Ep 247: AI – Your New BFF or Tech Terror?

The Impact and Challenges of AI

The strides in Artificial Intelligence technology and its democratization have been strikingly similar to the impact of electricity on industries in the yesteryears. Increased adoption and capabilities of AI at individual and enterprise levels mimic a revolution, transforming organizations and reshaping industries.

Breaking down Barriers: The New Reach of AI

Advancements in technology, augmented data literacy within organizations, and decreasing entry barriers have made AI implementation more accessible than ever. The business world is experiencing an AI-driven evolution—akin to a new electricity age—where both enterprises and individuals leverage AI, transforming their operational capabilities.

Recalibrated Conversational Systems: How AI Transforms Businesses

The world of AI has changed conversational systems beyond imagination. Decreased infrastructure costs facilitate business transformation at a broader scale. Simultaneously, these AI transformations are reshaping perceptions, sparking debates between the tool's beneficial potential against its possible threats.

The Evolution of Enterprises with AI Technology

However, with this swift evolution, enterprises face challenges in addressing, tracking, and communicating about projects and undertakings. The future of business comes with technology—collaboration tools and AI-backed enterprise testing tools are becoming increasingly important. Data security also plays a crucial role in tech developments, enhancing workflows and offering unmatched convenience and efficiency.

Visualization Dashboards: Enabling Efficient Stakeholder Engagement

Leveraging visualization dashboards like Power BI and Google's features can help understand and manage multi-stakeholder engagements, making workflow easier. Emphasizing on investing in enterprise education allows businesses to equip their employees with the future's most relevant technology—AI.

The Advent of Generative AI in Businesses

There's no doubt that large language models have a place in modern business strategy. To tread on this path, leaders might consider participating in courses tailored to help users learn how to maximize the tools like ChatGPT. Real-life examples from successful entrepreneurs underline the usefulness of large language models when utilized correctly. Post-taking such a course, refined 'prompting' and coaching protocols for AI models can lead businesses to harness the true power of AI.

Safeguard Your Future: Invest in AI

Incorporating AI into daily tasks can drastically boost productivity. However, with increasing AI utilized in tasks, there's a rising risk to those not utilizing AI—especially in the context of job security. It's essential to invest in both technical and soft skills, promoting the coexistence of humans and AI. After all, the future of all businesses lies with AI.

As business leaders, it's crucial to remain vigilant about the potential of AI. The importance of generative AI in businesses cannot be overlooked as those who fail to integrate AI could be left in the competition's dust. While traditional companies face the challenge of change management, examples like Tesla disrupting the automotive industry through AI reflect the transformative power of AI. The way forward? Embrace it, leverage it, and advance with it. After all, the future of business relies heavily on AI integration.

Topics Covered in This Episode

1. Evolution and democratization of AI technology
2. AI in the Corporate Sector
3. AI in Education and Skills
4. AI Integration in Daily Life
5. AI's Disruptive Influence


Podcast Transcript

Jordan Wilson [00:00:18]:
Can artificial intelligence be both a good thing and a bad thing? Is AI your new bestie, or could it be a tech terror? We're gonna be talking about those things to today and more on everyday AI. What's going on, y'all? My name is Jordan Wilson. I'm the host of everyday AI, and we are your daily livestream podcast and free daily newsletter, helping everyday people learn and leverage generative AI to grow your companies and to grow your careers. So if that is you, I think you're in for a treat today with our guest, and we're gonna be talking about that the highs and the lows, the pros and the cons, and if AI is your new bestie or a tech tear. I'm excited for this one. But before we get started, we're going to start as we do every day with our AI news. And as a reminder, whether you're listening on the podcast or joining us live like Rolando from South Florida or Tara checking in from Nashville, Woozy from Kansas City, Make sure to check out today's show notes as always for more and on our website at your everyday ai.com. Alright.

