Docusign's CEO on the dangers of trusting AI to read, and write, your contracts

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Hello and welcome to Decoder. I'm Nilay Patel, editor in chief of The Verge, and Decoder is my show about big ideas and other problems. Today I'm talking with Allan Thygesen, the CEO of DocuSign. You know, DocuSign, the platform where you sign things online. 7,000 people work there, which is one of those facts you see fly around sometimes. That has always felt like perfect Decoder bait. What are all those people doing, and what kind of a product roadmap does a company like DocuSign even need?

I always assumed that I would never find out the answers to these questions, because most enterprise software CEOs do not like being on Decoder. That's because most enterprise software is terrible, and they don't actually use their own products, so they have a hard time answering my questions. So I was pretty happy when Alan agreed to come on the show and told me that he'd actually used DocuSign himself just that morning. From there, we talked about what DocuSign's platform actually is, how it's expanding, and of course, how all of those employees are structured.

Alan's only been the CEO of DocuSign for three years, so he has a lot of interesting perspective on where the company was, the changes he wanted to make, and where he thinks this is all going. Of course, that brought us to AI. Alan and I spent a lot of time talking about the idea that DocuSign should summarize contracts for people before they sign them, and who is responsible if the AI gets that interpretation wrong. We also spent a while talking about how DocuSign's customers actually generate the kinds of documents that get signed and how automating that process with AI does and does not work.

You'll hear Alan point out that a lot of this looks like a fancy mail merge, which was at least refreshingly down to earth in the context of an AI conversation. Of course, I also asked Alan which parts of his enterprise software were bad and how he'd improve them. And he actually answered the question, which might be a first for an enterprise software CEO. This is a good one. There's even a couple dunks on Google in the mix, as you'll hear.

Okay, Allan Thygesen, CEO of DocuSign, here we go.

Thank you, Eli. Good to be here.

I'm excited to talk to you. Um, I always love it when an enterprise software CEO comes on the show. Uh, most of your most of your competitors in enterprise software are very reticent to show up, uh, and answer the first question. When was the last time you used your own product?

This morning.

This morning, what did you sign? Can you say

I signed an agreement for our procurement team, but yesterday I signed your release form.

very good? It's the it's the most important question, I think, for enterprise software CEOs, because the experience of using enterprise software is, I would say, on the whole, pretty dicey.

it's not great. I agree.

Um, and DocuSign is a is a weird one. It's in, it's in the background of everything all the time. Most people don't use it. I think a like a lot of lawyers, maybe procurement teams, like, use the product. Most people sort of experience DocuSign. How do you think about that split?

I mean, it is sort of a two-sided network, right? So we sell to businesses and other organizations that wanna send documents for signature, prepare them and send them. So that's been historically our business. And then consumers or other companies, um, sign documents, um, the the counterparty, um, but they don't pay us anything. Um, and so most people have experienced us that way. And then if you work at a company or organization that uses DocuSign, you may have experienced being on the on the sending side of approvals or, um, uh, other functionality.

That business is really interesting to me. DocuSign as a company is interesting, most notably because it's been an independent company for twenty some years, it's a public company. From what I experience, again, as somebody just experiences DocuSign, it's just there. It's just in the background of almost every kind of thing I do. But it's shocking to me that it hasn't been acquired or people haven't tried to acquire DocuSign, that the product range hasn't dramatically expanded in in other ways.

How do It's expanding you account for? now. Well, sure, what, what comes in the way that everyone's expanding, right? The now the chatbots are gonna do all the work for us. But like, how do you think about the fact that it it has been effectively one product experience all this time? What's made it resilient in that way?

Well, yeah, so you're right. We are a little over twenty years old. Uh, and you know, the original idea was to, um, help comp help companies and individuals sign agreements online. And at the beginning, no one thought that was a good idea. Not regulators, not companies, not consumers. And so there was a tremendous amount of trust building across those three constituencies that happened over time. Um, but as you said, you know, you know, over time we became trusted for a variety of transactions, and now it's sort of in the water, um, across companies of all sizes and functions.

