Ep 273: Microsoft PM Speaks – How AI is Shaping Product Management

The Impact of AI in Product Management

One of the most influential advancements in technology, Artificial Intelligence (AI), is dramatically shaping the future of product management. It streamlines communication and influence, offering significant benefits in crafting emails, recording and transcribing meetings, and identifying actionable items.

AI is a boon for individuals spending hours reading, analyzing, and crafting emails. Enhanced AI technology aids in writing emails and influencing large groups with minimal emotional and cognitive burden. It not only switches the paradigm of understanding and translating emails, but it also imparts an impact on the regular patterns of note-taking and processing thoughts during meetings.

AI and Meeting Management

AI’s applications spread way beyond virtual assistants and data processing - the technology is making significant strides in meeting management. By recognizing speakers, identifying action items, and providing a structured summary of discussions, AI is becoming an integral part of effective meeting administration. Its proficiency at producing notes from meetings makes it a valuable asset, especially when a meeting cannot be attended.

The Art of Crafting Emails Via AI

AI takes the tumultuous task of email communications and transforms it into an easy, user-friendly experience. By simplifying prompts like "make this better", AI boosts the efficiency of crafting influential emails. The technology removes the time-intensive process of wording an email perfectly, freeing up professionals to focus more on the content matter.

AI’s Role In Improving Customer Feedback

Interpreting customer feedback can be a challenging task, given the variety of views and experiences that customers bring to the table. However, AI can analyze feedback, identify common themes and patterns, creating a roadmap of actionable insights. AI can help build future product direction by synthesizing customer feedback and identifying emerging trends.

The Future of AI and Product Management

Just as the internet revolutionized communications, AI seems set to transform product management and customer feedback processing. It is notable, however, that AI tools are often formula-driven and may not completely replace the human touch of communication and influence skills needed in product management.

Nevertheless, the democratization of AI tools presents a significant step, offering equal opportunities for a wider audience to access and use AI technologies. As AI development continues at a rapid phase, embracing this technology becomes pivotal in staying at pace with the competition.

Embrace AI, Rethink Product Management

Offering a chance to save considerable time in daily communication tasks, there is no doubting the power and potential incorporated in AI. Whether it's Microsoft Copilot, Gemini from Google or meta AI, the truth of the matter is simple — embracing AI stands as a proven step in unlocking new thresholds in productivity and efficiency. Just like the transition to the internet usage in the early days brought about significant change, successfully integrating AI is the game-changer product management needs today.

Indeed, AI is becoming an integral part of everyone's job, especially those who rely heavily on computers. Irrespective of the job role, starting small and playful experiments with AI can stimulate comfort and familiarity with the technology. As AI continues to grow, so does its place in product management, driving decision-making to new heights. The challenge lies in adoption, geering preparedness and capacity building to leverage the potential of AI fully.

Topics Covered in This Episode

1. Role of AI in Product Management
2. Use of AI in Communication and Influence
3. AI and Customer Feedback in Product Management
4. Future of Product Management

Podcast Transcript

Jordan Wilson [00:00:16]:
There's AI in just about all of the products that we use now. Right? It seems like it. Everywhere you turn, whether it's, you know, your your CRM or your, marketing platform. It's there's AI everywhere. Right? But how is AI actually shaping those products, right, in in the future of product management? So we're gonna be talking about that today and more on everyday AI. What's going on y'all? My name is Jordan Wilson. I'm the host, and everyday AI, it's your guide. It's your guide for learning and leveraging general in, artificial intelligence, to to or sorry.

Jordan Wilson [00:00:52]:
Generative AI to grow your company and to grow your career. That's right, guys. We're live. Sometimes we mess up, but that's okay. So, if you're listening on the podcast, thanks. As always, make sure to check out your show notes, for more, and make sure, as always, to go to your everyday ai.com. Each and every day, we recap our conversation for the day when we normally talk to an expert like we do today. So make sure you check out that recap because there's gonna be, not just more insights from today's conversation, but also what's important going on in the world of AI news, which let's talk about that right now, the most important AI news.