Jordan Wilson [00:01:23]:
Let's get into the AI news for today. So first, OpenAI has released and updated its GPT 4 turbo with new features. Alright. So OpenAI has officially launched and updated GPT 4 turbo with vision in the API and within the chat gpt interface, featuring what the company is calling significant improvements over its predecessor. So some of the more technical updates now include the ability to analyze text in JSON format and execute function calls, enabling developers to automate tasks like sending emails, posting online, and making purchases. Also, the knowledge cutoff date, which this is a big one, will reportedly be moved to December 2023, enhancing, the model's relevancy and accuracy. So big jump there from April 2023 to, December 2023. Also, competition in the AI space is obviously intensifying with Anthropic's cloud, Opus 3 or cloud 3 Opus surpassing gbt 4 in some closed source model rankings, while Google's Gemini Pro closely follow suit.

Jordan Wilson [00:02:36]:
Speaking of Google's Gemini Pro, new updates there as well. So Google has introduced Gemini 1.5 pro with some advanced capabilities. So Google's latest update equips Gemini 1.5 pro with the ability to process audio files directly, enable it to extract information without relying on written transcripts. So this announcement came part of goo came as part of Google's Google Cloud next 2024 event going on now. Google announced the public release of Gemini 1.0 1.5 pro via its Vertex AI platform, which is where it's available now if you want to go, play around with that. So Gemini 1.5 pro supports processing prompts containing 1 hour of video, 11 hours of audio, 30,000 lines of code, or over 700,000 words in a single stream with that large 1,000,000, token context window. Alright. Last but not least in AI news for the day that's, been twisting my tongue, but Intel has unveiled its gaudy 3 AI chip, a what they're calling a game changer in the semiconductor industry.

Jordan Wilson [00:03:45]:
So Intel has just introduced its Gauzy 3 AI chip at the WEF, the World Economic Forum meeting in Switzerland. So the Gaudi 3 chip is, apparently, according to Intel, over twice as power efficient and 1.5 times faster than NVIDIA's h 100 GPU offering enhanced performance for AI models. So we'll see once the benchmarks come out. But if this is true, that's pretty big news, from in, from Intel. Obviously, NVIDIA has announced its newer chip, so we'll see where kind of the benchmarks, fall with all of these things. Expected availability for the new chip, for customers is, coming in the Q3 with collaborations from companies like Dell, Hewlett Packard Enterprise, and Supermicro. So Intel is aiming for competitive pricing against NVIDIA's latest chips, emphasizing open integrated network on chip and industry standards. Alright.

Jordan Wilson [00:04:42]:
So exciting. So we had big model news today, big chip news, but, I'm excited to talk AI now, y'all. Like, I like, one thing I love is is, you you know, bringing our our livestream audience the ability to, you know, learn live from experts. So very excited, to bring on to the show. Let's go ahead. There we go. So welcoming to the show. We have Sheetal Rishi, an AI transfer my, transformation leader.

Jordan Wilson [00:05:08]:
Sheetal, thank you so much for joining the Everyday AI Show.

Sheetal Rishi [00:05:12]:
Perfect. Thank you for having me, Dalton. Nice to be here.

Jordan Wilson [00:05:15]:
Alright. So much going on in the world of AI, but tell us, a little bit about your background. Sure. Oh, yeah.

Sheetal Rishi [00:05:21]:
I by the way, I loved, the daily 3 minute update that everything that's going on in the world of AI, and I think you do a great job in picking up what really matters, I think, the top of top news. So thank you, Jordan. That was fantastic to hear. So my background, I've been in the industry for I've been a professional for almost 2 decades, feels like just yesterday, and I'm still learning in my journey. When I started my career at McKinsey, did a lot of business strategy transformation engagements across the globe, advising c suite of customers essentially or what they could do to transform new business challenges, new opportunities, how do you grow, and stuff like that. And then from there onwards, I I had an opportunity to work with, financial institution, Citibank, for a couple of years, actually deploying a lot of my advisory to the to the to the bank itself, you know, how to transform and build the effort. There was something called 1 city that was part of that. So a lot of fun, exciting, learning experiences on what does it really take to deploy some of your own advice.

