Pivoting to WEB3

Ai Readiness: Empowering The Frontline (Special Edition)

• Donna P. Mitchell

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Are frontline workers getting left behind in the AI revolution?

Welcome to a special edition of Pivoting to Web3 with co-host Jose Garcia, founder of Talk Coded — today’s timely conversation: AI Readiness Empowering The Frontline. Let’s Get Busy!

In this special edition of the Pivoting to Web3 Podcast, we bring together a powerhouse panel—Jason Padgett, Dr. Amani Alabed, G. Kofi Annan, Lekha Mishra, and Brian Green—to tackle a pressing question: How can we empower the people closest to our customers as AI and automation take center stage?

From real-world community meetups and cutting-edge education strategies to hands-on advice for integrating AI in sales, support, health, and beyond, this conversation is packed with practical insights for leaders, entrepreneurs, and anyone navigating the new AI-powered workplace. We dig into the real concerns: Will AI replace jobs or make work more meaningful? How do you overcome fear, bridge the gap from strategy to frontline adoption, and build the skills for the future—without leaving anyone behind?

Visit [mitchelluniversalnetwork.com](https://mitchelluniversalnetwork.com) for more updates. 

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Connect with Donna Mitchell:

Podcast - https://www.PivotingToWeb3Podcast.com
Book an Event - https://www.DonnaPMitchell.com
Company - https://www.MitchellUniversalNetwork.com
LinkedIn: https://www.linkedin.com/in/donna-mitchell-a1700619
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Twitter/ X: https://www.twitter.com/dpmitch11
YouTube Channel - http://Web3GamePlan.com

What to learn more: Pivoting To Web3 | Top 100 Jargon Terms

Connect with Donna Mitchell:

Podcast - https://www.PivotingToWeb3Podcast.com
Book an Event - https://www.DonnaPMitchell.com
Company - https://www.MitchellUniversalNetwork.com
LinkedIn: https://www.linkedin.com/in/donna-mitchell-a1700619
Instagram Professional: https://www.instagram.com/dpmitch11
Twitter/ X: https://www.twitter.com/dpmitch11
YouTube Channel - http://Web3GamePlan.com

What to learn more: Pivoting To Web3 | Top 100 Jargon Terms

Jose Garcia [00:00:01]:
Here we go. Hello, Donna.

Donna Mitchell [00:00:04]:
Hi there, Jose. How are you doing today? I'm so excited to be here with you.

Jose Garcia [00:00:09]:
Yeah, really good. Really good. Because. And, you know, this is kind of like. Feels like we're kind of starting something. We had, like, this is the second event we've done now on AI readiness. And I have a lot of people kind of contacting me and talking to me about it and. And also people in my own personal life, they're like, oh, Jose, can you teach me?

Donna Mitchell [00:00:36]:
Well, it's been very exciting, you know, with everyone coming into AI readiness for the whole organization. It was quite successful. It generated a lot of interest, motivation, and people want to know and paying attention a little bit more than they were before, because it's happening just about everywhere. Everywhere.

Jose Garcia [00:00:54]:
And I think one of the part of this motivation was there was some comments in the after party of the first event. I hope you remember, Donna, someone was saying, what about the little people? Are they being left behind? You're talking, you know, you. We're talking about companies. What about the staff? And I think that was kind of like the motivating force behind the subject of this event, which is AI readiness. Empowering the front line.

Donna Mitchell [00:01:27]:
Well, the front line's important. I'm sorry, I didn't mean to cut you off. Go ahead, Jose. You know, I'm going to jump in.

Jose Garcia [00:01:32]:
Jump in, please.

Donna Mitchell [00:01:33]:
Well, I'm going to jump in because the front line today is more than just important. There has to be a balance, and it's really great that we're bringing that next in the series. I think there's a lot of great insight from our speakers. The audience was right on track, and. And you being the host with Talk Coded, I mean, you don't miss a beat. So here we are.

Jose Garcia [00:01:55]:
Thank you. Well, I think we're going to have the way the event's going to work. We're bringing on the speakers one at a time, and then we're going to have a group hug where they're all on the screen. And this is the tricky bit. We're going to have, like a final word. We're going to say goodbye. But we're not actually ending the event. We're just cutting the event there for the YouTube replay.

Jose Garcia [00:02:19]:
Let me go to the after party. The after party doesn't go on YouTube, so. But we're gonna say cut. Goodbye, everybody. But we're gonna stay. And during the after party, we'll be inviting you to come forward. We're gonna be putting some of you on mic. You can put Questions in the chat.

Jose Garcia [00:02:38]:
You can ask speakers about how for advice or I'm doing this or things like that. We're going to go into the. And I don't know how. What's going to happen. Every after party is a bit of a surprise.

Donna Mitchell [00:02:51]:
It was a nice after party. I had a good time. It kind of felt like an after party had a good vibe. Lots of questions and some personal revelations and reflection took place with some of the attendees. So I think it was a good time. I was very happy that I was there. It was a good vibe.

Jose Garcia [00:03:09]:
I might crack open a beer, actually.

Donna Mitchell [00:03:14]:
Well, we better get started. I think it's. It's about that time for us to move forward. And are you ready to get started?

Jose Garcia [00:03:21]:
Absolutely. Here he comes, Jason, ready or not. Boom. Pole position.

Jason Padgett [00:03:29]:
Pole position. Now that's appropriate, since I'm in Indianapolis and we just had the 500 and had a Spaniard win it. Right. For the first time. Jose. So that was exciting. Yes. Yeah.

Donna Mitchell [00:03:43]:
So, Jose, does everybody know you, Jose? Who are you? I know who you are. Did you introduce yourself?

Jose Garcia [00:03:48]:
I'm Jose Garcia, and I'm content lead at Top Coded. I don't really introduce myself, but thank you, Donna.

Donna Mitchell [00:03:59]:
I want us to jump to this.