Jordan Wilson [00:01:27]:
So first, Google has announced a slew of new updates at its IO developer conference. So they unveiled project Astra, an impressive new AI agent powered by Gemini. Google announced also enhancements to its Gemini models, including, Gemini 1.5 pro and Flash. The Ask Photos, powered by Gemini also was, was revealed for Google Photos. Google also demonstrated Google AI teammate, a virtual teammate for work tasks. There's actually so many, bullet points here, but two things I wanted to bring up here was, 1, new features for Google search were introduced leveraging generative AI for organized search results called AI overviews, which news publishers aren't very thrilled about. And then also Project Astra was probably the show stopper as it seemed to compete directly with kind of that live agent mode that we saw that OpenAI demoed the day before at its spring event. And while OpenAI has said that they'll start rolling out their kind of live agent mode in the coming weeks, Google has not yet given a release date yet for Project Astra.

Jordan Wilson [00:02:33]:
Alright. Speaking of OpenAI, an OpenAI cofounder has left the company after months of speculation. So Ilya Sutzkever, the cofounder of OpenAI announced that he is leaving the company. So Sutskever is the cofounder and chief scientist of OpenAI, and he announced his departure from the company on Twitter amidst leadership turmoil and internal conflict. That leadership turmoil stems back to November when CEO Sam Altman was fired, then rehired, and, obviously, the board shakeup that followed. So this also follows a series of other recognitions, resignations within OpenAI and raises questions about the company's future direction and commitment to AI safety and ethics. Also, Janilecki, who was the co leading the OpenAI superalignment team, also just said a couple hours ago that he resigned in a Twitter post. So a lot of, shakeups there at OpenAI.

Jordan Wilson [00:03:28]:
Alright. Last but not least in the AI news, US senators have proposed a budget for AI, but no regulation. So a bipartisan group of US senators released a legislative plan for artificial intelligence calling for increased funding for research and development while offering few details on regulating its its risks. So the plan calls for $32,000,000,000 in funding annually by 2026 for government and private sector research and development of AI. The senators also recommended creating a federal data privacy law in supporting legislation to prevent the use of deep fakes in election campaigns. The decision to delay AI regulation widens the gap between the US and other countries or regions such as the EU, which has adopted a law that prohibits risky uses of AI. So no real surprise there if you listen at the to the Everyday AI Show at all. I've said for, like, a year that we're not gonna see any meaningful, you know, AI legislation at least here in the US, but, it does look like, senators are preparing to propose federal funding for that.

Jordan Wilson [00:04:32]:
So, there's always more happening in the world of AI. So make sure you go to your everydayai.com and check out that daily newsletter. Alright. But you probably didn't tune in to listen to me mumble and stumble through the AI news. Maybe you did. But we're here to talk about the future of product management and how AI is actually shaping that. So I'm excited today to bring on our guest. There we go.

Jordan Wilson [00:04:57]:
We have her. Kimberly Williams is a senior product manager at Microsoft. Kimberly, thank you so much for joining the Everyday AI Show.

Kimberly Williams [00:05:05]:
Thanks, Jordan. It's really great to be here. I'm excited for the discussion today. All right.

Jordan Wilson [00:05:09]:
And hey, I always have to give a special shout out to people on the West West Coast who join us at, you know, 5:5 am their time. So Kimberly, really appreciate you making time for this. But can you tell us a little bit about what your role is there at Microsoft?

Kimberly Williams [00:05:24]:
Absolutely. I'm a senior product manager at Microsoft. I've worked on several different products within our what we call our Power Platform suite, mostly focused on developing no code, low code, app development platforms, automation, most recently integrating Copilot, generative AI into our business insights, Power BI product, and now working on a data unification platform, which is our fabric platform. One of the things that gets me really excited about these technologies is democratizing these technologies, making them available to customers who are not only pro users, so pro devs, who maybe don't need the low code, no code, but it helps them do their job faster. But then people like me who, you know, I'm not a developer, but I wanna be able to to to develop my own apps or automations. And, of course, now bringing in generative AI and making that available to to everyone. So I I'm really proud of the democratization just improving productivity from a business perspective, but also enabling some of that creativity for our users as well.

Jordan Wilson [00:06:48]:
Yeah. Love love to see it. And, you know, this is just a a reminder to our live audience here. Thanks for everyone for joining in. So, you know, Cecilia joining us from Chicago, Rolando from South Florida, Tara from Nashville, Juan from Chicago. Thank you all for joining, but now's a great time to have a senior product manager at Microsoft to get your questions in. So know, I'm gonna start at the end here, though, Kimberly. Right? So even the topic of of today's episode is about the future of of kind of AI in in product management.

