How Powerful Women Tackle Tech in Business

Estimated read time: 1:20

Summary

In a spirited discussion led by influential women in tech, the challenges and opportunities of embracing new technologies like AI in business were explored. Key factors such as timing, maturity, and consumer needs were highlighted to ensure technology adds value and fosters trust. The conversation also addressed the importance of diversity and awareness to navigate biases inherent in tech. By sharing personal insights and advice, these leaders emphasized the role of women in steering technological advancements aligned with business goals.

Highlights

Using AI can increase personalization by understanding consumer habits, but it's vital to apply it carefully to maintain trust. 🔍
Technology adoption should be based on the real needs of the business and customers, not just for innovation's sake. 🚀
There’s significant potential for AI to enhance discovery and recommendation services by anticipating consumer preferences. 🔮
Diverse perspectives are crucial in testing and developing AI to avoid biases that can harm users. 🤝
Sharing failures in tech adoption, especially with AI, can help improve industry-wide practices and innovations. 🔄

Key Takeaways

Timing is crucial in tech adoption - too early, and you might jump on hype; too late, and you could miss the bus. 🕰️
Technology should solve real problems, not just be adopted for the sake of innovation. 🛠️
Diverse teams are essential to minimize bias and ensure equitable tech solutions. 🌍
AI in business can greatly enhance personalization, but it must maintain a human touch. 🤖
Women in tech are encouraged to raise their hands and be involved in tech discussions—it’s not just for the CTOs! 🙋‍♀️

Overview

The powerful dialogue between these tech-savvy women unraveled how businesses today must navigate technological waters carefully. With AI evolving rapidly, debate surrounds the timing and processes for adoption amid hype cycles. While some advocate for early adoption to maximize impact, others caution a strategic approach with robust testing and incremental implementation to fit consumer and business needs.

Highlighting real-world applications, the participants shared success stories—like AI-driven customer service improvements that enhanced productivity—and acknowledged setbacks, notably in AI-generated content fraught with bias. These stories emphasize the importance of harnessing technology to truly serve and connect with customers, rather than isolate them.

Furthermore, the discussion steered towards women’s representation in tech, encouraging greater participation beyond traditional roles. The speakers underscored raising awareness about conscious inclusivity and promoting gender equity to foster environments where technologies are developed and employed without default biases. Embracing technology goes hand-in-hand with human oversight to ensure forward-thinking, consumer-conscious innovations.

Chapters

00:00 - 00:30: Introduction The chapter begins with a speaker expressing excitement about being with a group of influential women in business. The focus is on how technological innovation is imperative for businesses, especially those that are consumer-focused. The speaker acknowledges the constant influx of new technologies and the necessity for businesses to adapt or face obsolescence, but also highlights the impracticality of adopting every new technology that emerges.
00:30 - 01:40: Evaluating Technological Advances This chapter discusses the approaches and considerations for evaluating technological advances, especially regarding new services and technologies like AI. Debbie emphasizes the challenge of dealing with the overwhelming pace of technological change, comparing it to a 'water hose' of advancements. She addresses the importance of adopting new technologies to avoid being left behind, reflecting a sentiment shared by many in the industry.
02:10 - 03:30: Customer Service and AI Deployment The chapter discusses Open Table's commitment to serving restaurants by evaluating technology based on its effectiveness in helping manage businesses more productively and efficiently. There is an emphasis on the community role played by restaurants and the need for technology to assist them in having their questions answered more quickly.
04:00 - 05:30: Timing and Maturity of Technologies The chapter discusses the North Stars or key guiding principles that a business uses to evaluate the adoption of new technologies. The focus is on whether the technology assists customer support agents by speeding up manual tasks, thereby allowing them to concentrate better on guests. The evaluation also considers the benefits to restaurants and consumers, exemplified by the use case of OpenTable.
06:00 - 16:30: AI Application in Travel and Dining The chapter explores the integration of AI technology in the travel and dining industry. It highlights how AI processes personal dining behavior and preferences, allowing platforms like OpenTable to customize dining experiences. For instance, the AI can recognize a user's family situation or favorite cuisine, enabling restaurants to tailor their offerings based on this data. The selection of AI implementations focuses on enhancing restaurant operations and customer satisfaction.
18:00 - 21:00: Personalization and Discovery through AI The chapter discusses the impact of AI on personalization and discovery, particularly in online travel companies. Initially, there was an eagerness to integrate new AI technologies into products for customers. However, the adoption rate of these AI-integrated products was not as high as expected. Customers appreciated the offerings but indicated a preference for different solutions, leading to valuable insights and learning about customer needs and preferences. This highlights the importance of understanding customer feedback in the process of implementing AI solutions.
21:30 - 28:00: Addressing Bias and Gender in AI The chapter 'Addressing Bias and Gender in AI' discusses the practical application of AI technology in customer service. The companies must evaluate the effectiveness and value-addition of AI solutions. One example provided is using an AI tool, Geni, to generate summaries for customer service agents, significantly reducing the time required for customer service interactions and enhancing efficiency. The reflection highlights the importance of aligning AI solutions with actual business and customer needs rather than implementing technology for its own sake.

