more positive around other areas of their work, like technology, innovation and communication.
So, now I want to talk about that intersection of people with disabilities and artificial intelligence.  What we found regarding AI is that while there was actually little difference between people who did and did not report having disabilities regarding AI, when we look at those people who say that their disability impacts them at work a lot, these people were significantly more likely to actually be using AI at work on at least a weekly basis.  So, 55% of people who say their disability impacts them a lot say they were using AI on a daily or a weekly basis, and that compares with 45% overall.  So, significant difference in those two groups.
They are also more likely to be actually excited, right, not just hopeful, but excited about AI.  So, 20% of people on a continuum of very worried, worried, neutral, hopeful or excited, 20% of people with a disability significantly impacting their work say they are excited, compared with 15 overall, right?  So, I find that optimism to be really encouraging.
Companies that are able to effectively adopt AI across their organization are going to be those that I think are going to win in the long run.  When companies embark on any kind of major adoption effort, like an AI transformation, they need to find change agents, right?  And it seems to me that based on our data, that people with significant disabilities may be more willing to, than others, to embrace AI.  And if I were leading a digital transformation in an organization, I would really be taking notice of this.
>> JEFF WISSEL: Matt, thank you so much.  I didn't ask you this, and I don't want to put you on the spot, but I guess I am.  Is that survey, is that available to the public?
>> MATT EVANS: Yeah, I will be happy to share out the results of our annual trends for distribution to conference attendees here.  Happy to make that available to you.  And if anybody is ever interested in diving deep into the data, I am just a LinkedIn reachout away.  Love talking about this stuff.
>> JEFF WISSEL: Outstanding.  Thank you very much.
Federica and Darren, I will go, if you want to share anything, any thoughts about either personally or in the organizations about, have you experienced anything with employees with disabilities being more jazzed or using AI more than others in the organization, by any chance?
>> DARREN ROWAN: Jazzed, I love that.  Love that phrase, that description.  I am happy to say a few things about it.  Personally, I think, well, it's heart warming to hear that people with disabilities feel more optimistic.  I guess it doesn't surprise me because when I think about AI, the use of it, whilst it enhances some people's experiences generally, I think it can be life changing for people with disabilities.  You know, I think by my own experience anyway as somebody who is visually impaired, like yourself, Jeff, in the past I would have to ask members of my family, for example, to read this, can you tell me this is the right milk, can you tell me if the banana is ripe, all this kind of stuff.  Now I can pull out my phone and use an app that will tell me all those things and I have gained a new level of independence that I didn't have before.
It puts people on more of a level playing field.  Again, you can create those fancy slides that your sighted colleagues could because of Copilot or you can join conversations and larger discussions through captions if you can't hear quite so well, or you can summarize information more succinctly with many uses like Copilot, again.
So, I think that not only is it, you know, leveling the playing field, I think the productivity gains for people, which also then enables them to be more successful in the workplace and feel more competitive, some of the many reasons not only I have experienced, but many of my colleagues at Lilly have shared as well.
>> JEFF WISSEL: Thanks.  This is Jeff.  I whole heartedly agree with you, I geek out on AI on a daily basis.  As visually impaired individual, it helps me immensely.
Federica, I'm going to turn it over to you.  Will you share with us, you launched a product in, I think it was May of 2024, and it was really about providing an AI‑driven platform that helped employees to discover accessibility resources.  And it really made ‑‑ it helped to empower the employees and make them feel more comfortable when asking for an accommodation, which is like magic wand kind of stuff.  Take some time and walk us through that.
>> FEDERICA TERRENZIO: Yeah, sure.  Yes.  I think that we think, we thought at the time, we had critical challenges, right?  Because employees don't always, as you said, feel comfortable requesting accommodations through formal channels.  They are reluctant to share that I monitors with the chart, and I was very surprised within the research that actually stated that 76% of employees in corporate and companies are really reluctant to seek accommodations due to fear of stigma.
And this, of course, will impact workplace success because they cannot really get access to the resources or the adjustment in accommodations they need to be successful.
