Ep 72: How Startups Can Adapt to AI Innovation

August 3, 2023

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Overview

As the business landscape continues to evolve, the integration of Artificial Intelligence (AI) has become a hot topic among entrepreneurs and startups. With the potential to transform industries and revolutionize customer experiences, AI is undoubtedly a game-changer. However, navigating the AI landscape can be daunting, especially for startups looking to adapt and innovate. This article explores key considerations and strategies for startups to effectively incorporate AI into their business models and thrive in an ever-changing market.


Understanding the Market Fitness:

Before diving headfirst into AI integration, startups should critically evaluate their market fit. Identifying the right problem to solve and assessing market demand are crucial steps. Ask yourself if there is a genuine need for your solution and if customers are willing to pay for it.


Differentiation and Communication:

With several startups working on similar problems, differentiation is key. Startups must effectively communicate their unique value proposition to attract customers in a crowded market. Utilize customer testimonials and educational content to build customer loyalty and establish your brand as an authority.


Customer-Obsessed Approach:

The success of any startup ultimately lies in meeting customer needs and understanding their behavior. By placing the customer at the center of decision-making, startups can create tailored solutions that resonate. Gather customer feedback and iterate on product design and implementation, ensuring that resources are invested in addressing their pain points.


Responsible AI Development:

As AI becomes more prevalent, it is crucial for startups to prioritize responsible development and usage. With AI-powered technologies, there are both productivity benefits and potential ethical concerns. Stay informed about the latest regulatory measures to ensure compliance and avoid any harm to society.


Integrating AI with Other Technologies:

While AI is undoubtedly powerful, it should not be viewed as a standalone solution. Startups should consider combining AI with other emerging technologies, such as IoT, metaverse, and blockchain, to effectively solve customer problems. The integration of these technologies can unlock new possibilities and enhance the overall customer experience.


Conclusion:

Incorporating AI into a startup's business model offers immense potential for growth and innovation. It allows entrepreneurs to develop cutting-edge solutions and enhance customer experiences. However, successful integration requires careful consideration of market fit, differentiation strategies, customer-centric approaches, responsible development, and maintaining focused efforts. By aligning these strategies, startups can adapt to AI innovation and position themselves for success in a rapidly changing business landscape.


Topics Covered

- Introduction to the prevalence of AI in various industries
- Mention of recent investments and developments in AI technology
- Introduction of guest Xiaochen Zhang, with experience in fintech startups
- Discussion of challenges and considerations for startup founders in relation to AI technology
- Questions raised about the difficulty of raising funds without incorporating AI
- Weighing the pros and cons of integrating AI into startup offerings
- Personal experience with Lemalist emphasizing the importance of involving customers in development process
- Question about startups using AI as a tool for tasks like finding new market segments and designing products
- Mention of AI-powered products like ChatGPT and coding tools
- Four key questions for successful tech products: problem, market fitness, customer, and pricing model
- Role of AI in improving products, reducing costs, and shortening time to market
- Possibility of creating new products to solve adjacent problems and tap into new markets
- Caution against solely focusing on AI as a distraction for existing products and problems
- Importance of responsible development and use of AI, considering ethics and potential harm


Podcast Transcript


Daily AI news


Jordan Wilson [00:00:17]:

How can startups use AI? And what does it mean for everyone else? Right? There's AI just about everywhere you turn and look right now. So that is one of the things that we're gonna be talking about today on everyday AI. My name is Jordan Wilson. I'm your host. And as a reminder, this is for you. This show everyday AI, it is where we can learn about AI together and how we can leverage it in our daily lives. So if you're joining us on the live stream, welcome. If you're joining us on the podcast, Make sure to check the show notes. come join us on the livestream as well. Also, make sure to check out our daily newsletter, your everyday ai.com.

So before we talk about the world of startups and how startups can even adapt to innovation in the AI industry because it is going at a breakneck pace. Let's first take a look at what's going on in the world of AI news. There's a lot. Alright. So 1st and foremost, a chip mech chipmaker has brought in a big investment. So the AI chip firm, Ten Storeant, has raised a $100,000,000 from Hyundai and Samsung. we obviously talked about Nvidia earlier in the, earlier this week and talked about how important these these GPU chips are not just for startups and the AI industry, but even for how we're now function functioning in our day to day, using all these AI technologies. So something to keep an eye on there.

Next, Google's AI searches getting smarter. So, Google has their new SGE feature, which is essentially generative search. You know, it's getting rid of the old traditional Google and bringing in, kind of this this next phase of AI powered search from Google, you do have to have that enabled in your search lab. So we'll share about that in the newsletter. But if you do have it enabled, you're gonna start to see a lot more multimedia results now coming in, you know, not just plain texts. You're gonna start to see a lot.