How Powerful Women Tackle Tech in Business Transcription

00:00 - 00:30 I am thrilled to be here with this group of incredible women who are shaping the future of business with the smart decisions they're making about Innovation so as we saw in the video technolog is really forcing businesses to change or risk being left behind and I think that's especially true in the businesses that are very consumer focused that each of you runs but you can't Embrace every new thing that comes along as much as you'd like to so I thought we'd start by discussing ing how
00:30 - 01:00 do you evaluate advances new Services Technologies like AI how do you evaluate them and make decisions about which ones are must doe and which ones you can take a pass on um Debbie let's start with you sure uh that's that's a great question um especially these days it feels like a water hose of technological advancement and that quote we just heard right if uh you don't embrace it you don't adopt it you might be left behind so that's very much the ethos that I think many of us
01:00 - 01:30 on the stage feel we evaluate in a lot of different ways but I think we first View at Open Table we're here to serve restaurants we're here to help them run their businesses more productively more efficiently right and we just heard about the importance of community and think about restaurants roles in all of our communities so when we evaluate things like technology it's like okay well first in foremost does adopting this help them does it get them their questions answered faster right with our
01:30 - 02:00 customer support agents does it help them do menual or manual tasks faster so they can focus on the guest um so I feel like the way we evaluate is what are our North Stars as a business does adopting this piece of technology and this part of our product help our restaurants and then you mentioned the consumer facing side obviously I hope everyone in this room has heard of open table and uses us frequently but it's also what helps consumers right we have wealth of
02:00 - 02:30 information on all of your dining Behavior right and in this day and age of AI we can be processing that information we can making it more personal so when you open up Open Table they know that I'm a mother of two kids who are very rambunctious so you know like we need a corner table or um you know they love pasta for example right like so there's so many exciting things happening and I think the way that we decide what to deploy what to invest in is is it helping our restaurants and is
02:30 - 03:00 it helping our diners I would just add one thing to that so we operate a lot of online travel companies and when this technology you know burst onto the scenes we went running and said we need to build a product for our customers right now and so we did that and then what we noticed was the adoption wasn't high so what our customers were actually telling us was the product that you have is good thanks for offering me this geni tool but I don't like that one as much so that was a really interesting learning for us that we said okay it's
03:00 - 03:30 not tech for the sake of tech right it's what is valuable to your points and so one of the things we learned quickly was that in customer service in customer service of any kind uh the agents have to take summaries of what they're writing and that takes time so we deployed geni to write the summaries for them and it cut the customer service time in I think a fraction so that's just an example of a learning that you really have to look at your business you have to look at your customers who you're serving your partners and to say is this going to add value not because you think that they're want something
03:30 - 04:00 that you should build I want to come back to that point but U yeah I you know I'm I'm a technologist I've been in the tech industry I think for three decades and so I think this is always with technology there's a life cycle there's a early stage where everyone's fascinated you know in in the tech lingo it's called the hype cycle people are like talking about it everyone wants to try it but there's risk at that early stages and then the technology matures and then it becomes really useful I think so your question about how do you
04:00 - 04:30 as a business evaluate I think the timing is the very very important thing in addition to picking which technology is right for your business you have to ask yourself when is the right time um if you're in the kind of a business where applying the technology is beneficial for you and you're okay with taking the risk then you should be an early adopter because the impact is higher if you're not then it's okay to be a fast follower you don't everyone doesn't have to be jump on the bandwagon of a particular emerging technology r away and there are many companies that
04:30 - 05:00 actually fast followers that actually benefit from a business perspective so I think one of the most important factors in judging when a technology should be adopted in inside of your business is the timing for that uh with AI right now I feel it is going through a little bit of a hype cycle uh everyone's talking about it everyone's excited about it the the reason is the rate of change and the rate of progress is so fast and it's such a powerful technology but the flip