Jordan Wilson [00:07:19]:
So, you know, you are obviously someone that's working at a company that's creating, you know, AI that, you know, probably 100 of millions or maybe even billions of people are already using, in in Copilot. So, you know, I'm curious. How are you already seeing, the future of kind of this intersection of AI and product management? And how do you think when we do look at the future, how is AI ultimately going to, shift or change product management?

Kimberly Williams [00:07:48]:
Yeah. Thank you for for the question. I think there's there's a lot of opportunity now, for using AI within the product manager role. And I'll and I'll kinda start by thinking about, you know, breaking down what what is the product manager role. A lot of our role is communication. And and I'll actually take this a little higher. We'll we'll talk about the PM role. Right? Because if you're in the space, PM can mean a lot of things.

Kimberly Williams [00:08:14]:
You can be a product manager, program manager, project manager. And there are nuances between, but there are a couple of of foundational things that go across all of them, which are communication and influence. And, yes, we do set up a lot of meetings or we have a lot of meetings. So I will give a little nod to that. Yes. I know. But one of the things that AI can really help with in in those spaces with communication, you know, we send you know, when we send emails, we're often having to communicate priorities. We're often having to organize large groups of people to move toward a common, toward a common goal.

Kimberly Williams [00:08:54]:
And there's a way that we have there's a way we need to communicate to drive that influence, to to manage without you know, to manage through influence. And, you know, sometimes it can be it can take a lot of time to craft those communications, to craft those emails. And this is an area where AI can, really help you in specifically gen AI, like Copilot, or if you're using Gemini or or other chat GPT type, Gen AIs, that can help you write those emails instantly. And even if it's not perfect in the way you want to send it, it hits that baseline, that template for you. Then now you only have to spend a little time tweaking rather than having to come up with the original context that sometimes we can agonize over for way longer than is really necessary.

Jordan Wilson [00:09:47]:
Yeah. And and even on that, you know, it sounds like such a low hanging fruit. Right? But, you know, so so many people time spend hours a day both reading and analyzing and rereading and reanalyzing and recrafting their emails. So I'm wondering, Kimberly, even from from your personal experience. Right? Like, obviously, you know, Microsoft has 100 of thousands of employees. I'm sure there's a lot of internal communications. So I you know, I'm curious. How has AI even helped you personally in your own, you know, communication and and influence as well.

Jordan Wilson [00:10:22]:
Right? Because you kinda connected those two things.

Kimberly Williams [00:10:24]:
Yeah. And and I'll actually pivot to one of the 3rd points, which is around meetings. So one of the things that has been really, really helpful about about AI is at least for for the meetings that we have internally at Microsoft using Teams as our as our meetings, product, it will be record. We often try to record our meetings because when we record the meetings, we get transcripts. We get notes. The AI will acknowledge it'll recognize and acknowledge who is speaking throughout the meeting. It will recognize, action items that are discussed in the meeting, and it will so in your after meeting notes, it'll actually outline a summary of what was discussed, tell you the action items, who the action items are assigned to. And so for me, that in the event that well, there's 2 ways to to leverage that.

Kimberly Williams [00:11:21]:
1 is when you can't attend a meeting you get very valuable insights into exactly what happened and the most important part is what were the action items? Right? I mean, if you don't have an action item that comes out of a meeting, was the meeting really necessary? Right? Is that a meeting that should have been an email? So, so having the AI that can can save the time that maybe you don't even need to attend the meeting, And then for for folks or times when you do attend the meeting, it drafts your notes for you So you don't have to, during the meeting, take your notes. The the AI is listening for you, and so you basically can copy paste those, throw them in an email, send it out to your audience. So I think, the meeting AI is probably the most and it's available to everyone. You you hardly have to, you know, as long as somebody hits the record button, everyone has access to the content, which is really great. So it takes the burden off of each individual person, whereas other uses of Copilot, you know, it's it's on each person to go and use it.