Jose Garcia [00:04:02]:
Time and I didn't, did I.

Jason Padgett [00:04:06]:
Did you fully introduce yourself, Donna?

Donna Mitchell [00:04:08]:
No, not yet. I wanted to do. I wanted to do Jose first, but I think everybody kind of knows me, and if they don't, I'm the host of pivoting, the Web3 podcast, and the founder and CEO of Mitchell Universal Network. I'm in the Web3 space, AI and emerging trends with Blockchain, and we joined.

Jose Garcia [00:04:26]:
Forces to produce this series.

Jason Padgett [00:04:30]:
And warp speed, it looks like Jose.

Donna Mitchell [00:04:34]:
So, Jason, you ready to get going? I think Jose's gonna start.

Jose Garcia [00:04:39]:
Oh, I wouldn't. And the reason why we put Jason on first is because he's frontline. He's going into his local community. He's having meetups. I'm kind of envious. I want to do meetups in the real world. I've not done it. And.

Jose Garcia [00:04:58]:
And you're getting into the room with people, and people from all corners of life are coming forward and they're bringing forward their use cases, and you're educating them and you're. And so you're actually seeing this from a completely different angle than I do, Jason. That's why I wanted to start with you, by the way. Have I. Have I. Have I introduced you properly?

Jason Padgett [00:05:21]:
I think I can take it from there. Thank you. That's very. And. And that Passion that I have is as big as my frustration as it is passion, or at least it has been because it seems like AI integration in the United States has been pretty much reserved for the enterprise level. And we know that it's going to affect everybody. So I love this topic of reaching out to the frontline workers. I am a human AI collaboration coach.

Jason Padgett [00:05:44]:
I have the good fortune of also having a day job where I work for a community paramedicine company that does a lot of work in behavioral health. So I get to explore AI there. But on the sidelines I'm trying to figure out how nonprofits and small to medium sized businesses are going to start to navigate AI as it begins to affect things. And before we turn the camera on, Jose, you were mentioning hoping to garner larger and larger crowds here. I find that when mainstream media starts reporting on this stuff, that's when people really start to pay attention to it. So I was just looking into the last 72 hours, you know, Signal Fire, their state of talent report, which is mainly tech industry related, said that new hires in technology are down 50% since pre pandemic times. And now that that may not mean a lot if you're outside the tech industry. But Dario Amadei, the CEO of Anthropic, just said that he foresees within the next five years 50% of white collar office job new hires will be eliminated.

Jason Padgett [00:06:43]:
That, that is fundamentally huge number even if he's exaggerating a little bit because they have a model. One other that I noticed was Axio CEO Jim Bandehy was on the Morning Joe show and he just came quite out and said you're committing career suicide if you're not aggressively experimenting with AI right now. And I think that to me, I don't disagree, but I, I think a lot of people haven't really realized that yet and they may be a little bit intimidated by it. So education is going to be a huge part of how we move forward. Whether that's education in the workforce to help reskill people, or education in community colleges and in universities and in K through 12. So I've been taking a really hard look at like what are we doing in the United States around education and AI. The Khan Academy has a Khanmigo chatbot, which is kind of a new age meet kids where they are personal tutor, custom GPT, which is really cool. But beyond that, I think probably the most progressive thing I've seen.

Jason Padgett [00:07:47]:
Bowling Green State University is going to start offering in the fall an AI plus degree so you can get A bachelor's degree in AI plus computer science, math, physics, history, journalism or public relations. That's the kind of integration into the education system that I feel like we need to be looking at here in the state of Indiana. Our community college, Ivy Tech, has put together and assembled a panel of about 50 industry professionals to discuss what their curriculum should look like. We have another startup ed company that's trying to pilot some of this in high schools. But again, what I really want to push people to think about is are we approaching education and AI the right way? We're currently pushing like tool literacy, and yet those tools change every three months, if not every six months at the very most. Right. We're worried about, we're not teaching discernment, we're talking about deep fakes and problems with hallucinations. But are we teaching people how to have a discerning approach to these models so that they can actually figure out whether or not something that was generated is appropriate to use or is properly sourced? Teams.

Jason Padgett [00:09:06]:
You know, this is going to be a much more of a team type environment. And our education system currently is. One person takes a test and they get graded on it. Well, that's not how the workforce works at all. You're going to be working in teams to solve problems. And so let's shift education toward that. I think we need to start looking at things like design thinking, AI, project management. I just heard a gentleman on a podcast say the other day, an artist say, if you still write prompts, then you're like a dinosaur because AI can run it way better.

Jason Padgett [00:09:35]:
And yet our community colleges are looking at classes on prompt engineering. How about prompt engineering and as a cross functional team collaboration effort. Now that I could see, right, if sales is sharing their prompts with marketing, now you're starting to see how can we get this tool used across the company and people talking about how to use it. We're going to have to look at risk management, change management, data analytics, process flows. Like, I think we need to really start to define what are the skills of the future. And they start with agency discernment and process fluency. And so I think that probably all of our speakers today are going to hit on some of those topics. I would urge you, if you don't already have some type of a change management and AI literacy program going in your company, reach out to anybody in this panel.

Jason Padgett [00:10:23]:
Reach out to somebody. Just start, just start hiring in or paying for Coursera courses to begin to let your employees safely, ethically and productively leverage these tools. Because five Years from now, if you haven't done that, good luck.

Jose Garcia [00:10:38]:
That's very timely. I've got. I've got three use cases myself. You know what? I did it the hard way, Jason. I spent six months nailing jello to a wall, and I just stuck with it. I got my three use case. Now I'm bringing another person on, and now we're doing those three use cases together. And then on the fourth use case, we're going to be doing that.

Jose Garcia [00:11:03]:
That's something we're creating together and doing together. And. But. And I think this is really important because a lot of people, they're really busy and that nailing jello to the wall phase is really intimidating. They give up or they just. I'm just going to use Gemini, like search engine, and they don't. They don't move beyond that.