05:00 - 05:30 side of it it brings with it a lot of risks right I think broadly though I would say with particularly with a I think your question broadly was about technology but with AI we should distinguish between Ai and gen AI they're very different things um I think one is much more mature and the other is not so much gen uses data to create content create text create videos create music um and so it it does have built into it a lot of biases and so unless the models are tra in uh content that's
05:30 - 06:00 culturally sensitive and literate it builds brings those biases as it creates the content so I think we should be careful about adopting those sorts of things in consumer phasing businesses but also B2B businesses because in at the end of the day there's a customer who's receiving our services right so I think timing and maturity are two critical factors that everyone should take into account okay let's do a quick check here um how many people have booked a restaurant on Open Table show
06:00 - 06:30 up hands warms my heart thank you thank you this is the best moment of my day thank you and plan a trip on booking.com all right and I can guarantee you that probably everyone here in this room shared a story um during breakfast with your neighbor at your table so um I think that's a testament that the decisions you're making are on the right track but I do want to come back to something you mentioned lesie which was this idea and
06:30 - 07:00 and podma about timing right and I found it interesting that you said when you offered the AI based because it's 2025 we have to talk about AI when you offered the AI Based Services which you would think for something like travel which is very data heavy right you could easily kind of help people figure out plug in their likes and get an algorithm that will pump out where they would you know be most comfortable um tell me about why you think you saw that people were sort of reluctant to pick that up and initially I think in general
07:00 - 07:30 consumer adoption you know if something works today you don't necessarily need to change that if the way you shop today works for you you don't have to change that so I think for a lot of Travelers there's a comfort pattern in how they book travel today and I think the opportunities in the future will be immense but to be honest the technology is not there yet so you need to integrate we are not the company that's probably going to build our own llm so we're going to have to work with Partners you have data PR privacy considerations we're a global company
07:30 - 08:00 you have different regulations of this technology all over the world different technology bases so there's a lot that will have to go into it how and where we share our customer data is something we take very seriously so there are so many elements that I think the potential for this to be there is gamechanging um but we're not there yet and I think consumers look at it and say okay that's not there so we have to sort of keep iterating and building on it but I will also say I think we're at an interesting Moment In Time sort of the deep seek moment when we realize that maybe this
08:00 - 08:30 technology can be more accessible than we thought it was in the beginning with just the billion dooll Tech players that that can afford to do this so I think we're going to start to see this layer of entrepreneurs and innovators building applications on top of these big technology platforms and I think that's really going to accelerate the Innovation and make those consumer products better if you think about it for example you know Uber couldn't exist until Apple built the iPhone so I think we're in one of those moments and when that cycle starts to happen I think we'll start to see that inovation make
08:30 - 09:00 the products a lot better okay and that was one of the surprises for for you at booking Debbie in the in when you were embracing and adopting AI um were there surprises negative or positive um that came to light as you were bringing that technology into Open Table yeah and we're very much in that process still but just quickly on Leslie's point the AI alternative has to be better right you have to like on the Travel side you have your way of booking travel you do your research you figure right everyone
09:00 - 09:30 I'm sure in this room has their way of doing it so you have to trust that the AI is going to do it better than you and going to tell you how they're doing it um and right now I don't think we're there yet I think we're going to get there really really soon uh on the Open Table side we've done a lot on customer service for example making our customer service agents much more productive and helping our restaurants um we are about to launch free form search on the consumer side so imagine hey I'm looking
09:30 - 10:00 for a restaurant in Santa Monica that you know is kid-friendly but also has gluten-free options and is by I don't know the ocean right like try doing that search on Open Table right now I guarantee you it's not going to work but it should right like that should exist because we have
10:00 - 10:30 e
10:30 - 11:00 e e
11:00 - 11:30 Lord favor after this
11:30 - 12:00 session thank you so much um so we are in the business of connecting uh great stories with people the with stories that you like so the exact problem you're talking about in the in the restaurant space we do that in the content space right so how do we know