Jordan Wilson [00:13:14]:
You know, you bring up such a great point and, you know, I I I don't quite have that for live like, a live stream like this. Right? Because I'm I'm over here. I'm typing notes. I'm like, oh, Kimberly see that.

Jordan Wilson [00:13:42]:
That's a great point. People need to really, you know, focus on that. But even in in meetings, even for me personally, right, when when I'm using an AI assistant, I find myself thinking differently. Right? Whereas before, kinda like what you said, Kimberly, I'm always typing up, oh, yeah. Gotta follow-up on that. Gotta do that. But when I have an AI assistant, I can actually think in a way that I haven't been able to to to think previously in meetings. So, you know, for you personally, you know, because you're I'm I'm sure using Copilot just about in every aspect of your day, How has this freed up, you know, just just your kind of, like, your brain and and your abilities to think about maybe other things, more creative things, more strategic.

Jordan Wilson [00:14:20]:
So walk us through how, you know, having this, you know, copilot on a day to day basis, how has this changed, kind of what you can accomplish in your role?

Kimberly Williams [00:14:29]:
Yeah. I I think some of the ways that I've used it directly are certainly to help expedite writing emails, emails that, again, where I have to influence a large group of people, moving them toward a common goal. This is, again, one of those scenarios where you could spend an hour, maybe even more, agonizing over the language, making sure you've said the right thing in the right order, being concise because that's an area I'm not always so good at. I like to talk. I like to talk in real life. I like to type a lot in real life. So AI helps me also be concise. And it can be simple too.

Kimberly Williams [00:15:05]:
Like, a lot of a lot of my interactions with Copilot, is very much a chat GPT type interaction. So, you know, they're short short prompts. And a lot of times, what I'll do is I'll even type out something basic, whether it's to be an instruction or an example, but I'll say, Make this better. That probably is my most used prompt is make this better. Now in those, you know, in those cases, I did start off with some kind of template, or maybe I've used a template that I've gotten from from Copilot previously, and I'm just adapting it for the certain situation. But definitely drafting those emails, it takes a lot of that, I'll say, emotional burden. And I and it probably sounds overly dramatic, but that is the burden that it has is, mental, you know, cognitive, emotional burden when you're when you're trying to organize these, these mails. Because, again, they're also going to a large audience.

Kimberly Williams [00:16:05]:
They're going to your executive leadership. You want it to be right. You want it to be good. It's your is crazy as it sounds sometimes. It's your reputation in that email. And again, I'm probably sounding very overdramatic, but those are the things that kinda come with that that AI helps reduce the burden of.

Jordan Wilson [00:16:23]:
You know what, Kimberly? I don't think you're being dramatic because I I also think that there's, you know, 2 very different types of people when it comes to email. There's people like me that don't really think about it. Right? And I probably have thousands of unread emails, and then there's those people that think a lot about their emails and they, you know, always read and respond instantly. And they put a lot of, you know, thought and effort into making sure that that unspoken communication speaks pretty loudly. And I love what you said there. Just something as simple as 3 words, like make this better. You know, you don't have to overcomplicate, you know, when you're prompting inside Copilot or these other systems. So, you know, I'm wondering what's the one biggest.

Jordan Wilson [00:17:00]:
Right? Because you you you have access to, you know, Copilot, and I'm sure you've been using it for much longer than the general public. But what is the one, biggest or best use case for you personally that's helped you in your role in product management that you look back at it and say, wow. Without me using AI in this way, I don't know if I would have been able to accomplish what I have.

Kimberly Williams [00:17:20]:
Yeah. I think one of the things we haven't talked about yet, and it is really important in product management, is customers. That's another area that is very unique to the product manager role is we talk to customers. And often, we are talking with customers, to understand how they feel about a product. We could either be solving a solution for them, or we could be getting feedback from them on new features or how to solve a challenge that they have that in a way that they wanna use a product or think about now that AI is here. You know, customers are they have questions. Right? They wanna they they we we wanna we have an opportunity to dispel myths about AI. We have the opportunity to, understand from customers what they're excited about in AI that helps us know what we can build that will help our customers.