So, to address this, we took a universal design approach, trying to work towards removing barriers and ensuring that all employees could easily discover the support available to them.  And so we partnered with U.S.‑based company called Inclusively and we adopted their tool called Retain.  And with this tool, an employee can simply interact with the chatbot.  This is an AI‑powered chatbot.  They can describe their situations, their personal circumstances, the barriers they encounter, the frictions they have, and they receive personalized recommendations in realtime.  And these recommendations link directly to internal resources they can access straightaway.
And this has produced significant bureaucracy, because if they have a ticket, it will take at least 48 hours to fill this request.  Whereas, they can actually straightaway get access to those resources.  And ultimately we have seen that this is fostering greater self‑advocacy, especially for those employees who may not even realize what accommodations could benefit them.
So far the results are very encouraging.  We have around 300 employees of our colleagues that have registered and are actively using this tool.  The average satisfaction score is 8.4 on 10, that is a strong occasion that it's delivering real value.  And we launched in U.S. this being our biggest market.  But now since the tool is working and I think this maybe sort of confirm the idea that you were discussing before, that people with disabilities are very, you know, willing to experiment with innovative tool, and this is an AI‑powered tool.  And so we want to expand and we will be expanding globally next Monday, actually.  So, we are just there.
And this is just the beginning, I think.  As AI continues to evolve, we see great opportunities to further remove barriers and we feel more inclusive workplace leveraging this technology.
Another example that is just of these days, we are thinking about leveraging our internal technology aging workforce to support, to provide support at scale on Slack to our internal communities.  So, we are just in the middle of really thinking about that.
But we are really looking forward to expand the AI use cases further because I am really convinced this is something that is life changing for our internal communities.
>> JEFF WISSEL: I love it.  Thanks, Federica.  We know through the Disability:IN Disability Index that so many of you out there, over 500 of our corporate partners, continually take the Disability Index.  And we see on average less than 5% of employees self‑disclose.  So, Matt and Federica, what you guys have just described so far is the culture that all of this research and your tangible actions are taking to make employees feel more comfortable.
And when we ask for the accommodations that help us to not only perform the task of our job, but help us to perform at our peak, that's life enhancing.  So, it's incredible.  Thank you for that.
Darren, what a great segue, when we are talking about this.  Tell us about some of the myths around employees with disabilities and the focus that Eli Lilly has on the positivity of AI, while being intentional, and the benefits for the employees.
>> DARREN ROWAN: Yeah.  I think Matt sort of touched on it a little bit earlier, say, maybe a couple of years ago when this whole, you know, gen AI stuff in particular hit the news and lots of people were intrigued, excited and then people got quite nervous.  And I think the initial reaction was, is this going to just take everybody's jobs, and that sort of scare mongering type headlines.
And, of course, when you see headlines like that and people with disabilities see that, we always know there's a big gap anyway in terms of employment.  So, you know, when we are having conversations in many forums, you would see that that was coming along say, this is yet the tool that will further marginalize it.
As Matt hinted at with the survey results, that in reality, what starts to embed is the real benefits of AI.  And it's true, where AI is being used, say, in whole kind of job interviewing process, then there has been issues discovered and been shared around this in many companies where you have screening solutions that are too reliant on AI and because of the bias that already exists and the data that exists to go with that, then that cause issues.
Ultimately at the heart of any AI, regardless whether this is about disabilities or accessibility, you know, we have to have a good, robust process in place that really looks at the governance of any solutions and looks at the ethics that go with that, and ultimately apply a responsible AI approach.  And that's why I hope all organizations will do, you need to have that human oversight around checking those kind of data points and the testing throughout the process.
We have certainly been learning and implementing, you know, going through this iterative process in Lilly as it comes to that.
I think, you know, building on that, on the sort of things that I mentioned earlier around some of the solutions that we are trying to put in place, there's the obvious things where we have assistive technology that we have always had for some time.  But as we start to see that AI itself has just become integrated into so many of those things, it's almost a question of what doesn't include AI anymore.  And in that, you have then got to, obviously, bear in mind some of the things that need to be considered.  It's great that, you know, screen readers may have AI in there, which will help to read those elements that in the past were inaccessible.  But you still have to have the processes that you still follow generally in a company like ours, where you are assessing the level of risk and security and privacy and all those good things.  But you still have to have solid processes in your organization that will help when you want to introduce any new kind of software and assistive technology, for example,.