12:00 - 12:30 Padma likes sci-fi but she likes sci-fi with dragons and a happy ending so how do I surface that exact book that exact TV show for you to watch so that's why we use AI um so it's more in the discovery and the connecting you to the community it's not in the content creation at least our company believes we call ourselves a tech company with the soul of an artist um so I I don't believe actually technology should replace human creativity should use we
12:30 - 13:00 should use technology to empower humans to create more and create better and so we we use Ai and we use a lot of AI um to connect you to the right content for the discovery process so how do we not just genre based um searches but really understanding the story is set in Paris and I want to read a romance novel set in Paris set in the 1920s um where there's a very strong female character in the story so you can actually ask those sorts of questions on
13:00 - 13:30 Fable to our AI agent called Scout uh named after Scout Finch from to Killa Mockingbird and Scout answers your questions and so that's sort of where we use it we also use it for you to track we call it utility features so what you've read keeping track of your activities is a very powerful way to use AI right like these are the books I liked why did I like them these are the TV shows I didn't finish watching why did I not finish watching so AI is actually great for that kind of a use
13:30 - 14:00 case you didn't like this TV show because maybe there was too much violence and you that was not what you want it you know I think those sorts of tagging the reasons and uh tracking as we call it your progress of what you've read uh the list you've created sharing those lists discussing it how do I find other people who are sci-fi fans that like Dragon Stories um it's like finding those interests I think this is where AI can really really play a huge role not necessarily to displace humans writing
14:00 - 14:30 those stories that's not what we believe in I believe in uh again we separate geni from ai ai is broadly very useful because it's great at analyzing looking for patterns and serving those patterns whether it's finding your travel or finding your restaurant or finding the great TV show or movie or book that you should um you should read and consume gen AI is difficult I think we did have some negative experiences with Gen I uh
14:30 - 15:00 where jna actually creates content like I said and when it creates content there are biases built into it and we got a lot of push back from our users where we were using jna to create summaries of you as a reader based on the books you've read we would create a summary and say hey Padma it's like this site of a person uh but when we were using gen we stubbed our toe and it actually turned out uh some content that was hurtful to some of our users and I think the thing that to keep in mind is especially when you're a consumer
15:00 - 15:30 business with millions of users even if there's one person hurt by a comment it's it's sort of like the counter right you test it obviously have to test it a lot we did 30 million summaries and one summary had an issue and so mathematically you say that's a very good success rate but the one bad summary was enough to hurt someone and that has a negative effect so if you're a global band you're a smaller company you have to be really careful about that uh I think the way to prevent that is making sure you have diverse teams
15:30 - 16:00 testing these things um people from diverse backgrounds test especially if you're Global as a company so I think a lot of testing a lot of loopbacks is where we use it in the storytelling space uh which I think applies to other businesses as well oh sorry I was just going to say I think that's a great point and I think something Brands really have to think about because people customers come to your brand because they trust you they trust you to deliver on something and that can go away so very quickly that you know when you have the technology excitement you
16:00 - 16:30 have to balance it with what and how you built that relationship I think that's a very important point right and that leads to my next question and we can start with you lesie um about there's been a lot of talk about how Ai and the algorithms that we use even though they're human generated can be a bit impersonal right and and take out that human touch travel is something that's very personal and um you know people have their preferences people travel differently how are you looking at Technologies like AI both gen Ai and Ai
16:30 - 17:00 and making sure that a company like yours retains that human touch I think that's a great point and I think it gets to a little bit of what I was saying earlier we have to be very cautious that we're delivering something that's useful to the customer and then to the point that you just made that we're not delivering something that breaks that trust with the customer right they they know and use our product for a reason and so we have to be very cautious about how we start to apply and we do every everything through a test and learns