Jason Padgett [00:11:28]:
Yeah. And that's really where it becomes kind of leadership's. Leadership's responsibility to help everyone in the company kind of find their, what I call Chad GPT moment. That moment when you wake up and realize, wow, this is productive and really helps me. And that's going to be different for different divisions, different employees. But once you can show them that how much this can open up their time as well as help them with brainstorming. I mean, I was just talking to somebody the other day. I'm like, hey, just ask Chat GPT what it would do in this, in this case and the ideas that it gives you, even if you don't go with any of them, it will really open your mind up to some ideas that you would never have thought about.

Jason Padgett [00:12:03]:
Right. So that, that, that brainstorming function is amazing.

Jose Garcia [00:12:10]:
Thank you, Jason.

Jason Padgett [00:12:12]:
Thank you, Jose.

Donna Mitchell [00:12:13]:
And thank you, Jason. Well, we're honored to have G Coffee Anon and G Coffee Anon.

Brian Green [00:12:21]:
He.

Donna Mitchell [00:12:21]:
He's a brand strategist, culture futurist, and founder of Brand Sensei. He's worked for some major companies, enterprises, Mercedes Benz, Puma. I mean, he is definitely the specialist and an expert in this area. And we'd like to share some information with you. All from Coffee. So coffee, take it away, because this is not south by Southwest. You've been there too, and a few great places that you shared. So everybody better listen up.

Donna Mitchell [00:12:49]:
This guy knows what he's doing. Coffee?

G. Kofi Annan [00:12:52]:
Yeah. Thank you. Thank you, Donna. Thank you, Jose. Glad to join the team again and kind of contribute to the conversation and help brands move forward. As we're talking about AI readiness, the area that I usually play when I work with different brands and different companies is more in the marketing, sales, customer service, customer experience context. So this particular focus on frontline employees is really key because at the end of the day, the, the people on the front line of a business, whether they be call center people or, you know, people who work in the, the retail stores, they are the, the. They exhibit what that brand is and what that product is.

G. Kofi Annan [00:13:45]:
So neglecting them and not pulling them into the conversation, not putting it into the fold, is definitely a big, big misstep for a lot of organizations. Unfortunately, I do hear a lot, I mean, we all hear that a lot, right? Where a lot of the conversation around AI adoption in organizations is really more on the executive level. Automation, efficiencies, those kinds of things. And as usual, as regular people, we know that that scares us. There was a stat that came up recently that I read where it says 45% of employees don't think their companies have rolled out AI properly contrast that to 75% of C suites who think that they have. Right. So if you look at kind of that dynamic, you can see that's a huge disconnect between what the C suite wants to do with the organization as far as making it efficient and accessible and all those kinds of things, and what the role that the employees and the frontline people are playing in that. And as much as directives can come from the C suite, a lot of that starts coming through when you're talking about something like a call center employee.

G. Kofi Annan [00:14:54]:
Right. You know, how their comfort with the material, understanding the brand, understanding the company, understanding the nuances, especially if it's a technology, understanding what the technology does and doesn't, their comfort with the product and their comfort with delivering that on behalf of the company. So their affinity to that company really is of utmost importance. And I think that there's a lot of work that still needs to be done to bring those folks along and let them even know exactly what the whole AI adoption focus is for. Like, what is their incentive? Like what is what's in it for them? How does that actually make their job and their lives better?

Donna Mitchell [00:15:36]:
Well, I agree with you on that. In regards to the front line, I think one thing I'd like to just enhance in what you had mentioned is the fact that the front line is important. They have to have the mindset, the buy in the AI design before you really just drop it down from your executive leadership. Jose, you were getting ready to add something, I think.

Jose Garcia [00:15:55]:
That question of incentives, does that come up in the afternoon party last effect? It did, didn't it?

G. Kofi Annan [00:16:01]:
Yeah, it did.

Jose Garcia [00:16:02]:
It did the people want to know what's in it for them? And I, I, I used to work in customer service back in the day and I know how that rep feels about their job and their tools. The customers know, you know, the customers know, even the management does it. Now can we go to the, and this is coming, this is almost like take me back to my composure. Service days, customer feedback. What, what kind of role is there for customer feedback in shaping a company's adoption strategy? And this is kind of like there can be that disconnect between the guys on the 30, sorry, the people on the 30th floor and the people on the ground who are actually implementing those policies.

G. Kofi Annan [00:16:57]:
Yeah, I mean, there's definitely, and again, this, this is a part that a lot of executive miss because, you know, let's, let's be real. You know, a lot of executives don't spend too many, too much time on the front lines. Right. They're busy doing again, important work. But at the same time there's, there's still a little bit more disconnected from what's happening day to day.

Brian Green [00:17:20]:
So.

G. Kofi Annan [00:17:22]:
It'S as we're trying to roll out things like AI and automation especially, it's even more important for the C suite executives both to get feedback from the, and take a pulse of the employees. But at the end of the day, the customers are really those, the people who really keep the company going. So as you're building out your AI adoption, hopefully it's a program and not a directive. So as you're building out your AI adoption program, there's a huge need to have a context around the employees, how you're enabling them, how you're powering them, but then also from the customers themselves. Right. So how are you over time keeping a pulse on the feedback from the customers? So is a customer calling into, again, I'll just use the example of a call center because it's, you know, it's the most, most clear example. But our customers, when customers come off of the line with your call center employee, that's helping them troubleshoot a problem when they go to that one question. Can you, can you wait around for a one question survey? What are the customers saying in that survey after they've interacted with your employee? Right now, the customer is not explicitly going to say that, oh, this was AI or something like that, but there are some, some keywords and some sentiment that you could pull from those surveys that helps you understand whether, you know, maybe the, the employee, the, the customer service person was flustered in finding information.