Look, we we we did do, we did come up with a great idea. And and when you have a when you have a good idea, you want to run with it. And I think, uh, DocuSign has done a really good job of that. With that said, I mean, part of my goal joining about three years ago was to say, okay, that's an amazing foundation. And we're privileged that people have positive associations and we're used by 1.8 million companies.

What do we do for encore? How do we broaden the platform? Uh, and the company, I mean, we'd had some ideas on that for a while, um, thinking about the entire agreement journey, but we'd never really put it all together. We'd never gone beyond the marketing side of s of identifying that problem to actually delivering solutions that could solve it. And I think that's what we're doing now, and so that's very exciting. But the signature piece is a foundation that is the most pivotal moment in the life cycle of an agreement.

It's very high value, a high stress moment for many people, and making that simple and delightful wa- was a very meaningful value proposition. And it's a lot harder than it looks.

Can I let me ask you a very existential question first? Uh, you know, again, I, I, I assign DocuSign's the my signature in DocuSign has no relationship to my actual signature, right? Like, DocuSign just generates some cursive that says my name. What what is a signature? Like in DocuSign's worldview, what is a signature?

I mean, signature to me is really identity and consent commingled, right? Uh, and the identity aspect, that there's a lot of things we do to identify you, right? We we, you know, obviously, this thing comes to you in your email or your on via SMS, or via WhatsApp. Um, we do all kinds of IP tracing and other things and that to validate that you are the intended, let's say you're the signer, that you are the intended recipient.

Um, and that whole trail is then auditable and and can be used in a court of law. So it's it's a perfect substitute for a wet signature that that you might otherwise have done. Um, in practically all cases, there are a few in the US that are still requiring you to sign something in person, but but we've we've done a pretty good job over time, uh, getting to a place where that's felt that that's super secure.

And from the consent perspective, I mean, you're right, you. It could be a dot, it could be a checkbox, it could be a signing. It's almost less important. There's some ident. There are some personal expression aspects of it, but um, it's the it's the identity piece that's the the most important. And then the fact that you take a s a a step that indicates consent.

Just to make that as reductive and simple as possible. It sounds like the service that you're providing is docu sign is you know who I am, you know who the other party to the agreement is. I hit the button and your database says this person that we've verified hit that button and they say agree. And then, if you know the contract comes into question, you can say, well, you, you definitely signed it. At the very least, maybe you disagree on the terms, but you definitely signed the contract.

We're not gonna argue about that. That implies, like, fundamentally, the product is just a big database of identities and then a marking of consent. Is that how you think about it in in, like, the most reductive way possible?

that's the aspect of the execution side. There's all the stuff that leads up to preparing a document for execution. And we have a lot of products there that that you as a signer would not see, but that companies use uh, to get documents ready for signing and to get them approved internally, uh, to get them maybe customized for you. Let's say I'm running a big sales team, let's say DocuSign sales team, uh, and I wanna send an agreement to the decoder, uh, for you to be able to use DocuSign for your, um, you know, releases.

I can automatically sort of mass customize a standard template using DocuSign's functionality that's embedded in Salesforce and other CRMs. So that that's an example of the type of workflows that we do. We do that for hiring, we do that for procurement, we do that for new vendor onboarding. All those tools that lead up to that magical signature moment where it is, I think, about identity and consent.

Even that part where you're okay, we're gonna generate a bunch of documents, that's downstream of the first product, which is right signing. The reason I ask about it in that reductive way is there's a lot of ways you could verify identity and mark consent. You have a lot of competitors there. Is is DocuSign's sort of dominance, market leadership, is it based on just network effect, that it exists? It's the one you can use, it's one everyone trusts, and because so many people have already used it, it's the easiest thing to use.

Well, I do think that that network effect is very important, and people choose DocuSign in part because they know that, um, the recipients, consumers mostly, um, trust it. Um, and so, yeah, maybe if you're a giant bank and you have an existing relationship and you're sending something to a customer that's already yours, you know, that matters a little less. But for most companies in the world, in most situations, all new customer onboarding, et cetera, that trust component is super important.