Sheetal Rishi [00:06:19]:
I think I'd like to say that to myself. And from there onwards, I'm sure you have heard of, Deputy. So IBM Watson was the first or one of the first supercomputers, if you will, for the lack of a better word, that actually took on the challenge to defeat, in humans in the game of Jeopardy. If you haven't seen it, you must check it out. There's a lot of great YouTube videos about that particular episode. So I had an opportunity to work with IBM, spent close to 7, 8 years using AI, to actually solve for some of the most pressing needs, you know, of the world, if you will. And then a couple of years in the middle between with, you know, deploying AI, building the infrastructure itself, you know, at HPE. What does it take? So the announcement about Intel especially of relevance, you know, and and of interest as well to go back and figure out what is this chip going to do and how is it going to impact my current customer base, I think is what, I'm really intrigued about.

Jordan Wilson [00:07:19]:
Yeah. Yeah. So I'll I'll go ahead and say this out loud. Your your background is extremely impressive. Right? So you worked with some of the largest companies in the world. You know, you mentioned, you know, IBM, HPE, Citibank, McKinsey. So, you know, I'm curious, you know, from someone that has a deep background, you know, working in artificial intelligence and in business, you know, in business in general. How have you seen kind of the business world change, you know, specifically since generative AI.

Jordan Wilson [00:07:47]:
Right? Since, you know, traditional AI has has been used for decades. But from your vantage point, how has the generative side, really changed how businesses operate?

Sheetal Rishi [00:07:58]:
That's a great question, Jordan, and I've I I has it changed? The answer is absolutely yes. You know? There's a lot of boardroom conversations. I mean, the fact that we this morning at 7:15, your time, I think, and talking about AI should be very revealing that there is just a lot of excitement, a lot of hype about AI itself. AI is not new. I think the cat is out of the bag, and that's how I see it. We've already been using different forms of AI. Again, you know, just to throw in some more terminologies here, machine learning or deep learning is not relatively new. You know? I think it's been around 9 since 19 fifties sixties.

Sheetal Rishi [00:08:38]:
I wouldn't call it a well kept secret, but probably it was one of those things. It was accessible, but we did not have the infrastructure that is required to scale and use these technologies, you know, at at larger scales. So just like, you know, what electricity did to the industry back in 18 eighties, when Edison literally had the first light bulb moment. Right? He started off in, I think, in 18/82 in New York. There were about 50 buildings that were lit up. They were the first one. There's obviously there's a lot of excitement about it, about Lexiti itself, and there was also a lot of concerns. You know, what if people start getting electric shocks, if you will? What it can do? What's the capacity? I think we're in a similar revolution right now if you think of it.

Sheetal Rishi [00:09:24]:
So the boardroom conversations are definitely picking up on how can I use AI, and I'm using AI as a very generic broader terminology? The technology capabilities have become astronomically different is what I can tell you. And I was listening to another podcast myself last evening, and it was interesting to hear a comment again. There's just so many statistics around us, which sometimes I wonder which one to follow. But I think the net of it was that the speed of capability advancement over the last 10 years is is just phenomenal that you and I can actually use AI, our ourselves as individuals without having to invest, you know, 100 and 1,000 of dollars. So I think the capability itself has been democratized. It's available to larger audiences. So what will happen with that really depends on human creativity and human capacity. At an enterprise level, I am seeing much wider adoption of where it was.

Sheetal Rishi [00:10:22]:
A lot of still, you know, barriers to entry, if you will, from an infrastructure capability capability perspective, the amount of data integrity that's required in enterprise, regulatory requirements, the skills of the humans itself, we're actually gonna deploy it. There are those, but I think those hurdles are becoming smaller and smaller as we move along. So the next 5 to 10 years of how we do business, how we see business, you know, it could be financial, it could be health care, would be very, very different from what we've seen in the past in my opinion.

Jordan Wilson [00:10:51]:
Yeah. And and, Sheetal, you you know, you kinda mentioned that, yeah, AI goes back many decades, you know, back to the fifties sixties and the expert boom of the, you know, the experts boom of the eighties. But, you you know, something you mentioned there that, you know, hopefully we can, you know, talk about here quick is, you know, Watson. Right? So, you know, working, you know, on the Watson team, I think, you know, that was at least even for me, that was kind of my first, you know, kind of introduction to AI. Right? When you had an AI, a supercomputer go on Jeopardy and win, you know, maybe how do you think the conversation has changed, right, in in the past, you know, 12 12 or 13 years since Watson, you know, went on Jeopardy, and I think that really opened a lot of people's eyes to what was capable, with AI. So, you know, as someone who is involved on the Watson team for for a few years, how do you think that the conversation has changed since that very pivotal moment?