Kimberly Williams [00:18:15]:
And so to that point, when we get feedback from customers, it is, it's variable. You could have 10 customers all telling you generally the same thing, but the way they say it, that open text format, makes it harder to, to kinda pull those common themes together. And this is a this is a space that AI has been really helpful, especially when we're not just talking about 10 customers. We're talking about 100 of customers, thousands of customers, maybe millions of customers. And having all of that feedback in these variable text formats, you can you can use Copilot we have used Copilot, to say, you know, what are the leading themes here? You know? And this takes the burden off of reading 100 unique translations of what the customer thinks and feels about a product or an experience. So AI can help find those patterns. And what's great is not only that it can do that faster for you, but sometimes AI could even find things that you wouldn't find yourself because when we do put ourselves in that cognitive load, sometimes we also we see what we wanna see. That is one thing that, I'll say AI I'll say something that I'm sure people are gonna argue with me a little bit.

Kimberly Williams [00:19:42]:
There are some ways that AI can be unbiased, you know, but that's a little different than, the other kind of bias that we often talk about. But when we're talking about interpreting what's being said by customers, when we read the the context of customers, a lot of times we might read what we wanna read. Right? We wanna read that they love our products. We wanna read that they want the feature that we wanna build, but AI will look at it from a different lens. Right? The AI doesn't really care what you build. It's, you know, it's looking unbiased at that at that feedback. So that's been, I think, the greatest opportunity in product management is is helping us get to those insights, not only faster, but then seeing it in a way we wouldn't have seen without that assistance.

Jordan Wilson [00:20:29]:
That's that's such a great point, Kimberly, because, yeah, I'm I'm not a product manager, but I can assume that there's always a pretty heavy bias, right? When you're looking at customer feedback and like, ah, you know, maybe they're upset about this, but you know, then maybe they just don't understand. Right?

Kimberly Williams [00:20:44]:
So, you

Jordan Wilson [00:20:44]:
know, that's that's a that's a really good point.

Kimberly Williams [00:20:46]:
They just don't understand.

Jordan Wilson [00:20:48]:
Yeah. Yeah. Yeah. Kind of, you know, taking away those those rose colored glasses and, you know, helping you maybe better understand, you know, humans, which is interesting, you know, that AI can help in that way. You know, what about when, you know, when you think of, you know, product strategy and, you know, product road maps because I'm sure that's a big part of what you do in product management. You know? So it it makes sense how, you know, AI and and large language models can help make sense of, you know, human feedback and unstructured data, right, when we talk about that aspect of it. But what about when it comes to strategizing or building the future of of of products, right, whether we're talking Microsoft or elsewhere, how do you think that AI can help in that regard?

Kimberly Williams [00:21:30]:
Yeah. I I think the again, this kinda comes back to well, I'll start by when we when we build out a road map, often, we're looking at, there's multiple things that kinda come into, into that plan. One is we're trying to understand, what direction we wanna take our existing products. And that direction can either come through our customer feedback. It can also come from what we understand about the emerging landscape. Right? Like, a year ago, nobody was asking for AI or generative AI. We jumped on that. We saw the opportunity.

Kimberly Williams [00:22:08]:
Of course, we have that partnership with OpenAI. And now, you know, more than a year in development, you know, our customer like, every customer is chomping at the bit to have access to to Copilot. So we're taking our feedback from our customers, what we understand about the emerging landscape and the opportunity, and then pulling those 2 together. And I think where AI can really help us with that strategy is, again, as we collect customer feedback, understanding the themes that are coming through, because, again, we don't wanna build you know, of course, we do wanna build what's cool and what's exciting, but we also wanna build what customers need and what they want. I mean, they're not, you know, you know, that's that's what we're in the business to do, is to help our customers. And so I think, you know, that's where AI can help us. And, you know, before we had AI, there was a lot more, I think, manual effort in understanding what is happening on the emerging landscape. And this now is an area not to say we wouldn't still do some of that manual load.

Kimberly Williams [00:23:18]:
Like, I love reading about emerging trends and emerging technologies, and I'm involved in a lot of forums. But I do think there's an opportunity where AI can help with that too, where AI not only can help you review like, when I think of all the places I get data and information from, I have to go and I have to read every newsletter. I have to go to every forum. You know, on a certain cadence, AI can provide that summary. Right? I can go to all those places almost instantaneously and provide a summary. So it can help me understand, that landscape and maybe even more so because AI now can also reach beyond, you know, the 10 forums I follow. It can reach out to a 1,000 forums. And so those are the things that can help us build our strategy or understand the opportunities and then talk to customers about it.