But other things in terms of trying to think about more innovative solutions, I guess, is asking questions around our employees, around what are some of the things that maybe you are using outside that could be brought in to help in terms of helping you be more productive.  And I think one of the things that we are seeing trending, I suppose, for want of a better word, is the use of wearables and things like meta glasses, for example, and various other smart glasses.  And what's interesting with those is that, like many things now, that they are a mainstream wearable.  They sold a million of these last year.  Where they integrate certain aspects like live streaming to describe what you are looking at.  You can start to see that these potential use cases for helping employees around your facilities, for example.
But like I said, with any of these, sort of, experimentations, we need to always check, you know, what are the potential security or privacy risks.
And I suppose on the other side of that, in terms of what I talked about, the enabling solutions, there are clearly systems that we buy in to help with automation and try to encourage the adoption of automated tools across the enterprise.  But for us, one of the things we are excited about now is our own in‑house tool that we have been working on that helps to remediate some of those problems that we might get when we try to put something in a PDF format and we find that actually has lost a lot of those accessibility things that was in the source document.  And so, you know, we really have tried to work quite hard to use things like AI vision to automate and fix that.
Because one thing I will say is that with any employee, they want to do the right thing, like any employee, we are all very busy.  But the more things we can give to people that will do a larger amount of the work for them and they see the results of that, they are encouraged then to do the other bits that might complete that to make it as accessible as it can be.  So there's some of the examples of things that we are, sort of, working through.
>> JEFF WISSEL: Outstanding.  Thanks, Darren.  I want to remind the audience, if you have any questions, please use the Q&A functionality and put your questions there.  And then in about 15 minutes, Joan will walk us through the Q&A part of the program.
This next question, next couple of questions is going to be for each of you.  And the first question that we have, let's go in order of Matt, Federica and Darren.
Can you share one other key learning that your organization has learned as they are rolling out or deploying AI?  Matt, anything that you can share?
>> MATT EVANS: Yeah.  Good question.  So, one of the things that I would suggest is that we start with trust rather than the technology itself.  We have seen this both internally with use cases, as well as positioning our AI tools, features and functionality with our customers.
When we start solely with the benefits of a specific AI feature, we find that adoption lags.  When we put things up front, like explainability, transparency, accuracy of tool output, as well as data security, we find that we get better adoption, better listening from our customers, who we are trying to nudge in the direction of using these tools, as well as subsequently usage by their employees.
You know, these things, these are really necessary components for people to change behavior, these elements of trust.  And I think that driving AI adoption is like any kind of sale, right?  People have to know about a tool before they like it.  They have to like at least the benefit of the tool before they trust it.  And but they ultimately have to trust it before they buy it.
So, again, heavy emphasis up front on elements of trust, whether it's the credibility of the tool, the security of the tool, and the beneficious of the tool to make someone's life better before specifically moving onto these technical benefits.
>> JEFF WISSEL: That's great guidance.  We always hear about the hallucinations.  Because it's out there on the Internet doesn't mean it's accurate.  So there is that trust factor.  Also, just it's something new and it's ‑‑ and I know folks who are using it really see the benefits of it.  But it's try it, you like it kind of a thing, I think is the rule of thumb.
Federica, how about yourself?
>> FEDERICA TERRENZIO: Yes.  Yeah, I can, sort of, cover some lessons learned that are more related to my experience with artificial intelligence, AI, tools implementations and the experience I was mentioning earlier.  And I think one of the biggest lessons I have learned over the past three years is the importance of embracing experimentations, when, you know, thinking about improving announcing the support for our disability community.  And also that means also when we evaluate tools.  So, for example, with Retain, the I‑platform I was mentioning, describing earlier, it took significant time and effort to implement and there were no guarantees of adoptions or success when we launched, there was no play group.  
So, we have final approach through (?) iterations.  And one key element that asked was getting some, you know, data around the adoptions of this platform.  Of course, the platform is, you know, we don't get any individualized data.  So we get aggregated data.  But still, this admin counsels provided us with really significant and meaningful informations about the usage, about the use of feedback, and this allowed us to proactively understand, okay, what is working, what is not working, what gaps are there.  And so we allows us to make the necessary adjustment.