Sheetal Rishi [00:11:48]:
Yeah. Great question. And, again, I think, three things that stand out to me, when I'll try to boil the ocean here. 1 I think number 1 is Watson itself so conversational systems. Right? They're typically you ask a question, you get an answer. And the way they were trained, we used to call them short tail, long tail question. Short tail was frequently asked question. What's your address, Jordan? That's a, you know, short tail question.

Sheetal Rishi [00:12:26]:
Hopefully, you're not asking what is your address, somebody else is asking for you. But in the world right now where we are, if I would ask the same question, I think technology has become smarter enough to actually triangulate, pick up pieces of information from different sources, and compile what is called as generate an answer, and feed it back into you. That is one big difference. I don't necessarily have to have question and answer pairs versus, you know, I can give you a dump of data and the patterns are being recognized just as we as you're building a sentence, we need to know where the verb goes, where the noun goes, where the subject and predicate goes in the language. Right? Technology does it for us, infuses the words, and I think the accuracy rate is, if you haven't used chat if anybody has not used chat GPD, please guys go and try it. I think and, again, I'm not advocating for one technology, but there are many different versions of chat, GPD, or Gen AI conversational systems. Go use it for yourself, and you'll see how it has evolved. Right? Number 2 was the the data literacy itself in organizations.

Sheetal Rishi [00:13:28]:
So back in the days, a lot of my conversations will begin with, you know, this is AI, this is ML, this is deep learning, this is how the neural networks run. I think the conversation has gotten much smarter now. The enterprises, employees, executive across 360 degree board, I would say, you know, the the newbies definitely are way ahead. People who've been in the industry and the executives, their level and appetite and understanding of technology is much far superior than what it used to be. And part of this is, I think, driven by the fact that many hyperscalers, many education institutions, you know, Coursera's, edX, MIT, they're offering courses that anybody can go indulge in. So I I think plus enterprises are having structured programs about AI, and I think it's the gamification of education industry in this space has completely up leveled the bar in terms of what I know about technology now versus what people generally knew about 10 years. Back in the days, people had sort of heard about it widely. It was a child, you know, poster child of everybody.

Sheetal Rishi [00:14:28]:
I wanted to know about it, but I think this the skills level skills, parameter in the industry has really evolved significantly. The third piece is back to the infrastructure side of the story. So a lot of times, I would go, we'll build many POCs, demos, prototypes. It would take probably couple of days to a week or multiple weeks to build the demos of these AI and edited solutions, which is fantastic. But we were really getting caught up in the infrastructure and then big bigger issues around how can I infuse data in real time? So if a certain information has changed, how is gonna that impact the model? And the model throws a different result. So those limitations I see are getting much better right now. So things that costed $10,000 per unit, and, again, I'm saying unit as an example of storage compute network, The cost and the speed at which we could access them has probably is probably, I would say, you know, few hundred times cheaper. I'm probably gonna just throw a number out there.

Sheetal Rishi [00:15:30]:
I think it's at least lower by 1,000 right now. So if anything that cost you $10,000, probably at $10 right now available out there. So there is huge transform exponential, you know, transformation going on. So imagine what could happen the next couple of years. I I don't wanna look out 10 years quite frankly because I think there's just so much unknown out there. But But in the next couple of years, I see the opportunities really enhance significantly.

Jordan Wilson [00:15:57]:
Yeah. And that's that's such a great analogy that you said. You know, the compute, you know, that used to cost maybe $10,000 might now be 10,000 and and what that means for business transformation. And I think that has a lot of people both excited, but also maybe nervous. Right? Because if if they're not, you know, adaptable enough, I think now more than ever, companies are feeling like, oh, I might get passed up because it is so easy, you know, to implement, you know, data transformation, you know, company wide. So, you know, that begs the question, right, to our original topic here is is AI your your new bestie or your tech terrorist tech terror, which I love that. But, Sheetal, like, can it be both? Can AI, like, be your your your best friend, and can it be a tech terror, or does it depend on, you know, your your leadership and your ability to to implement AI?