Kimberly Williams [00:24:13]:
I mean, there are times where we have very close customers that we work with under NDA where we might throw an idea on the table, be like, hey. What do you think about this? You know, if we've worked on something like that, would that be helpful for you? Would would that be something you'd be interested in? And then that can help us guide, you know, what might be the next really cool thing.

Jordan Wilson [00:24:32]:
Yeah. And, you know, speaking of that, you know, Kimberly, the next cool thing, and you talked about emerging trends in technologies and in AI, you know, obviously working at Microsoft, right? Like, I think you all are in a very unique position, you know, you just kind of, you know, the Microsoft MAI 1, and then, you know, I know that Microsoft is already, you know, implementing the new GPT 4 0. Right? So you have all of this very powerful technology, you know, not just from Microsoft, but other companies as well. You know, it's been a very busy week in AI. So I I think people always naturally start to see the progression of of these models and new capabilities, and they start to think, how is this gonna impact my industry, you know, in the long run. Right? There's obviously all of these positive insights that that you just, you know, talked about. But then there's the, okay, what if the AI gets too good? What if the next model from from OpenAI or Microsoft is way better than me at everything? So, you know, when you talk about that and, you know, like, even like, okay, could AI replace the role of a product manager? Like, what are your thoughts on that?

Kimberly Williams [00:26:39]:
Well, Jordan, I I have, a bit of a controversial view on that. So we'll, we'll throw this out there. So it's my opinion that PMs will not well, product managers will not be replaced by AI in the near future. The, the controversial piece of that is, I would say, software developers have a greater chance of being replaced before PMs. And I'll just let that sit there for half a second. I'll wait for people to come yell at me. And here's why. When we think about what AI is most capable of doing, it's most capable of following a formula.

Kimberly Williams [00:27:23]:
It's most capable of you know, it's being trained and it's forming these these definitions. And when we think about what you know, we talked about product management being about communication, being about influence. Those are very nuanced. It's not just a formula. There's nuance between how you communicate in different audiences, how you influence in different audiences, how you talk to customers. When we think of software development, not only do folks get degrees in computer science, they have degrees in mathematics. It's very formula driven. It's very defined.

Kimberly Williams [00:28:01]:
I'm not saying there can't be some creativity involved in there also, but it's defined. And in fact, when we think about some of the earliest copilots that were available, one of the first copilots was GitHub Copilot. GitHub is our software development, open source platform. So I think, you know, for the PMs that are worried about, AI replacing our jobs, not so fast.

Jordan Wilson [00:28:30]:
Oh, love it. Love it. Saving saving the hot takes for the end of the episode. I like it really. And, you know, I don't I don't think that that that you're alone in that thought, you know, even, you know, NVIDIA's CEO Jensen Huang said said something similar. Right? And and emphasized the actually, the importance of what you're saying, you know, communication, soft skills, being able to, you know, talk nicely to a model to prompt it to get better results, right, and have a conversation, with AIs, which I think is incredibly important. A couple couple questions. I'm not sure if we'll have time to get to all of them, but I I like this one here from Cecilia.

Jordan Wilson [00:29:07]:
So, Cecilia, thanks for the question. So she's asking, what is the best result you have seen from the democratization AI has brought, and what has AI missed in democratizing what you do? Cecilia, with the tough questions right after your hot take, Kimberly. So what are your thoughts there?

Kimberly Williams [00:29:24]:
Let me think about that. The best result you've seen for the democratization and AI has brought, what has AI missed in democratizing? I think one of the things that I think is really great about let's start with the first part, democratizing AI. This is one of the things that I think has been amazing when when OpenAI released chat gpt. This is, like, November 2022. So we're just over a year, year and a half. But it was available to anyone and everyone who had access to their Internet website. And it was free. And I think there's so many times when new technologies or new developments aren't available to everyone.

Kimberly Williams [00:30:11]:
And they're not available in a way that people know how to use them. Chat GPT, again, I'll say something maybe a little bit controversial. When we think of Chat GPT from sort of a foundational level, it's basically like a super hyper Google Google search. Right? I mean, that's initially how a lot people use it, is they went into GPT, they typed in something that you could have easily typed into Google search, and then you get a result. Now your result that you get is a little different. Right? You might get a more summarized result. So, like, the output looks different, but the point was it gave everyone the opportunity to get on this AI wave without leaving so many people behind. So the opportunity is there, whether or not people, you know, got on board.