G. Kofi Annan [00:18:56]:
And that might be a result of the. They couldn't even understand how the AI was working with them. Or even, you know, if you've, if you've gone so far as to automate the whole customer dialogue, you know, looking at that customer feedback and reading meticulously, going through that and processing that can give you a sense of how well it's reflecting on your customers and whether they'd want to call back into the. And get in contact with the organization. Well, so customer feedback is the paramount metric as far as I'm concerned. And then everything else works back from there. And um, and that's why I think rolling out AI adoption programs should be systematic and not a blanket let's do AI and get all the get and automate everything. So yeah.

Jose Garcia [00:19:49]:
Don, you've got more big corporate experience than I do.

G. Kofi Annan [00:19:54]:
And this. And the same thing goes for sales too, because a lot of times I remember years ago when, when dating myself, but when iPads and tablets first came in, first became a thing. Hilsey, you might even remember this if you said you were, you were in the sales days. You know, traditional salespeople would, you know, would kind of go from, you know, from client to clients with a briefcase full of brochures and papers. And they got used to that, right? Like this is when you. I asked this question, I pull out this thing, you know, so that's that kind of cadence and that kind of. For a salesperson that kind of comforts in knowing what to what. How to guide the conversation.

G. Kofi Annan [00:20:32]:
I remember years ago when tablets first came out and iPads specifically, and they were a mandate because they did all the things that the, the. On the corporate side they wanted to do. There's transparency, there was efficiency. You know, you didn't have to print as much paper. You could read the data and see the salesperson was actually, you know, having. Making the connection with the customer. So all these things. So it all made sense on paper.

G. Kofi Annan [00:20:57]:
But for a very long time, the usage, the usability of when given those iPads, it was less than 15% of salespeople were even using that you would give them. They would agree, they would not like. This is great. And if you did a ride along with the salespeople, you'll see that they still went in their briefcase or that what you call and pulled out the paper. So I think where we are now is a clear example of the similar thing that's happening where you have to understand the context to which your frontline salespeople are having the conversation. And the interactions and then incorporate them in the decision making about how to roll that out. And I know when we did it, in some instances we went from, I know for one project we went from about 10% utilization for the iPads, for instance, to about 35% in less than a quarter. Right.

G. Kofi Annan [00:21:53]:
And again, that was just based on them feeling that they had a role in the rollout. But then also they actually understood how to use it in, in and customize it for their use at the front lines. So I think it's a, it's another example of how you could make these things work really easily by bringing the front lines in earlier.

Donna Mitchell [00:22:13]:
Can I add to that, since I had spent so much time in the reservation centers way back in the day, all those centers and all that frontline, trust me, they're your customers. It's not just your external customers, they're your internal customers. They need to feel the experience, have a good experience and the support and a pathway to go forward. That would minimize some of the fear, it'll minimize the feeling of being displaced and it would give them a feeling that they're included and, and there's a way to go forward and enhance their skills. I think it's really important that we don't forget about the training aspects with your chat bots. Utilize your AIs and the new services that you have today and the technology that you have today to provide support and show the care in that change. And if you want the transformation, they have to feel part of the change, the mindset and the transformation and the consistency of external and, and internal customers.

Jose Garcia [00:23:16]:
Well, we're going to our next speaker. We're going to bring on somebody who implements and builds out some of this technology. So we're going to have a different point of view. Welcome Leica.

Lekha Mishra [00:23:37]:
Hello. Hello everyone. So let me introduce myself first. So I am Leka Mishra, founder of IPS Technologies and also founder of Mindstein LLC that is a AI power solution. And at IPS Technologies we are basically specializing to develop the custom software solutions powered by AI, deep linking and machine learning as well. And my background is to, to leading end to end operation, whatever is going for the digital transformation, crafting the mobile strategies and how the AI and ML design analysis are going on. So I am having more than 15 years of experience in this industry and recently working on the solutions which is powered by AI as of now. So really thank you to provide me the opportunity to speak here and I am really excited to share the thoughts on this like how the practical strategies can be implemented to make the AI more powerful, you know, instead of just being accessible.

Lekha Mishra [00:24:44]:
It could be adopted by the frontline team members as well. So I am looking forward to your questions. Like if you do have any then I will answer those.

Jose Garcia [00:24:56]:
Oh, I've just opened the chat apparently, apparently I had it set wrong so the, the audience can chat with each other as well and I wanted to kind of. I thought this would be a good time to ask you your experience and about problems people have been having to. Let's see, send chat to the.

Jason Padgett [00:25:27]:
People.

Jose Garcia [00:25:27]:
Have been having when they're implementing AI. Sorry, I'm going to sort out the chat in a moment. Sorry. I know there's a problem. Common challenges and hesitation you'd see from businesses when they're thinking about implementing AI for their frontline teams. Are there certain problems, pain points more than others?

Lekha Mishra [00:25:50]:
Yeah. As Coffee and Donna has also covered one of the two things like for the frontline team members like their main concern is a fear of replacement, you know so they are thinking like if they the system is adopting the AI then they can be replaced instead of like the AI can assist them. Same for the frontline teams like there is always a training gap there. They don't really understand how the system should work and there is always a less of training and sometimes the system is built, you know, not for. Not for the user friendly thing. This is more technical things so people don't understand how to use it. So they are having a hesitation to use those things. So these are the concern based on the frontline team members point of view.

Lekha Mishra [00:26:38]:
But if as per your question Jose, if we are talking about business owners point of view and businesses point of view then there is like I have been working closely with some of the business owners in healthcare industry and they are specifically having a fear of trust. You know like the healthcare industry is something which actually needs a good results cause it is related to the patient care or something and they always have a concern might be the solution would not provide the correct results what they are looking for same for the accuracy of the system. Also one more concern is as a business point of view if you are working on any of the fintech sector or anything else then they like if something goes wrong then what the risk is involved in the financial thing, you know. So this is a big challenge for them. Apart from this there is could be the compliances like the system that we are building is it fully compliant like hipaa, gdpr? It is like the system should be like this is major important point as a Business owner point of view, the system is covering all those aspect or not the business owner is safe while, while using this tool. So this is very important thing and some common concern is the data security and like how the system is using their data, their customer information and their patient information. How the system is using this, is it secure or not? So these are the major concern as a business point of view, as a frontline point of, frontline team point of view, like they feel like get replaced or they have a lack of training. So these are the major things and challenges I have faced seen during I had a like workshop with the people and also I have contacted with the business owners.