Sheetal Rishi [00:18:02]:
Again, it's, I think there's a lot of debate in the industry right now that is AI going to replace humans. Let's face it. You know? I don't know the answer to that yet with and I can't say it with 100% confidence what will be the future of jobs looking like. But I do know that people who use AI versus who don't use AI, they're definitely at risk. Right? So start incorporating AI in your in your daily lives, if you will, and not just for, you know, going on Netflix or Amazon Prime movies and picking up letting the computer tell you which which which topic you should watch, which movie you should watch, or whatever episodes you wanna watch. But use it to your advantage and use it for your own efficiency improvement, for example. And most of the organization enterprises, I urge everyone out there that, because the employees will use it. Right? And employees can use it.

Sheetal Rishi [00:18:53]:
They're pretty vulnerable, in my opinion. I mean, start at home, your children, especially, for example. In New York, back in the day, I think again, back in the day, it feels like. But I think when OpenAI chat GPD came out first, there was there was a lot of nervousness. There is gonna be a lot of plagiarism. So kids should not be using AI, but I don't think that's the way to fight with the technology. We don't have to. It's always going to be human and AI.

Sheetal Rishi [00:19:16]:
Think about a scenario when you can use a machine to actually do the task for you, but you still own the decision making capability that what task and what outcomes are expected out of you. I think then it's it's your best day. But if you still tend to do operate in a place where you're trying to compete with AI and memorize things and try to win over it, that's not gonna happen. So if your tasks if your daily work involves lesser of judgment, lesser of rules based decision making, I would really encourage everyone to start elevating, you know, your own profile, your own value add that you bring in because in my opinion, the tasks that are more rules based, data entry type jobs, and they're just a task in itself. They're not interconnected to one task after the other. Probably are going to be at the highest risk of being disrupted in the near future. So that's where that class of people is definitely a teller. Now is it you use it as your bestie or as, you know, someone's gonna replace you.

Sheetal Rishi [00:20:14]:
Totally depends on you. How you're gonna uptick yourself. You know? Invest in yourself. Prioritize yourself is what I encourage everyone. Independent small business owners, you know, individual contributors in enterprises, large scale business owners. Whoever you are, it's for everyone. The good news about AI is it's just like LexiTi, you could do anything. You could turn on you could turn on a computer.

Sheetal Rishi [00:20:34]:
You could turn on a TV. You can turn on a light bulb. You could do what you want, you know, what you what what your needs are. I don't think anyone you should need to wait for somebody else to come and tell you what your needs are. If you can identify where where you want to play, there's a lot of AI policy, AI governance, training, AI, securing AI. Cybersecurity is gonna be a big hot topic to go after. Depending on what skill sets you have, go and invest in your technical skills, on your soft skills, on a domain knowledge. Pick up an industry, banking, health care.

Sheetal Rishi [00:21:02]:
Everybody's AI will look different from the others, quite frankly. I don't think there's gonna be one solution that fits everybody. So pick up your battle, operate, you know, elevate your game, your skills in in your specific area that you wanna go after, and I think you're gonna be fine. AI will be your best bestie.

Jordan Wilson [00:21:19]:
So I love what you said there, Shital. Like, if you're if if you're trying to compete against, AI, that is when it will or could become a a tech terror. So one thing that I'm curious about, you know, you have a very, you know, deep background in working in enterprise. You know, if if if you're just joining us in the middle of the show, you know, maybe maybe you missed, you know, your your background there. But working, you know, at at Citi, working at, HPE, working at IBM. You know, there was a study recently, I believe from Cisco, a 2024 study that said still 27% of enterprises are banning generative AI use. With that in mind, do you think you know, just speaking generally here, do you think that those type of companies is AI going to become a terror for them? Or, you know, at least in the foreseeable future, is it gonna be hard for enterprises to compete if they're not using generative AI from top to bottom?