17:00 - 17:30 test and learn lens so we do a ton of ab experimentation so if we do have a new product idea we will test it on a very small subset of our customer base look at the reaction and then gauge from there and if it's not successful go back to the drawing board but we have to take that approach very cautiously versus just unleashing something because you risk uh alienating your customers or creating a product that they don't know or trust Debbie same question for you nothing more personal than eating preferences right yes it's it's true we I think of AI or and gen AI as ways
17:30 - 18:00 to increase personalization especially on the consumer Diner front of our site like I said we have a lot of information about your dining habits right we know that when you go out with girlfriends is a different type of meal than if you go out with your kids versus uh your mother-in-law for example um and so we know all of those instances but we're not stitching it together um the way we should so I actually think having AI
18:00 - 18:30 working that and pulling the the themes out right you have themes and dining as well um and then showing you restaurants that we think you could like so for me it's if we're using it properly under the right guidelines it should actually increase personalization because we're looking at your past dining behavior and places that you've rated highly um that you book a lot on to then go and recommend new restaurants that you've never been to um so I I view AI as
18:30 - 19:00 helping the personalization um effort that we're doing on our on our diner side I think there's a really important distinction here um I think I agree with Leslie I think it's really I think focusing on what are you really solving a problem versus just using technology for technology sake I think that's very important I think that filter we have to apply there's a distinction in all our businesses between recommendations and Discovery recommendation is like knowing your behavior I can recommend something
19:00 - 19:30 for you which is where AI is really good at but Discovery is those serendipitous things that happen to us as human beings you're walking along you see something uh in the window of a shop perhaps if there's still shops with Windows maybe they won't exist someday and you walk in because you like that or you're in a bookstore and you're browsing and you pick up something so I think Discovery is something that we feel like AI has the next potential to really surface things for you that you have haven't thought of or you haven't read that
19:30 - 20:00 author before and you know you pick up and because Fable recommends it you pick that up I think that's the next level of personalization we call it hyper personalization really understanding not just your past behaviors but anticipating things that you are going to like um and I think that's where there's a lot of potential and it's a new area I think in consumer business that's going to be groundbreaking uh to really figure out this hyper personalization which someday people believe actually it'll replace search you won't be searching randomly anymore
20:00 - 20:30 because technology really understands you but you have to balance that with privacy how much data you Expos to get to that hyper personalization that's the balance you have to strike um at Fable we work really hard to connect you with people who have similar tastes as you do to discuss books that I read this great book right now I want to talk about it you know it's it's called all the colors of the dark and and so I have a group of people I have a community on Fable that
20:30 - 21:00 is also reading that book that wants to talk about that it's sort of like that discovery of finding people who like similar things as you and then when they suggest something it's a real human making that recommendation but I wouldn't have found that human without technology connecting me so I think that's the balance we have to strike not necessarily to break human connections but using technology to make real human connections with real people that like similar things that offer a different perspective for you to gather from things that You'
21:00 - 21:30 you've read right because literature and stories are very subjective food is too and you know places you visit are too how I might react to a certain kind of food is different from how Debbie might react so I think how do we really get quantifiable information from these subjective experiences this is I think the challenging part with AI but also the exciting potential we have and I think um two areas that we can look at you know there's still lack of equity when it comes to leadership roles for
21:30 - 22:00 women in the tech industry um bias is also another issue that all of you have brought up so just really quick down the line would like to ask each of you either lessons you've learned you know in in terms of the the role that you're playing now uh in making sure that you know any application of AI or gen AI um is addressing the potential for inequity and bias um or solutions that you would like to see let's start with you lesie I would say maybe I'd frame it as a piece
22:00 - 22:30 of advice from my own experience which is do not leave this is gamechanging technology the way you know the internet change things it touches everybody this technology will touch everybody so my advice would be don't leave this to your CTO make sure in my own Department we have every Department across our business is required to have objectives related to technology so I think that's one way we are already facing a gap in terms of women representation in in technology but this this is now an opportunity for every woman no matter