Alright. Last but not least, Meta Meta's llama 2 may have a new open source competitor. Alright? So we've talked about this on the show as well. Meta has released LAMA 2, which is essentially an open source alternative for something like GPT or chat GPT. So, Meta made huge news when when they announced that this was open source and Lama 2 was out, but, Alibaba has just rolled out their version of open source AI model. So a lot going on in the open source large language model, kind of race. Right? So I'm excited. I'm excited for today's conversation. we already have a ton of of comments coming in. A lot of people joining the show. So with that, let's let's start talking. Let's start talking startups and how they can adapt to AI innovation. So I'm gonna welcome in my guest for the day who has a just great background in working with startups for a very long time Shaojin Chang is the president of Fintech for good. Thank you for joining us.

Xiaochen Zhang [00:03:35]:

Thank you for your invitation and looking forward to conversation.

Jordan Wilson [00:03:39]:

Oh, yes. Oh, jeez. It's every everywhere you look now, I feel so many startups are are raising money. and, you know, startups you didn't think would be using AI. They're using AI. But before we get into that, just tell everyone a little bit about your your backgrounds. working with startups and and fintech for good, because you're you're involved in a lot of ways, but just just tell people how you're working with startups right now.

Xiaochen Zhang [00:04:03]:

Sure. And the FinTech for Good is a venture building studio where that's, we help her basically identify the most promising, emerging technology based startups and then bring the right ecosystem around them and help them to grow to be successful. And of course, that's uh-uh the startup that we focus on need to solve the right type of problem that's a, you know, because the full good part is really as important as the tag part where that's, you know, we hope that's our startups, the are able to bring positive, change to the world including, financial inclusion, poverty redaction or economic growth, gender equality, and, climate change all all the environmental protection. Those are the type of the problems that we hope that our startups can just help to solve.

Jordan Wilson [00:05:03]:

Yeah. And you must look at a ridiculous amount of startups. You know, a lot of people probably looking to fintech for good for support, mentorship, investment. Right? So first of all, how many startups are are you looking at and Have you seen any change, you know, over the last year or so, you know, kind of with this new, not just the generative AI boom, I would say, but it also seems like there's a lot more money now, on the VC side going to startups that are, you know, trying to incorporate AI into their product their service, their service or their offering. So, yeah, just just talk about just the number of startups you're you're you're seeing. And if you're seeing any change or trends with with how they're using AI.

Fintech and AI


Xiaochen Zhang [00:05:49]:

Sure. And, FinTech will start you know, in 2017 where that we've had a lot of focus on blockchain and, you know, just recently we, you know, included the artificial intelligence as another core focus before, you know, on a weekly basis or even a monthly basis, and we may just look at, you know, 1 or 2 AI startup, but the rest are really, you know, blushing startup. But so just from, you know, chat JPD was introduced and then the startup community, entrepreneurs are really responding to the markets, the fattiest, you know, faster than than, capital faster than corporate, faster than government. So then immediate, many of the the star star the the entrepreneurs started to really build a very exciting AI based or general AI based, innovations which are pretty exciting. And then on a, you know, weekly basis now that we are looking at at least 10 to 15 AI based startups for now. Yeah.

Jordan Wilson [00:07:06]:

You know, and do you I'll ask this because, you know, there's a a story a couple weeks ago that kind of kind of made headlines. it was a a a group of, you know, former you know, a group of former people that that worked at companies like like Meta, you know, big names, and they they created kind of a generative AI company. And before they even had a product, they had raised more than a $100,000,000. Number 1, is that is that a good thing? and and do you see that as a problem, at least for startup founders, maybe that have a great product, a great service, a great offering, and maybe they're just not generate, they're not using AI really, in in any marketable way, at least, So do you see a problem with maybe an over reliance on AI, at least when it comes to fundraising?