One of the key, you know, lessons learned was about the marketing strategy.  And I think this is about what Mark was mentioning, about trust.  So, I would want to really drive adoptions, making sure that people felt comfortable using this technology, because we have done all the due diligence around privacy, around the trust of the platform itself.
And I think this experimentations and this flexibility was crucial for us to ensure that, I mean, this platform, AI platform was really meeting the needs of our employees.
Another lesson learned was that impact is not always about skills or should not be only measured by numbers, because as I was mentioning, today we have around 30 ‑‑ 300, sorry, users, which may seem small amount of people compared to our 76,000 employees.  But for those that are using it, the impact is significant.  And, you know, the benefits that were discussed earlier are really clear when you have used the platform.  So, we think that the right tools can really effective powers and (?).  So even if the numbers are small, this is really making a tangible differences in the life of individuals and in their workplace success.
And finally, I would say enablement is really important.  As the other companies, as strong push in companies for AI, enabling everyone on AI and AI specifically to our new product suite, Genforce, but also in our internal AI adoption efforts.  So I think it would be very important for all companies to keep employees, to keep employees to invest on, you know, making sure that people have the necessary knowledge and the confidence to use these new tools effectively.
So, my suggestion to people on the call is really don't be afraid to push boundaries and innovate, because I think employees with disabilities need to see companies actively trying new approaches to support that.  And I think it goes in the same direction what, you know, the Qualtrics surveys was, was mentioning.  Maybe, you know, disabled employees are trailblazers in adoptions of AI.  So I think it's something we should work and continue working on.
>> JEFF WISSEL: I love the trailblazer connotation, too, for all the trail blazing opportunities through Salesforce and all the materials that you all provide to all of us in the public.  I love that information.
Darren, how about yourself?  How about one additional lesson learned as Eli Lilly has been deploying AI?
>> DARREN ROWAN: Just one?  I'm going to probably pick my favorite one, which is probably not my favorite one as well.  So, it's around generation ‑‑ sorry ‑‑ gen AI, and it's really around the fact that, and you can go and test this out yourselves, right, with various solutions that are out there today.  But it will have a tendency to create stereotypical images if you want to get it to create things for your PowerPoints slides and you say, give me an image of disability, and nine times out of 10, you will get somebody in a wheelchair in various places, right, and, obviously, we have people in wheelchairs, but that's not the only type of disability.
So, it will very much kind of, you know, take the kind of data or the image that is it's got tagged and will give you those kind of, hey, everybody, therefore, has a disability and therefore they have ‑‑ or they sit in a wheelchair.
And also it uses outdated languages in places.  And I think the lesson learned here is, you know, yes, it will get better over time and we need to be mindful of what the kind of data, marginalized data, if you like, that it's using.  I think that what we do need to remember to do is just to educate everyone around what disability inclusion means, especially in a more progressive workplace, a progressive society.  And therefore, they can check to see when these images come through, because if people don't have that base‑level education in the first place, then they make think that's perfectly fine, that every image is exactly what I described.
So I think we should never forget the need to have human oversight, but also at the same time it's having a good level education around the topic of disability inclusion and accessibility in the first place.
>> JEFF WISSEL: Love it.  Great guidance.
Real quick reminder for the audience, please continue submitting your questions in the Q&A functionality there.
And this next question I'm going to ‑‑ whoever wants to go first, but it's for all three of you and I really want you to put your geekout hats on.  When you think about AI, what just jazzes you?  What knocks your socks off when you think about the potential of AI and folks with disabilities?  Who wants to geek out first?  Matt, I'm going to call on you.  Or Darren, was that you?  Go ahead, Darren.
>> DARREN ROWAN: Yeah, sure.  So I guess, what really excites me about AI is if you think about where we are with it today, this is the worst that it's going to be, right?  And we have got all those issues today, like hallucinations and with we have got biases in the data and we will maybe have some regulations around that.
But for me as we look at it more through an optimistic lens, I think that what AI can do, everything from, you know, early diagnosis of diseases, for example, so it can prevent in some cases things arising into, you know, severe cases or even disabilities regarding that.  But, you know, I think the power of that and we are seeing it already in use in some medical settings and the level of accuracy it's able to achieve is quite outstanding.  So, that will only get better.