22:30 - 23:00 where you work in your organization to actually be at the the Forefront of Technology Debbie I love that don't leave it to your CTO that's so good um I was recently in a meeting or on a call with other CEOs I was the only woman um and the discussion was like well what what we what should each of us be doing in our business with AI and make sure we catch the wave and we're doing all the right things and um group consensus was well we need someone in
23:00 - 23:30 Silicon Valley who's connected and who knows what's going on um you know so maybe that guy or maybe this dude and I'm sitting there and I'm on a humble brag okay so like I live in I live in the Bay Area I went to Stanford I went to MIT open table is involved in almost every single AI launch like Sam Alman was playing around with operator using open table and no one in the room
23:30 - 24:00 thought to consider me now that's on me I also didn't raise my hand right but my point is like make sure that like you're packaging and marketing yourself like that could be me now like that's not necessarily like I'm not saying like I want to be that person that helps all these CEOs figure out gen aai but I at least want to be considered and I feel like my qualifications are credentials at least should get me to be considered
24:00 - 24:30 right but it would it did not and these are men who respect me who like me who think I do a good job but I'm not even in the the thought of perhaps this woman could help us with AI based on her location and her educational background and the type of company she runs right but it's and it's not on them like I I actually view that that's on me right like I'm not raising my hand I'm not put positioning myself as a technologist because like yeah I went to Stanford and
24:30 - 25:00 MIT but I was like a political science and business major so I'm not you know like hardcore like you but I at least know enough and am connected enough to be able to like move the needle but no one thought of me that way and it wasn't even until that call where I was like wow like I didn't even think of myself that way and I should so that's not on the men that's on me so like just think about that like I was like this happened two weeks ago I was like wow like I got some like packaging marketing work to do
25:00 - 25:30 on myself right to make people think of me and not just like oh I'm I'm a good girl that runs Open Table a lot of good girl you do run over you're more than that deie you're more than that that's awesome yeah you should you should raise your hand next time I'm going to call and check on you I'm going to ask you did you raise your hand um yeah I mean I I'm a hardcore techie I live in silen
25:30 - 26:00 Valley I've been in tech companies all my life you know technology is something we create as humans and so it's going to carry all the biases we have inherently there's a lot of racial bias there's a lot of gender bias uh as clean as models tend to be there is a lot of bias in inside the models because the data is biased it's only the output is only as good as the input right and the input is contaminated so the output will be contaminated it's really as simple as that it's not complicated um it's actually not technology it's
26:00 - 26:30 it's like Common Sense uh I think as Leaders as women leaders it's our responsibility at this stage maybe at every stage in the evolution of Technology there is a human in the loop uh to test these things and test the output to make sure it's not spitting out uh bias inside the solutions that it's coming up with especially with Gen I think there is that risk um and I think it's on us to make sure we're challenging ourselves and our teams to make sure there is a diverse team like I
26:30 - 27:00 said looking at this um I think human in the loop probably is a smart idea for businesses to have in other words if you're using AI for customer support or customer service make sure there is a real human being checking those for for now at least um and then have a diverse team developing those Solutions um I think that's really important I think to advise businesses on how to use AI it's very complicated because each business is very different uh I think if you have expertise in in a particular kind of
27:00 - 27:30 business it's on us to make sure our businesses are not reflecting um those biases in the output Solutions and if we are clean about it and I think we can then speak to it one of the things we're a small company we made a mistake with Gen and actually I went on Bloomberg and talked about the mistake we made so that we could help help other entrepreneurs not make those same mistakes I think that's the other thing we should also share um our failures with this technology that's where the technology gets better that's how it gets better I
27:30 - 28:00 think I actually feel you women uniquely are better positioned for that cuz we're good at identifying things that break faster and and fixing that and you know maybe I'm biased in saying that but that is a true statement and so I think we're uniquely qualified to do that okay well I could keep going but um lesie Debbie podo thank you very much for sharing your insights and it's clear we have a lot to look forward to