Jose Garcia [00:28:30]:
Yeah, I think actually we had a webinar yesterday and behind some of those concerns Amy Zoloto said is the individuals and they might be in the front line, they might be in administration. They're worried about their own legal liability. So they may have been told, okay, you can use this tool, it's been approved. But if something goes wrong and there's legal consequences. Yeah, is my reputation going to be destroyed? Am I open the liability is how is that going to affect me? Even if it's been and whether that's. And I, I, that's not actually an irrational fear as far as I know. Because these people, these people are professionals. They've had decades of experience sometimes and so I think that might be.

Jose Garcia [00:29:28]:
How could an organization and I might be going off piste here reassure the frontline staff that they're okay from a legal liability to perspective if they're using these tools, does that make sense?

Lekha Mishra [00:29:52]:
Yeah.

Jose Garcia [00:29:56]:
How should the, or how can the organization does something? The organization, that's the organization needs to make that clear or give them that kind of confidence. I don't know Donnie, you got more corporate than I do.

Lekha Mishra [00:30:12]:
Yeah. So yeah, yeah. So as a organization point of view, like we have to make sure all the legal points and everything should be covered whenever designing the system and software. So all the data protection laws and everything, whatever is mentioned in their compliances. The system that we are going to build, if it is for healthcare, then HIPAA and GDPR and everything and if it is even for education, even for FinTech, there is some different guidelines and regulations are there. So as a organization point of view, whenever we are talking to the business owners we have to tell them, okay, this is the system that we are building behind the scene and it is also keeping all the legality and everything. So this is the most important aspect that we have to take care of it and we are dealing with transparency with them so they are aware of whatever we are doing and how we are handling it.

Jose Garcia [00:31:04]:
Okay. Like, I'm going to bring on the next speaker, but stay here then bring me back in about 20 minutes. The group hug.

Lekha Mishra [00:31:17]:
Okay? Yep.

Donna Mitchell [00:31:23]:
And now Dr. Amani, we Dr. Amani Alet. I think she's up next. And she's a scholar, a thought leader at the intersection of ethics, health and artificial intelligence. She's got a lot of bridges in academia and startup and innovation. And I'm going to let her introduce the rest of her background because she is one of the key thought leaders on the panel. Dr.

Donna Mitchell [00:31:48]:
Amani, hello.

Dr. Amani Alabed [00:31:51]:
Hello, everyone. Thank you for having me tonight, wherever you are. So My name is Dr. Amani Alabad. I am an assistant professor at the University of Doha for Science and Technology. I studied AI and practiced AI for the past five years. So my background is a bit diversified. So I did work in digital marketing.

Dr. Amani Alabed [00:32:14]:
So I carry this lens of really consumer first, user first. We need to be very mindful of how we build these systems to match the needs of the users. So I'm happy today to share with you my thoughts on, on this topic because I do believe that it's very timely and we need to be raising awareness on why it is important for us to be AI ready in organizations.

Jose Garcia [00:32:45]:
I've got some questions for you. And training and upskilling. I know you're very empirical, Amani. And what kinds of training and upskilling programs have been most effective? Because right now people, a lot of people are just saying, oh, there's a course, get one, take a course, take a course. What kinds of training and upskilling programs are most effective? Building AI literacy and confidence in the frontline employees.

Dr. Amani Alabed [00:33:26]:
Yeah, so when you talk about AI literacy, I think this is a concept that needs to be explained, I think, to an extent where it's not scary to people. When we're talking about AI literacy workshops, we're not talking about making every worker a data scientist or a machine learning engineer. Instead, we're trying to basically try to equip them with a practical understanding of what are the capabilities of AI. And some of the workshops I delivered, that was a key aspect of every single workshop that has to do with AI literacy. So just trying to get people to know, this is what I can do, this is what AI cannot do. And this is very important because once we see an AI tool that is very trendy, sometimes if we're not scared of being replaced, we would just go and test it as it is and Just try to use it for any kind of purpose without knowing the limitations of that tool. So, for example, in the context of research, one of the things I highlighted in the last workshop I gave in academia was basically, if we were to use AI to do our own research, we have to understand what is the model that we are using. And that comes again, not knowing how the algorithm or the recommendation algorithm is actually coded, but trying to understand that this data or this model is trained on data that has a cutoff date of iron or 2023 or 2024 and so on.

Dr. Amani Alabed [00:34:56]:
So anything that it would produce would not go beyond that date. And if you were to do up to date research, this tool is not good for you. So we don't want to blindly trust the AI. And this is a key, a key thing of AI literacy. So we need to know basically what are the capabilities, limitations and how we operate in a daily context. So that's one. The second thing you would want to train employees on, what are the use cases of AI in the role? So you don't want to know, for example, again how a recommendation algorithm is coded, but they would need to understand that if you were, for example, in a customer service department or whatever it is, that if a customer, for example, browses for a specific online items, then the AI might suggest relevant products in store, making the sales experience or the sales pitches much more effective. Just for you to understand this.

Dr. Amani Alabed [00:35:54]:
And also try to understand that if we were to use AI, it doesn't come without limitations. So just trying to see that if we were to deploy AI, maybe in AI, chatbots or agents, whatever it is, there are still, still this human element that it cannot replace. So we cannot just 100% say this is the tool for us. Some of the skills we focus on a lot is just really getting people to know how to prompt the AI. And I do know Jason highlighted that earlier in the webinar. Knowing, getting people to know really what is a prompt. How is it that you can get the best out of the AI tool that you're using? Say for example, you are a customer service representative, you want to draft an email. So what are the things that you would need to feed the AI to get the best output from it? Another thing is just knowing when is it that we can use AI.