Kimberly Williams [00:31:00]:
What has democratization, what has AI missed in democratizing what I do? I think I don't know if I would categorize it so much as what's been missed, but I think the one of the challenges is AI is moving so fast. Right? And that's the thing with democratization. You have some people, like myself who are very interested probably everyone here in this forum. Right? We're all very interested in in new technologies. We're very interested in AI. We are jumping on the bandwagon. There are other people who are and it's moving so fast. So we're getting so what started out as being an equal opportunity, we're already kinda seeing this divergence of the people who are jumping on and learning and getting way ahead.

Kimberly Williams [00:31:57]:
I mean, look how fast these models are developing, and new versions are coming out. And those of us who are already in it, we're already, like, learning all the new stuff. And there's still there's still a a large group of people that are, you know, they're still somewhat suspicious of AI. You know, the Terminator movie isn't helping us very much right now. A lot of people see those worst case scenarios rather than the the opportunistic scenarios. So Yeah. I I see that right now as kind of being the opportunity.

Jordan Wilson [00:32:29]:
Yeah. And you bring up a great point. That's something I think I talked about on the show earlier this week is, you know, it seems like, I don't know, even especially, like, the last week with, you know, big announcements from from Google, from OpenAI. You know, it's it's almost like the divide that can exist between those that do use AI and do not use AI now is even greater. Right? So with all of these new and exciting possibilities, I think also that divide between, you know, the uses and the do not use just grows exponentially, which, you know, it's it's kind of crazy to think about. But maybe we'll we'll we'll we'll go with something much easier here, but I I love this very, practical, question here from Douglas. So, Douglas, thanks for, your question and tuning in as always. So asking what are the top publicly available tools that you use for PM work, and what productivity increase might you estimate that these tools have allowed such as an x percent increase in whatever, productivity, savings, etcetera.

Jordan Wilson [00:33:26]:
So what are those top tools and what kind of productivity increases, Kimberly, might might people see?

Kimberly Williams [00:33:32]:
Yeah. Well, top tools, I would say Microsoft Copilot. Publicly available if you are accessing it through, Bing search. At one point, it was called Bing chat. And now when you go to Bing, you'll see it named as Copilot. I do also use Gemini from from Google. I'm now starting to experiment with meta AI. And sometimes, I'll go to to actual OpenAI and use Chat gpt.

Kimberly Williams [00:34:01]:
But, but those, a lot of times I use admittedly, I often use AI outside of our Microsoft products. You know, right now, Microsoft products we're trying to bring Copilot in almost everything, right, into Power BI, Excel, PowerPoint, everything, you name it, Teams. And I have used AI in all those. But when I think about my regular daily usage, I'm often just using a chat GPT function, essentially. And I would say productivity increase, I would rather than thinking about it as a percent increase, I would really think about it more in terms of time saved. I mean, you could still do the calculation, but, I would definitely say a a couple of hours. I would say 1 to 2 hours a day, just being able to very rapidly generate communications, being able to leverage the the meetings AI. So whether it's, leveraging those notes, actioning on the action items that were identified in the notes.

Kimberly Williams [00:35:12]:
But I think it's, it's important to and maybe I'll just I'll kind of build on this question to to another point that I'd like to to share broadly with the audience, which is, you know, the hype while the hype of AI might sizzle, AI itself will not go away. AI is going to be part of everyone's job. Well, let's say, everyone whose job is on a computer, AI is going to be part of your job at some point in time, whether your employer is going to expect you to use AI within your role, within the org, or you're using it outside of your job function just to help you do it better. And I think there's there's an opportunity there to to start with something small. Like, even if you're not being asked to use AI within your company, within your organization, do something that's fun. Like I think some of the first AI, other than playing with chat gbt, is, I played with DALL E, creating pictures. Midjourney is one of my favorites. So I've spent some time on Midjourney, just doing fun stuff that really didn't have anything to do with anything.