But I think, again, going back to how it will make a difference to people with disabilities in the level of independence, if I geek out on it and I think about what the potential is, as I can get into self‑driving car that will take me to a record shop that I can walk in there with my wearable glasses and I can browns through all the albums and pick whatever album I want to go and buy, because I don't have anybody else who I am boring to death in my family to read that to me.  That's just me living my life with those little things that are augmenting my reality, if you like.
And I think that's what really excites me.  I think the power to be able to have it in addition to your life and, sort of, take that and leave it as you please, it's got so much potential still to come.
>> JEFF WISSEL: Fantastic.
Matt, how about you?
>> MATT EVANS: Yeah.  So, this is coming I think a little bit more, perhaps, from a place of personal interest and personal passion.  So, gen AI right now is still a little bit dodgy when it comes to math, but it's getting better.  Agentic AI, which is really the next frontier, I think of what it is that we are looking at is AI with the ability to essentially act independently without regular and constant human interaction.
Something I'm really interested in as an individual is personal finance, and personal finance I think for folks is something for everybody, can be a complete mystery, and I think particularly in many ways for people with disabilities.  Even when that mystery is solved, behavior change around personal finance is really difficult.
So, I'm going to get hyper specific and just say that my dream AI agent is one that has this sort of colloquial narrative input from an individual, their hopes, their dreams, salary, personal lives and not only spits out an exact budget that can be used, which is great, but also puts in place the kinds of nudges and behavior changes that I think oftentimes get in the way of people from meeting their goals, whether it's automated deposits, limits on the types of things that you are spending on.  We live in a country, I think, where 60% of folks don't have $1000 to meet an emergency if it comes across.  This is solvable problem, I think for everyone where the assistance of AI.
>> JEFF WISSEL: I love it.
Federica, your couple of minutes to geek out.  What really gets you excited about AI and the future for folks with disabilities?
>> FEDERICA TERRENZIO: Yeah.  I think all the things that the others, I mean, kind panelists had mentioned.  This AI, we don't know where it will get, right?  But I think from my perspective and the work that I do, I think this gives a lot of hopes in terms of the speed of impact we can have.  And impact for our colleagues with disabilities.  Because I think we have seen, I have seen the last few months a proliferation of AI, assistive technology integrated tools that are really making life of our disability communities much better and easier, and actually the life of everyone, because we are, for example, assessing now a mind mapping tools that, yes, it's useful for neurodivergent colleagues, but actually being empowered by AI can be used by everyone, right, and we make our, sort of, projects and ‑‑ much easier.
So, I think the speed and I feel like is limitless in terms of what we could do in the future with AI and agentic AI.  So I think I feel a lot of optimism around the use of this new technology.  So, that's what excites me in my daily work.
>> JEFF WISSEL: Thank you very much.  We are talking artificial intelligence.  And we just had some amazing human intelligence that was just shared with all of us.
Federica, Matt, Darren, thank you.  Thank you for your leadership, your partnership, your friendship.  Thanks to Salesforce, Eli Lilly, Qualtrics for being just amazing corporate partners.  And thank you to the audience for being part of our panel webinar so far today.
And we are going to turn it over to the Q&A portion of this event.  And I just want to give a shout‑out to the backbone of the Inclusion Works program, our incredible consultants that bring a wealth of knowledge, lived experience, and intelligence to the overall part of Inclusion Works.  And with that, I want to turn it over to the amazing Joan Bohan, who is one of our wonderful consultants, to walk the panelists through our Q&A event.  Joan, over to you.
>> JOAN BOHAN: Thank you, Jeff.  What a lovely introduction.  So, yes, I have a few questions for ‑‑ from the audience.
This came out, Federica, people are very interested about the partner that you use for the chatbot.  So, if you could put the name in the chat here.  A couple of people from the audience would appreciate that.
>> FEDERICA TERRENZIO: Not a problem.
>> JOAN BOHAN: More of a housekeeping question.  But, yeah, it sounds like it's a really cool thing you have there.
Here's our first substantial question there.  So, how are you training your AI?  What datasets are being used to create your applications?  Anybody want to take that one?