Sheetal Rishi [00:22:18]:
Again, this is me speaking. I do not represent my enterprise as an organization. I work for personally, the pace at which I'm seeing technology and how useful it is, I really think if anybody decides not to invest, we'll be left behind. I'm also a little surprised in my eyes, my head rose when I hear that number from Cisco. And I'm not saying that's a wrong report, but I I'm really thinking, they're probably more laggard. A lot of conversations, I definitely can speak with experience, a firsthand experience of that about AI. I do understand, AI is not click to deploy. Right? It requires I think building solutions is probably gonna be faster than driving adoption.

Sheetal Rishi [00:22:57]:
So enterprises are really looking to, you know, I think, understand how you apply, how do you drive change management in your own enterprises, legacy enterprises especially. And I think that's one of the reasons why you see startups in almost every sector because they are able to there's not a lot of legacy. You know? So there's a famous book, that recently came out, the fusion strategy. If you haven't checked it out, someone people might wanna read it. But the company really dramatically talks about automotive sector, multiple sectors actually. You know? For example, I mean, the way Tesla came up and about, and they were able to, you know, disrupt the traditional GMs and Ford Motors of the world, you know. And and and I think with all due respect, the legacy automotive companies are still trying to catch up with how the software automaker has actually turned the entire industry around how to introduce the first electric vehicle in the market. So there is definitely an internal resistance both from a skills infrastructure and what to prioritize and the investments required to transform a legacy company.

Sheetal Rishi [00:23:57]:
So it's a matter of time, in my opinion, that when these legacy companies will turn around. So I don't think there will be any company that is not an AI company in the near future. It's just a matter of time.

Jordan Wilson [00:24:10]:
Wow. That's, that that really makes you think about, you you know, the future of business and and where, you know, us as as business leaders and, you know, leaders in our organization should be focusing on. I I think that's, some very, you know, powerful words with someone from a lot with a lot of experience. You know, you're kind of mentioning, you know, different, you know, you talked about the book and we'll, you know, make sure to link that in our newsletter today recapping today's show. But maybe are there any, Sheetal, many maybe any good use cases that that you've seen recently? Because that's, I think, something people are always interested about. Right? Like, people want first. They they they wanna be able to win back their time first and foremost, and then they start to worry about, like, hey. What are some good use cases, from your vantage point? Maybe what's a good use case that you've seen where companies have maybe actually correctly leveraged, AI and it became their their bestie?

Sheetal Rishi [00:25:04]:
Yeah. Couple of things. So I think many of us who are in corporate sector probably spend hours and hours of attending meetings and then hours and hours of, synthesizing what we heard, what the priorities are, and then hours and hours on tracking, what should be done, and then hours and hours on communicating, making sure that the entire project end to end, everybody is on power. So I'm connecting multiple steps here. Right? So the use multiple use cases and rituals could be, please use AI. Again, I would encourage you to use AI for people in the in the companies. Use AI that's approved by your enterprise. So GitHub Copilot is one of the most fanciest thing that I think all engineers are wishing and craving, man.

Sheetal Rishi [00:25:47]:
I wish I had it back in my days. You know? So those are great examples of how it's helping, in your code development itself and collaboration on code. So use IncorporateJNI for your own efficiencies. If you're going into a meeting, please urge your enterprise organization essentially to help you leverage a Gen AI, technology. And I think it's a CIO and CTO's nightmare right now because if you don't allow, people are still gonna be able to use it because they're out there. You know? It it it is available so easily. So use it for your own recording meetings, documenting your meetings, and sending minutes out, synthesizing what matters, what doesn't matter. It's a huge time saver.

Sheetal Rishi [00:26:24]:
You could do it much, much faster. But, again, I don't wanna encourage go wild, wild west. Please use it as approved by your enterprise because there's just so much of enterprise data and the issues around data security and privacy. We're still going through them. So use what you are allowed for. If you're not allowed for anything, definitely talk to your CIO and CTO organizations who are who are, I'm sure, are working round the clock to make sure that technology reaches you faster than you think. The other thing that we incorporated for my own work was a visualization dashboard essentially pulling the is there multiple stakeholders involved in your own engagement? So you know exactly where you play, but you also know people who come before you and after you from an end to end supply chain, how are they doing. So online, live, workflows, if you will, with with a very simple visual, that is something I think every business unit must look to invest and build it very simp again, I'm I'm not here to talk about vendors and products, but, Power BI for Microsoft has been my most favorite most recently.