Startups benefiting AI market, but caution long-term


Xiaochen Zhang [00:07:57]:

Yeah. So when the answer to, you know, whether it is a good thing or bad thing, you have to say that, you know, the good thing for whom. And, you know, for the market, in general, you know, if you look at it as a startup community, that's a good thing because, in the sense that, you know, AI is still emerging. And this is really the beginning of leveraging general AI for, you know, solving, solving, challenging or impactful problem. And by, you know, having startups, who are, you know, successful, you found racing and you are able to, you know, send the rights send the the the message to the market, to the innovation, to the ecosystem. That's a, you know, AI innovation can help you to be successful. That message itself is a very important for, you know, the the sustainability or the growth of the AI, you know, innovation market. And and then if you're just to talk about the specific startup who received that last month uh-uh investment. I don't think that's a a good thing in the long term. And many times that you see that those startups may, if they still don't have a product and, you know, there that's, you know, you may not have the right team who can manage a larger enterprise and you may not just have the right incentive to even to, you know, dive deep and then to just get hot dirty to do the building because now you have all the capital available to hire the, you know, engineers and the others, then the founders really just, you know, before you becoming a founder, then you're becoming a large enterprise operator, a manager, and then that is really not the skill set of a typical, you know, entrepreneur at a full startup. Yeah.

Jordan Wilson [00:09:59]:

Yeah. Do you think just, you know, obviously, you've been working and investing in startups for kind of long before this, you know, this generative AI boom, But do you think it's now more difficult? You you know, even for, startup founders that maybe maybe they're pre seed, maybe they haven't raised a lot of money yet. so in my head, part of me thinks, oh, there's all these great user friendly, generative AI tools that you can, you know, code faster. You can get a better business plan, all these other things. But then on the other side, I think it might be hard if they're not integrating AI into their end offering. It might be harder for fundraising. So I guess what advice might you have for a startup founder, and they're just confused. Right? They're saying, oh, should I go all in using an incorporating AI, or should I just stick you know, should I stick on a path that is is not, reliant on that, whether it's for fundraising or for operating?

Double down investment for AI startups


Xiaochen Zhang [00:10:56]:

Yeah. And there's not a strategy which, you know, fit for all, and it's really, you know, you have to look at the nature of your, solution and also the market fitness. And, you know, one, you know, example is that if you're working on a side of the products, which has market fit now and you should just not, you know, trying to, ride with the hype and the changing your strategy, changing your resources because and update the number one challenge for startup is to stay focused and, you know, because your product is still early stage and you can go to many direction. Because you start up, you don't have many resources And because of your startup, that's, you know, you have a lot of noise destruction. So the you know, number one factor to 4 star to fail is that you lost the focus. And if you lost focus and then you will fail, no matter the hype now is the AI or another, you know, emerging technology. If you lose focus and focus around things, send, you know, put your resource into run run, strategy and then your well phone. And of course, that's, you know, for some for other startups who, you know, from beginning build, they try to build an AI startup, and that's natural. That's this is a good time for them and where that's to double down of their investment. And if they, for example, are still a part time startup, founder, and, it could be a good time that to try to accelerate their, you know, prototyping of our product or strategy. So to make sure that's when this is at an early stage and when the, you know, mark market is still hot and especially, you know, it's easy for them to find cofounder. It's easier for them to find the technical resources and also it's easier for them to tap into the bigger ecosystem who want to be part of the the AI cake. And I think that's a good time for them to double down their their investment. Yeah. Yeah.

Jordan Wilson [00:13:20]:

you know, earlier, the name was escaping, my mind. I think it's a misrule AI. That was the, the startup with with the co founders who who worked in big tech So so even when we talk about situations like that, are you seeing too many of these new startups pop up, you know, saying, hey. We're gonna offer all these all these generative AI tools because they're seeing just the the the sheer amounts of of of money and investment coming in. Do you see that as a problem, or do you think that there's still gonna be use cases for, you know, so many different people, companies, enterprise, to be using, these these different tools that these, startups are promising to create? Essentially, is it gonna get oversaturated because of all of the money right now, going into kind of, you know, AI related companies?

Entrepreneurs sensitive to trends, need market fit


Xiaochen Zhang [00:14:15]:

Yeah. And, again, that's, you know, from beginning, we talk about, entrepreneurs are the most sensitive to market trend. and then they are fatties to them. And then they are also the the the most innovative in that sense. When there's a trend, you know, emerging. And then there's markets and message that there is saved naturally that they are going to just responding to that. that happened during the, you know, the dotcom era. That's happened during the, you know, the blocks and and, that's also happened for AI that happened for Metaverse. So anytime when there's a very strong, you know, message from the investor, from the ecosystem that this is a a area where that's, you know, more investment is going to go there and you will see a lot of startup, a lot of innovators who will go in into that. And, I never think that, we have too many innovators. And but, it doesn't mean that all of them will be success Okay. So, you know, there are data data, you know, in the market as common sense. And I can I send off the startup will fail? So, yeah, you wanna be that 1%. You don't wanna be that, you know, 99%. So then If or not, you know, the market will not have a problem in the sense that's, you know, a lot more join, you know, to join this this big trend of, you know, AI innovation, but I think for you, your startup, if you are an entrepreneur or think about it, so and you have to really just answer a few basic questions. Number 1 is that you know, do I solve a a a right problem? Number 2, does this problem have market fitness number 3. And, do do I have, you know, customers who are willing to pay no matter 2b2c2g, there are somebody who want to pay for my service of for my solution. Number 4, do I have a pricing model and which really supporting that customer to leveraging my service. If you have all answers, go for it.