Dr. Amani Alabed [00:36:49]:
So AI is not there for everything you need to know, specifically when is the right time to use it. So we saw a lot of bad use cases of AI where it was used, for example, for trials or court cases where it fabricated evidence. And I was just reading one yesterday in California where I think the lawyer was, or the law firm was having a $31,000 fine and sanctions against these law firms involved because they didn't have any grounds for the research that they have presented to the court. So a lot of things, and I think for me, the most important one is to really critically evaluate the output that we have, which relates to my previous point. So is it really what we want? Is it something that is going to make us better at what we do? So these programs usually would again, be programs in the format of personalized learning, I would say. So you don't want to have an AI course for everyone, a general AI course. You might want to start off with that and then go to specific use cases, things that would fit in every single role there. So you see a lot of institutions, for example, implementing the micro learning modules where it is something that is easy to digest, knowing that if you are a frontline worker, your schedule might be very busy, so you might need to adjust, again, how your employees would be able to access this content.

Dr. Amani Alabed [00:38:29]:
So, again, that is one of the things some of the programs. And as you mentioned, I think Lika was mentioning that, and you, Jose, was mentioning that. How can we make sure that there is an environment where people are able to experiment without having these consequences? So maybe establishing a sandbox environment where we're able to allow employees to play around with the AI outputs and just really try to see or not have the pressure of using AI and just joining it. So these are some of the strategies I saw really effective when I was doing these AI workshops.

Jose Garcia [00:39:12]:
We're actually on time.

Donna Mitchell [00:39:14]:
Yeah, we are, but of course I want to. Of course I want to add something from back in the day when you start changing everything. I think Dr. Amani's right on point because you really need to bring them in and let them play around. But the executive leadership, I think they really need to be focused on what they're trying to do. Are you trying to change the culture? Your transformation is going to be efficiency, people, processes. Is it a combination of both? What departments, what type of AI? There needs to be a true mindset, a true discussion, and a strategy that threads through the silos and your departments down to your front line. This is not going to be the time where there's no communication.

Jose Garcia [00:39:59]:
I'm so pleased we're on time. That almost never happens.

Donna Mitchell [00:40:07]:
So here's Brian.

Brian Green [00:40:11]:
Wow, we're on time, right? We're on time.

Donna Mitchell [00:40:16]:
We're in time. So Brian could take it away because Brian is the AI ethicist. He's the director technology. And, and Brian just brings so much to the table. I'm gonna let, I'm gonna not let. Jose, you do the official introduction of Brian Greene and met Brian, he's been.

Jose Garcia [00:40:37]:
In a lot of my webinars. I met Brian, I saw actually a post you put on. I started following you on LinkedIn and I thought, and I need to know more about this. You actually, you actually. And I've, I featured you in some posts recently, some clip posts. I'm not going to go into them because it's not the subject matter today.

Donna Mitchell [00:41:04]:
And we're gonna stay on time.

Jose Garcia [00:41:08]:
Brian, do you want to introduce yourself? I'm doing a terrible job.

Donna Mitchell [00:41:13]:
I'm gonna be the bad cop.

Brian Green [00:41:15]:
Let me just do a very short intro. Hi, I'm Brian Greene. I've worked in healthcare and on the patient, the HCP side and the pharma side for about 30 years, both in the non profit sector and the for profit sector. About a year and a half ago I started my own consulting company called Health Vision AI where I work with clients that are looking for AI solutions in healthcare and life sciences. And then this year I started another company, call me Crazy, where we're actually developing an AI solution for patients with rare diseases. That's early days. I have two co founders for that and won't talk about that right now. For our topic today, AI readiness.

Brian Green [00:42:09]:
Wow. We heard a lot already from all of our speakers today and I think there's some real key takeaways here. Jason talked a lot about the real need for education, both the need for AI literacy and educating people and the practicalities of how to use AI in the workplace today. That is an absolutely essential and critical topic I think, you know, we see right now, according to, I believe it's Gartner, but It could be McKinsey really the same, frankly, that 70% of AI pilot projects in Fortune 500 companies failed and did not get beyond the pilot. And the number one reason, well, actually multiple reasons, but one of the big reasons is the lack of AI literacy throughout the organization and the inability to take those pilot findings and either understand the ROI from it or more importantly, to scale up and do what they learned from the pilot at the enterprise level. Now, one of the reasons why they weren't able to do that is they really weren't ready. They didn't do the readiness assessment, they didn't do the preparedness stuff that all of our speakers have talked about today that you really need to do up front. So one thing I'll also pull out from what Kofi said, which I think is you know, really, you know, important for what I just said was around the alignment of around incentives.

Brian Green [00:43:45]:
So if a company is struggling with not being able to either move forward from pilot to larger scale AI integration or adoption and or the employees themselves disagree with what the C suite is saying about the preparedness and readiness and have they done what's needed to make AI successful which Kofi highlighted that data point. It really is around misaligned incentives. That misalignment actually takes a number of forms. One of those is what is the risk appetite for AI. Right. And that's a big challenge because what we don't talk about and what you know, you don't hear a lot of conversation about out in the world around AI you hear a lot of hype. You hear about how AI can be transformative and the negative things are things like bias, hallucinations or errors from the model or people fearing losing their jobs. Right.

Brian Green [00:44:46]:
Those are all challenges. However, they have nothing to do with the real problems or challenges with AI that are unique to AI which is around the risk exposure that comes with it, which is broad based and we, you know, I could talk for hours, I won't around what those risks look like, how we can categorize them, how we group them and how we actually need to understand them. There are two solutions. One is ensuring that you discuss those and align on those up front before you move to thinking about the benefits for your organization. That's part of the awareness and co creation structure which I think Laka and Dr. Amani both spoke about. Not directly using those words but in terms of thinking about the need for co creation, okay. Both of them spoke about the need for coming in, understanding the needs of a client, understanding the needs of an organization or individuals, entrepreneurs that are trying to utilize AI within their workflows, within their workplaces.