Sheetal Rishi [00:27:23]:
Google has come up with a lot of feature functionalities that lets you build these visual. You don't need really to know the SQL code to actually build a program and then go deploy it, and then the governance becomes a nightmare. But I think these tools are much simpler to use. Please incorporate that, right, in your in your in your life. So 2 tools. Anything that helps you document stuff and anything helps you visualize your stuff that you can then democratize and collaborate with your peers across the world, try to build start there, you know, I think.

Jordan Wilson [00:27:53]:
Wow. So, y'all, I don't know if anyone else is is feeling like I am right now, but I have so many notes here, like so many great takeaways. I I actually think I have more notes from the conversation than I did preparing for today's conversation, but, you know, so, Sheetal, we've we've talked about a lot, but as we wrap up, because we've gone over how AI has changed over the decades, some great enterprise implementation tips, AI optimization versus job loss, practical use cases. There's been so much good, you know, so much good information from our conversation. But, you know, as we wrap up, maybe what's your one, main takeaway, that you can suggest out there to business leaders, whether it is, you know, a small business CEO, whether it's someone working in an enterprise right now in charge of AI implementation. What's that one thing that maybe companies should be doing, to make sure that AI is actually their best friend and doesn't become a terror?

Sheetal Rishi [00:28:51]:
It's a great question and puts me I wonder because there's definitely more than one thing.

Jordan Wilson [00:28:56]:
It's hard. Right? It's hard.

Sheetal Rishi [00:28:58]:
It's the hard one. Yes. I really think I think we humans are very, very smart. Innovation is distributed in our times today. Right? It's not in the hands of 1 or 2 people telling us what to do. So I think we should enable innovation. We should enable creativity. And how what I mean by that is that as an enterprise leader, I think I'm a big fan of learning, and this is a team sport.

Sheetal Rishi [00:29:25]:
So if you know something and I don't know something, we're not gonna be able to move the needle here. So I think enterprise wide, it's a revolution. So invest in learning, give the tools to your employees so they can come back to you with solutions. So, I heard a comment that's interesting. Distracted with that, but yes. Absolutely. So nineties, main con. Who does that in these days? So invest, educate.

Sheetal Rishi [00:29:52]:
I think investing in enterprise education will help you as an enterprise leader so people are not distracted. There's just so much being thrown at us at at astronomical space. So if we can create structure, you know, just like in an academic institution, these are structured environments to promote education. I feel like I think within enterprise itself, the learning function has to be very well thought through. It'll obviously require inputs from what the company's strategy is, who you want to be, what kind of skills you want to develop, what do you wanna what do you want to be known for. Right? So it should infuse. It should boil down to that learning catalog, and then that should get passed on to different roles in the organization. ABI AI will be embedded in each and everything that people are doing.

Sheetal Rishi [00:30:38]:
Data scientists, engineers, architects, business leaders, you know, finance leaders, HR person. I just can't think of any function in an organization that will not that does not have a use case for AI yet, in my opinion, you know, with respectfully. So let's start with enabling our teams, our people with the right tech that's relevant to our strategy.

Jordan Wilson [00:30:58]:
I I I love that, Sheetal, that saying that AI is definitely a team sport. Right? And I I think that sometimes people don't think of it that way. So thank you, for joining us. Thank you for putting all of this, into perspective and for sharing your insights on the Everyday AI Show. We really appreciate your time.

Sheetal Rishi [00:31:16]:
Thank you for having me. It's great.

Jordan Wilson [00:31:18]:
Alright. And, hey, as a quick reminder, there was literally so much great information there that she tells, shared with us. So, if you haven't already, make sure to go to your everydayai.com. We're gonna be recapping everything that was said because maybe like me, you were jotting down notes, but you still couldn't keep up with all the great insights. So make sure to go sign up for the newsletter. We'll have more there, and we'll have more the rest of this week and every day. So please join us for more everyday AI. Thanks, y'all.

Sheetal Rishi [00:31:46]:
Sounds good. Thank you.

AI [00:31:49]:
And that's a wrap for today's edition of everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit your everydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers, and we'll see you next time.

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