>> MATT EVANS: I could talk to that a little bit from Qualtrics' standpoint.  So, from our perspective, we use anonymized and aggregated datasets to train our AI models.  So, the anonymization process ensures that really there is no reference to customer PI; personally identifiable information, or brand personally identifiable information or employee PI:  And then we aggregate the data so it can't be traced back to one specific customer, one specific employee, one specific brand.
We also have a human in the loop to really minimize the risk of that PII.  Slipping through.  One of the things at Qualtrics that we benefit from is being a very large experienced management/survey type of a company is that we have an enormous dataset of billions and billions of data points with people's experiences around customer carriage and products, their employee experience at work, from which to draw from.
That's great.  And we also have a significant number of, on the employee side of things in‑house, industrial and organizational psychologists who are able to help ensure the quality of what models are producing so that it's not just something that's genericized, not something that's coming from off‑the‑shelf LLM but something that's contextualized and has expertise built into it so that when, say, a manager is looking at a set of employee experience data in a dashboard and they ask, what can I do to improve work/life balance for my employees, we have that data to draw on and we have the expertise of people in‑house who have evaluated the efficacy and quality of the model in terms of its output. 
>> JOAN BOHAN: Thank you for such a great response.  Anybody else want to comment before I move to the next question, Federica on Darren.
>> FEDERICA TERRENZIO: I was comment on a tool retained.  Retained artificial intelligence, generative artificial intelligence we use, so they use the Job Accommodation Network dataset that it's the leading source of free confidential guidance on work‑based accommodations.  And then, of course, there are all the informations that we provide as our internal resources.  So, this is the datasets that the, sort of, AI is using to provide recommendations and best practices to our employees, linking this informations into our internal resources.
>> JOAN BOHAN: Thank you, Federica.
Next question, what ethics of artificial intelligence do you add here to?  So, Darren, I think you mentioned something along these lines early on.  Is there something you want to add and expand on this?
>> DARREN ROWAN: This is something that we, I suppose, continue to grow and learn on.  We just, you know, announced a chief AI officer that's come with a great deal of experience in this area.  And, obviously, it's core to what I mentioned earlier.  In terms of putting a governance process around and AI solutions, we encourage across the company, in terms of people coming forward with ideas that they just want to put out there without maybe any technical knowledge of what that might look like or even procuring solutions to bring in, then we have a process that is gone through that checks at various stages in terms of, you know, what kind of data would that be, expected to be relying on, if it's already a bot solution, then where are those kind of large language models that we are going to and what kind of level of policy has been put on those as well.
And then we could run through a process of checking from both a legal and a privates perspective, as well as courses around any sort of potential security risks there.
What we are trying to do as well as part of this process is to encourage more involvement from some of our different employee resource groups in terms of involvement from, obviously, we have a disability ERG ENABLE, but others as well to start to get involved in more of the testing of these solutions to really understand, you know, what does that really look like.  Is it showing any potential bias in that process.
So, you know, at the heart of any of these things, there has to be a great deal of attention spent on, you know, what's the output, what do we expect are some of the output to be, kind of, obviously, knowing what some of the answers to the questions should be, is that accurate enough to what level are we, you know, able to accept some kind of leeway as the models learn as well.
So, it will vary depending on the level of risk that we are also allowing to have on certain different types of solutions and we got multiple of them in the organization for different purposes.
>> JOAN BOHAN: Thank you, Darren.
Matt or Federica, anything to add to that?
>> FEDERICA TERRENZIO: Well, this is not really my specialty.  I would say that trust is one of the core values at Salesforce and, therefore, there is a sort of huge commitment in terms of what is called ethical human use of technology.  We have, you know, a person that is in charge and she has a team and works, you know, when it comes to the ethical and human use of technology within our, you know, product and services.
So, I assume, you know, most of our companies, big corporations have, you know, safeguards around the way we implement and we adopt artificial intelligence within our product.
So, there is the commitment, for sure, in the appointment of the chief on ethical and human technology officer in our company.
>> MATT EVANS: Yeah.  And very similar for us, to what Federica said.  We have a cross‑functional team that's focused on defining standards that allow for responsible and ethical use of AI in terms of our products, I sit on that group.  So, when it comes to the principles that we actually developed, we drew from psychological research principles, ethical software design principles, IO ethics so pulling from the medical community as well to really help shape what our direction was going to be.  And then much like Salesforce and much like Lilly would have as well, we have various processes and controls in place around model risk management, bias reduction and things of that nature.