Jordan Wilson [00:16:34]:

Wow. That was that was just a master class there, from from Xiaochin. Just, if you were struggling to keep up with this point there, don't worry we're gonna recap it all in the newsletter that we're gonna send out, after this. But, we we have a great question here. from from Maybridge, in the comments. So as a reminder, if you are listening, make sure to get your get your question in, about how your startup or startups in general can use AI. So maybe it's question here is what are your thoughts on startups that don't have an AI focus yet? We kinda touched on this, but instead, Should they work on a tech product and just focus on the AI element later, or do they not even need to have their eyes on an AI element?

Xiaochen Zhang [00:17:16]:

Yeah. My answer is you're right, and you don't need to. So if if you work out a tech product now and, which means that you already answered that that those 4 questions. There was, problem. There was market fitness. There was a customer. They were, you know, you have a good pricing model and then, you know, no matter is AI matters or another emerging technology, that for you becoming noise. Right? And course that's, you know, when when you continue to improve your product and naturally you may see AI can improve your product. Meaning that's, you know, a lot of time that's a AI can reduce the cost for you to just, you know, launch a product. and I can help you to just, you know, reduce cost and the time of your go to market strategy. and and I can help you also to, potentially create a new type of product solving, adjacent problem to the core problem that you're trying to solve and then that's also have a new market which you can tap into. So those are the additional problems, additional, you know, opportunities. But again, if you are a a startup, have a problem, have a problem, have a product to already ready and only because that there is a high e. AI that's, you know, you started to think about, so, you know, whether I should expand and all that that's becoming distraction rather than, you know, an opportunity.

Jordan Wilson [00:18:50]:

Yeah. Yeah. That's that's such an interesting way to to to reframe the thought. And the conversation around, you know, should my startup use AI or not? and, you you know, you mentioned go to market, which I should, you, you know, put this out there to to to our viewers and our listeners as well. So you also served as the global head of innovation and go to market with Amazon Web Services, right, given given that experience too, you you know, I guess what what are some takeaways from from your time there that you can share, with a with a startup founder right now and maybe they're they're struggling to say, okay. Which direction should should should I take my startup? You know, with with that go to market background, How how would you advise them?

Customer obsession: Listen, invest, improve, communicate, adapt


Xiaochen Zhang [00:19:36]:

Yeah. And the the number one message is really around customer obsession. your customers are smarter than you. And, we're, you know, you you will your customer will guide you and, where to invest, what we invest, and, also, what product they need. And so to try to understand better of your customer and to just bring the right product to them and, also understand that their behavior and also understand, you know, the the the core challenge for them to adopt your products. And I think those are really key. That's, you know, everything what's your, you know, working on, you know, internal off go to market is around your customer. So you need to have a, you know, proposition what value can bring to your customer and communicate that to the value propositions through your market, through your marketing team, and to your customers. And number 3 is, you know, always bring your customer into your, product product design and production implementation roadmap. where that's how have have them to give you feedback in term of whether you have the good feature. Your feature really just, you know, solve their problem. how easy to use. That's it to, you know, require one click, 2 click, multiple click, and, your customer want one click on multiple click, And so whatever your customer need, I want, that's where, you know, you need to just invest more of your time, your resources to improve.

Jordan Wilson [00:21:13]:

Oh, you know, one one thing you mentioned there, which when you said it, I'm I'm jotting myself down notes as well. Right? So you said being obsessed with the customers and and and not just, you know, whether they're spending their money or not, but you you know, you said bringing them in, you know, to the process. It just, you know, it reminded me I've I've used, you know, personally, probably 700 pieces of software. And I remember early on, there's this company called Lemalist, you know, and and I was chatting with their founder. It was 2 AM local time, and he was asking me about the question. And, you know, now they're obviously, you know, unicorn status. But we have another, another great question here from Ben. So Ben is asking, what about startups using AI as a tool? to help them find new market segments, design products, images, videos, developing pitch decks. Right? So, you know, you're chatty PT type products, but then, you know, you also have products that can help, you know, people code better, you know, a copilot, you know, all of those tools. So, yeah, what's what's your take on, Ben's Ben's question here?