Kimberly Williams [00:36:25]:
But one of the things that also helped me understand was, effective prompting. Because I do think, like, when we talk about your percent, improvement of productivity, AI is very generative AI is very easy to use, but you get your best outputs and your best productivity when you when you really lock down your your prompting and asking the right question. Here we go again, using the right words. So So now you're gonna agonize over the right words to use in your your AI prompting. But there's a but that's the opportunity is just start to get comfortable with AI.

Jordan Wilson [00:37:09]:
That's that's such great, you know, that's such great advice because it's something I tell people all the time, you know, because people are always trying to place, you know, generative AI on on a hype cycle or look at this Gartner or, you know, and I'm like, no. That's not how AI works. You know? I tell people, like, replace the word AI with Internet, and it's like, do you work on the Internet? Do you use the Internet? Does the Internet help you grow? Does it help you learn? Right? So just swap out the word generative AI and I think that's, you know, pretty applicable. So, you you know, as we as we wrap up here, you know, Kimberly, because we've talked about a lot from, you know, AI can help take the emotional burden off in in your soft skills and help you influence to how AI can specifically help with product management and help find better insights and customer feedback and and better impact the direction of future products. But, you know, maybe what is your your your one biggest takeaway for people working in or around product management, and and how AI can really help them, you know, in their future using it?

Kimberly Williams [00:38:09]:
Yeah. I think there's, there's there's 2 things that I would love to to highlight. 1 is as a product manager, one of the key aspects of our role is to talk to customers. And I think we have a real opportunity to, as we talk with customers, to inform them about AI. So dispel any myths. Some customer there's change management, that's involved with AI, and that's really a change management across all of us. Right? It's not just a product product management. It's not just, you know, customers, but there's a there's a global shift in how we think about and use AI, both at work as well as personally.

Kimberly Williams [00:38:54]:
And I think as product managers, because we have that, that direct connection with our customers, we have the opportunity to hear their concerns, understand what some of that change management shift looks like and what's needed. We also get to hear from customers the art of the possible with AI. Like they also come to us with ideas and ways that they want to use AI. So I think, one is being that listening, conduit with our customers, specifically with regard to AI. But then also when we collect feedback from customers, whether it's, directly through a conversation or if we're having surveys or we have, feedback forums where customers can still leave digital feedback, using AI to help sift through and translate all of that variable text, feedback so that we can have real insights that we can take to action, for our customers. So I think that's the main thing from a product manager perspective. And then I'll just say again, I think everyone, you know, AI isn't going away. The more we get comfortable with using it, I think everyone can be successful in this space.

Kimberly Williams [00:40:14]:
And if you're not already using it or you don't some companies don't have AI. They don't they don't allow AI in the company. So there is an opportunity outside to to play with chat g p t or play with, you know, DALL E or Midjourney creating images, just anything that's fun. Because then that also takes away the burden of, you know, I have to I have to be productive with this thing. Because your first couple of things might not be as productive as you want it to be. Again, it kinda comes back to, you know, the value of the output that you get is somewhat related to the value of the input that you put in. So, good prompt generally can give you good output.

Jordan Wilson [00:40:58]:
This this has been an amazing conversation. My gosh. Y'all, I I have 19 main points, right, that I somehow have to boil down in a newsletter where where we'd normally go over the top 3. I'm gonna have to use AI, Kimberly, to to help me here. I'm gonna go into Copilot and see if it can help me. But, so so much great information, on today's show. Kimberly, thank you so much for joining the Everyday AI Show. We really appreciate it.

Kimberly Williams [00:41:24]:
Thank you, Jordan. Thank you, everyone. It's been a really great conversation. Thank you so much for having me.

Jordan Wilson [00:41:28]:
Alright. And, hey, as a reminder, y'all yeah. There's a lot there. So if you haven't already, make sure to go to your everydayai.com. I'm a human. I'm gonna be typing up this newsletter, but I'm gonna honestly need help from AI because there's so much helpful here. So make sure you check out today's newsletter. And if this was helpful, please share it with a friend.

Jordan Wilson [00:41:45]:
If you're on LinkedIn, please go go repost it. Leave us a review on Spotify. Follow us, Spotify, Apple, all that good stuff. Thanks for tuning in. We hope to see you back tomorrow and every day for more everyday AI. Thanks y'all.

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