>> JOAN BOHAN: Thank you.  Thank you all for such great responses around that topic, which certainly really important in this.
I have a question here from a member of the audience, who wonders what the right amount of time one should spend using AI.  They were relatively new professional.  So, just joined versus somebody who might have 20 years or so that might have learned to work differently.  So, today they use, for example, 1 1/2 hours AI per week, professionally.  And a bit more personally.
Do you have any thoughts about what an appropriate amount of time would be at work, for example?
>> MATT EVANS: If you don't mind I have a couple of thoughts on this one.  The way that I think about it is maybe less about the amount of time that I am spending in AI and more, one, what are the principles that are guiding my usage, and then, two, when I think about those principles, what are the tasks or activities that I am undertaking that are most replaceable, augmentable by AI or stay away in terms of AI.
So, you know, for example if I work in, say, a talent acquisition recruiting type of a function, I may be fully happy with completely automating my approach to drafting a job description based on a hiring manager's requirements, at least coming up with the first draft.
I may be able to augment what I'm doing from a screening interview perspective by having AI summarize the results of a screening interview, but I may have a task like writing a job offer or negotiating that I don't want any AI to have anything to do with.
I think once you start to look at the tasks that you are performing on a day to day or a week‑to‑week basis and seeing which of those tasks are most enhanceable by AI, I think that starts to give us direction on how and how much time we should be leveraging artificial intelligence in our work.
>> JOAN BOHAN: Thank you.
Another question.  So, this is for everyone.  What are the best places to go to build confidence using AI if you only put your big toe in with ChatGPT and are intimidated about it, but interested in trying to have more advanced use with apps.  Any thoughts on that?
>> FEDERICA TERRENZIO: I can start saying something because I'm not really not a ‑‑ I'm not such a technical person.  So, somehow even though I work my whole life in technology, right?
I would say that it's a bit of, I think, confusions around the complexity of AI.  Because I think we are already using AI without us even understanding that, right?  Because if we use Google doc we have Gemini that we can use, right?  I think it's a matter of really experimenting and starting using the tools that are fully available.
In terms of, I will spend some word on my companies and, you know, learning systems that is open and free for everyone.  So I think it's important to know that.  And it's called Trailhead.  I can provide, you know, the link to everyone on the call later or after.  But it's free and it's free of resources around artificial intelligence, agentic AI, so I think as Salesforce there are plenty of other companies, I think out there in technology that are offering these resource ‑‑ free resources, and it's really a matter of curiosity and, you know, willingness to upskill themselves.
And I want to refer back to the questions about the time that junior professionals should spend on AI.  If I had a junior in my team, I would say, yes, spend time to learn AI because this is the future world, right?  So, maybe it's worth investing.
>> JOAN BOHAN: Thank you, Federica.  I think it's important to make the comments that you did coming from a nontech person because I think a lot of us are intimidated and we want to be able to access this in a way that feels comfortable.
We are at time.  We have one minute.  So, Jeff, I would love to hand it back to you to round out the session.
>> JEFF WISSEL: Joan, you are wonderful.  Great job.  Thank you very much.
Thank you to the audience.  Thank you for being part of the Disability:IN family and a special thank you to Federica, Darren, and Matt.  Special thanks to Salesforce, Eli Lilly, Qualtrics, and special thank you to our ASL interpreters and our captioner I want to remind everyone, you have about 15 minutes of a break here.  There's going to be one session coming up at 11:45 a.m. Eastern Time on the future of supplier inclusion.  It's a must attend.  It's going to be some great information.
And, again, thank you for learning and sharing together.  And we always say, competitors in business are collaborators in accessibility and to quote Jenny Lay‑Flurrie in Microsoft.  When one of us wins in the space of accessibility we all win.  Thank you for sharing your practices and helping us all to be better and to advance through AI and to learn to embrace it while being intentional.  Looking forward to seeing everyone at 11:45 eastern for the future of supplier inclusion.  And thank you all for joining us for this session.  Have a great rest of your morning.
>> MATT EVANS: Thank you.
(Session was concluded at 11:30 a.m. EST) 

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