Xiaochen Zhang [00:22:19]:

Yeah. That's this question related to the last question you asking, do we have too many? Right? And, so interestingly, for all all the, you know, area that's been asked, there are basically a lot of startups and who are working on the similar problem. And then, you know, there that's, I think, your differentiation strategy becoming very important. You know, if, say, my AI tool can help you to write a social media post. Your AI tool can also do the same. Then now the customer have a choice Right? And why do I use this one? Not that one. And then so similar thing, you know, to for for example, design products and leveraging video and the image to just create a new insights and all that. you're basically half of, you know, tons of twos and are trying to solve the similar problem. So then if you are a customer, you have a choice. Then if you are a startup founder and, you know, you addition to the differentiation, you know, strategy that you have. and the second, you know, piece of that is how to bring that differentiation strategy message to your customer. make sure your customer understand that, you know, for this tool, this is different from the other tools who are trying to solve the same problem you have and then why this is better and then create the right channel and then, you know, to bring that message to your customers. and also again bring bring your customer testimonies and using your customers to educate other customers. And in that way, that's, you know, your customers to finally understand that, you know, even they have more tools in the future, then you still they still have loyalty to yours and then stay with you.

Jordan Wilson [00:24:17]:

Wow. You know, if you're listening and you're in startups, you just got a master class. Wow. I can't I can't thank you enough. you know, I guess I guess before before we wrap up, do you have any last, advice or just last thought on on where AI is is trending in the startup industry, that that people can really just just take and and use and feel more confident in building their startup.

Final takeaways


Xiaochen Zhang [00:24:46]:

Yeah. definitely. Number one thing I think is really is the responsible development and the use of AI. and, you know, and suddenly that's, you know, a lot of, innovators that care about AI and a lot of, large enterprise even, you know, government care about AI, but, you know, AI has is a double sword where that's, you know, you have the the benefit offer improved for productivity, but you may also create a bias. You may create a, you know, the the, you know, impact to gender, inclusion, you create, you know, talent and hallucination, and it may also have a lot of other ethical related issues. and then regulators around the world trying to just, you know, you know, create a new, laws regulations, you know, for negotiation. So if from the beginning that, you know, you didn't pay attention to that piece, then you just think that's it. I can view with a product that I offer to the markets and then no matter how your AM model is to train, what data you use, the and you cannot verify that you didn't do do harm to the society to, you know, the, and then later, you will enter into trouble. No matter is the fines on the litigation and the or your customer will leave you. So those are the things that you need to really fun beginning. And then when you are innovating, trying to innovate in a responsible way, gather yourself informed you know, make sure that's, you know, your the ethical concerns are being addressed and that I think is a very important And the second piece to go back to your customer. I'm trying to really think on behalf of your customer. At this point, yeah, I can do a lot for the customer. and what are the biggest problems that they face and, you know, connect that with your strengths, your resources and, you know, why I'm, you know, at the fastest position to solve that problem. for my customer. That itself is, you know, the number 2 met most important question. The third one is that's a AI cannot solve our problem. and, you have to look into, you know, AI, IoT, metaverse, and blockchain. other emerging technology and also other, you know, already mainstream the technology to combine, you know, or technology together and then by the end of this, you know, technology is not an end goal and it's not end goal. And your problem, the problem customer problem is the end goal. and bring the right technology mix together to solve problem for your customer. I think that will, you know, be essential.

Jordan Wilson [00:27:32]:

Wow. After after each one of these, you you know, responses, I just say, wow, and I'm jotting down notes. So, you know, you shared so much, today that can really help start, you know, startups not just understand AI, but how they can actually innovate and grow with it. So, shot, shotcha, and thank you again so much for joining the everyday AI show. We appreciate it.

Xiaochen Zhang [00:27:54]:

Thank you very much. for holding us, and thank you for everyone. Listen to us.

Jordan Wilson [00:27:59]:

Alright. And just as a reminder, there was a lot in this conversation. Don't worry. We're gonna recap it all. So make sure that you check out the newsletter. If you're not subscribed, go to your everyday ai.com sign up for that daily newsletter. We put it out about 2 or 3 hours after the podcast. So we're gonna be sharing a lot about what you heard today, but also we're gonna be sharing a little bit, hopefully, about the Chicago AI conference that, Shahin's working on as well. you know, we're a Chicago based show. I know we have a lot Coggle listener, so make sure to check that out as well. Alright. So that's it. We hope that you can join us tomorrow. We're gonna be talking about our favorite chat GPT plugin. So hope to see you back tomorrow and every day with everyday AI. Thanks.

Xiaochen Zhang [00:28:41]:

Thank you.

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