Brian Green [00:45:54]:
And the best approach to do that, that really aligns with being ready for AI is around helping them. See, I'm not jumping in, I'm not parachuting in as an expert and fixing your problem for you. I'm not adding AI and stirring. Right. I think that's the phrase I've used for forever about like people that think there's magic bullets for everything. You don't add whatever and stir and come up with a magic solution. It's about co creation, it's about co development, it's about co strategizing. Right.

Brian Green [00:46:28]:
So you experts that come in, whether they're developers, whether they're ethicists, whether social technical people, where they're practical, operational focus people. You need to co create and understand how AI will help solve clear business problems and then even map that out and outline it and architect it with input from the front line. So I think one more important topic that Dr. Armani also raised, which kind of overlaps a lot with what Jason was saying, is around this kind of workshop approach and co creation approach to understanding these needs and how to best implement within any organization. And that is that it needs to be learning focused first, AI literacy and other learning that's needed within an organization. And Donna herself, you know, jumped in and said, you know, it's really about organizational transformation and change management and how you communicate this within an organization. Right. So this is the larger framework and structure about what AI readiness really means, you know, and you know, it's easier in some ways to articulate all of those pieces that you need to be ready and then integrate and then be successful and then measure with KPIs.

Brian Green [00:48:00]:
When we're talking about medium size or larger businesses in a way, when we're talking about solopreneurs and individuals using it on their own, it seems like AI is not very risky, right? I can ask ChatGPT lots of stuff. It's not. And as long as I don't put in personal data, I'm not exposing myself to risk. Well, guess what, you can still do that. I think one of the things that Jason said earlier that you know, he was just quoting someone else, but I disagree with the statement of whoever he quoted is like, you know, essentially that prompt engineering is dead. Not those words exactly, but I kind of disagree there. Some of what people have been hyping around prompt engineering is not needed. However, there's a lot around structured prompt and what you need to do in terms of ML operations around prompts that is very different than what we call freeform prompts.

Brian Green [00:48:59]:
Freeform prompts are not a good idea. They do bring out way more risk and challenges and problems. All the hallucinations and things that people cite around this are because people are, you know, winging it and free forming a prompt instead of using structure, instead of using some of the fundamental tools that are taught when you're talking about prompt and engineering. Now the reason that people are saying experts are saying prompt engineering is dead is because 2025 is the year of what agents agentic AI. Right? That's the new hype and there's some truth to that. Because of the success of generative AI and the need to have hybrid models agentic AI makes a lot of sense. Agentic AI can also bring forward some solutions that address some of the biggest challenges within just thinking about generative AI world that we were in last year. However, agentic AI also exposes a huge set of risk that you need to be aware of.

Brian Green [00:50:08]:
I'm not going to talk about them today, that's not the focus. However, what I will say is one of my specialties I guess is focusing on AI governance first. So I have lots of tips and tricks around how you can look at governance first approaches which will minimize your risk. And for agentic AI there's a lot of complexity here, but it's quite doable. There's practical tips. You can boil it down to very simple steps and I think I'll be sharing one of those in a takeaway handout that we'll be linking that one that the PDF won't be ready today but it'll be there tomorrow, FYI. So I think, you know, that's one kind of practically focused things and I'm happy to talk about some follow up steps with people as well. One plug is if you look at my LinkedIn, just today someone tagged me in a publication that finally came out, was published today.

Brian Green [00:51:05]:
It's a monograph. I'm not the lead author. Ken Huang, my friend and collaborator, is the lead author. But I'm one of the, I don't know, 30 collaborators and co writers of the document. It just came out today. It's around agentic AI and risk and solution of red teaming. So if you check out my LinkedIn, the link's there. It's a free document.

Brian Green [00:51:30]:
I haven't had time to read it. The final one, I've only read the draft, but it actually has some very practical, focused solutions as well. Some of them are a little technical, but again I'll be putting together. I don't want to say Guide for Dummies because I hate that, you know, it's a trademarked, you know, whatever for dummies type book. But what I usually say is like simplified guide for or 101 version. So I said a lot there. I wanted to kind of wrap up and highlight some of the key themes that I think came through here. I know there's some questions that have also boiled up, some of which we've addressed in the chat, but there might be some that we want to kind of surface up here in some of our thoughts.

Donna Mitchell [00:52:18]:
And.

Jose Garcia [00:52:20]:
I think you just gave me and Don an idea for the next Webinar. But we won't go off piece.

Donna Mitchell [00:52:26]:
Yeah, I think. Yeah, I think so. Because I really like the idea of agentic AI, but there are a lot of risks for some organizations, nonprofits and those that have a lot of silos and divisions and behavioral or process and different areas. Agentic AI is exactly what they need, but you got to mitigate the risk.

Jose Garcia [00:52:48]:
This is the group hug, by the way. And I got something I want to. This is something actually somebody put in the chat about half an hour ago and this is something that keeps on surfacing. I think there's a legit. This is from jd. I think there's a legitimate concern amongst frontliners of all forms, particularly amongst the intern beginning of the professional ladder positions. I was working with AI startups and every subtle sweet pitch pivoted from wow, this is amazing. To this could take the place of X number of employees within the first meeting.

Jose Garcia [00:53:29]:
And this is something you keep on hearing about where senior leadership. The first thing is, who can we replace? And this is. I mean, people say, oh, don't be paranoid, but they're not paranoid. They know what the C suite is thinking. And it's also kind of concerning that they go there that fast. And it's probably not even the right way to think about it. You should be kind of empowering people so they can do their jobs better. They can actually be more productive.

Jose Garcia [00:54:02]:
Instead of like, who can I get rid of? Does anyone want to tackle that? Jason?

Jason Padgett [00:54:10]:
I'd love to. I'd love to throw something. I think from the employee standpoint, this comes from a mindset. Are you opportunist or are you, you know, Linus, carrying your blanket? Like, if, if AI is going to revolutionize things, whatever you're a subject matter expert in or whatever you're good at, and you become good with AI as well. Imagine how valuable you just became to your company. Like, there's a lot of opportunity there. When they stopped mining ice, you know, if I, if I didn't learn to be an electrician and build refrigerators and I wanted to keep that ice pick in my hand, then I'm kind of sol. But this, with every change comes infinite opportunity.

Jason Padgett [00:54:48]:
If you're an opportunist.

Donna Mitchell [00:54:52]:
Hey, Jose, I'm sorry, I was just gonna, I was just going to add to you. Would you any, anyone want to attack that? My first thing would be with the leadership. That mindset that we've talked about consistently needs to be with the leadership. That should not have been the first thing out his mouth or her mouth for anyone to hear, even if they thought it, it didn't need to be communicated because that is all about environment. That is all about treating them as internal customers. So therefore, when you are getting ready to do a transformation, mindset, education and being able to really have some empathy and humanize who you are and who they are, you got to start with your leadership. And I would start training, management training there at that time, even before you step into middle management and frontline, everybody would have to be on board at that point, top down.

Jose Garcia [00:55:53]:
You know, can I just say something? I know I'm blundering here because I'm a solopreneur, but I'm doing the same thing that I was doing seven years ago. See, now I'm using AI Now I'm busier. I've got to hire another person. I think that's the attitude. You know, grow your company, grow your head count. Oh, we're gonna have to bring on more people to help us. We're so busy now. Not like, how can we just get rid of people? That seems like a race to the bottom to me.

Jose Garcia [00:56:22]:
But that's just my take.

Lekha Mishra [00:56:25]:
Yeah, I also, yeah, I also want to add something like AI works best with the people. AI is nothing without the people, you know, so we have to change the mindset. It is not replacing the job. Like we have to take this leadership like it would be make us more productive if we are doing that efficiently. So without us, AI is nothing, you know, it is making us powerful. So this is something we have to change our mindset. It is not actually replacing us. No one can replace us.

Lekha Mishra [00:56:57]:
Human. No one can replace AI with AI. It works faster. We can be more productive. We can be more equipped. The things could be much more faster, you know, but no one can replace replace us and human minds, you know.

Jose Garcia [00:57:12]:
So you know what, we're going to the after party. We're actually going to wrap up the event because the after party is not going on YouTube. So I'm gonna like wrap up the event and go cut. But don't leave. We're staying. I'm just cutting. The after party doesn't go on YouTube. What happens in the after party stays in the after party.

Jose Garcia [00:57:37]:
And so final word. But don't go. Amani.

Dr. Amani Alabed [00:57:47]:
Yes. Right. So I think my final words would be you would want to empower your employees by making them practice and not just by talking to them about theory. So in that sense, you would want to make sure that you are training them to. As we were trying to argue for the whole event just to become better at what they are doing, not just say that you would be replacing what they are supposed to do on a daily basis. So it comes by fostering this kind of ecosystem. Not just saying that this is a project that's a standalone project for AI, but really going further by looking at how it's impacting the literacy of your people, the productivity of your people and so on.

Jose Garcia [00:58:34]:
Final word Jason.

Jason Padgett [00:58:39]:
I would say from everything I heard today, growth, mindset and lifetime learning from either an employee or an employer standpoint, use these things to multiply as force multipliers for what you're already doing and always be willing to learn more and you're going to thrive in the age of intelligence.

Jose Garcia [00:58:59]:
Final word Brian.

Brian Green [00:59:03]:
Let me come off of mute here. Yes, I agree with a lot of what was said here in the last few minutes. I definitely think that AI literacy and multi stage training approaches within an organization that focus on key understanding and change management and leadership development is critical. However, I also believe in interactive approaches to training and ongoing coaching and there I think you, you know, focus on skills. I think there's a several skill. Well I have a list of 10 skills related to AI and integration and understanding that I think are kind of fundamental. And then beyond just those basic skills I think it's also important to look at focused, you know, case studies or project related approaches. I know Jason has shared some recent examples not today but online of some really creative things that he's done with what I would call real people and within work place settings that are I think really some interesting approaches to how to use AI practically within, you know, a skill based approach.

Brian Green [01:00:26]:
I think there's lots of good examples of that that can be focused in your specialty area. So healthcare or other areas of focus like financial services etc.

Jose Garcia [01:00:42]:
Final word?

Lekha Mishra [01:00:46]:
Yeah, thank you again for the great questions. So guys, if you are in today's session, if you think like you there is any ideas that you think like can you how to support how to use AI to support your frontline team and you need details over it and you you are unsure how to get started, what the first step should be and you are not aware of it then here we go. We are having one to one session in this month. Few sessions are available there so we can connect and talk there more about it here. This session would be short focused and we will go through your existing workflow how AI can be integrated in your existing workflow. We can create a roadmap accordingly and create a clear path to the real results. So if you are interested, you can. Yeah, we can.

Lekha Mishra [01:01:39]:
We would love to connect. Or you can simply add AI calls in the chat. So I'll approach from there. Yeah. Thank you.

Jose Garcia [01:01:48]:
Donna, do you want to close the event and say goodbye to YouTube?

Donna Mitchell [01:01:52]:
Oh, YouTube. Yes. We're not going to be on YouTube. And I'm really glad everybody is here. It was a great exchange. Awesome question. Questions. And the speakers, experts, as usual and very professional.

Donna Mitchell [01:02:04]:
So stay tuned for where we're going forward. We're going to the after party right now. And be glad to join us and stay on the line. Thanks for attending.

Jose Garcia [01:02:12]:
Hi. Thanks to you. The audience. The audience.