Now, to to the other thing that was implied in your question, which is, um, well, what about identity and these alternative technologies for establishing identity? Well, I, you know, we we could sort of see that coming, right? And so we we worked on a federated identity strategy to give you all kinds of identity validation at different levels of risk. So you probably, you know, we we let people do knowledge-based authentication. That's sort of on its way out, but that's answering those questions that you probably remember.

You know, where did did you live on the street, uh, 2010 years ago? We do biometric-based identification, so video or other. We c, you know, we can link up with the, you know, the Apple and Google stuff. Um, we do risk-based assessments, so we can fork you to to which validation mechanisms, right? We use the new digital IDs, so in the US, clear or ID dot me, which is the government one that the IRS uses.

In Europe, of course, many governments have a national digital ID, same in many other parts of the world. And all the way up to a notary solution, we have online, uh, notaries. Uh, so whatever your, they should say, um, risk assessment, whatever you feel is is the appropriate trade-off between convenience and security. Um, we can give you all those solutions, turnkey in one platform. And then at the end, most of the time, you're also legally required to get a signature.

So

Um, when you think about that journey, right? Who are your biggest customers? Is it just big banks? Is it mom and pops? How how does that break down for you?

we're incredibly diversified, so we are used by, as I mentioned, 1.8 million companies. You know, by definition, if you have that many customers, most of them are going to be small. Uh, but we are used by over 95% of the Fortune 500 and equivalent in many other international markets, and then many mid-sized companies, and then a huge long tail of small companies. And no one company represent any, you know, meaningful share at all of our business.

Um, our, that said, our biggest customers tend to be banks or other large companies that have high volumes of high value agreements. You know, if you have agreements that matter and you and you're entering into them in large volumes, you're very likely to be a DocuSign customer.

Is that the push for growth? And I I do wanna talk about your expansion into other kinds of products and services. Is part of that you're just out of big customers? There's not, there's no more fish in the sea.

Well, we we already have, you know, most, uh, large companies in the world as customers. But of course, there's so much more we can do for them beyond the signing piece, and even the signing piece, you know, we're we're certainly not done with that. I mean, even the large banks who've been with us for a decade plus, um, but they will. You go and audit them on on how many of their agreements are are actually automated and digitized and and executed electronically, and it's twenty, 30%.

Um, because, you know, people take the biggest high-value workflows and and everything else is sort of left to the side. So we have a lot of opportunity. If we can make that more efficient and easy to do, we can, we can, um, close all of that, uh, gap, as well as, of course, provide this broader value in all other aspects of the agreement cycle.

Talk to me about that. So there's identity in in signing, which I was very curious about, cause the notion that a signature represents many complex concepts underneath. I think most people don't ever spend time on paper. Think about it. Yeah, So that's the first part. Then there's okay, we're generating documents for signature. We might as well help draft the documents and prepare them and get them approved for that final step. I wanna I wanna understand that a little bit.

And then there's obviously your expansion into AI and other tools and other parts of the workflow. At what point do you run into Microsoft Word, right? Like, where is the boundary of some of that work, and like, where are the boundaries of some of that opportunity?

well, I mean, we ran into Microsoft Word the day we got started, right? And Microsoft Word is where ninety plus percent of legal documents get authored. That's what the tool that most lawyers use, that's where documents are crafted and often negotiated, redlined, and, you know, et cetera. So we've always been deeply integrated with Word, and of course, with with Google, uh, as well, and frankly, with all of the tools that people use to to do their jobs.

So, I mean, we've had a twenty-year partnership with Salesforce, saying we were, I think, the first or second vendor on the App Exchange and deeply embedded in their flows. We do similar work with Workday and SAP and so on. So to your question about, you know, I don't think that we or Microsoft have ever thought about competing with each other. Like Microsoft, I mean, I I worked at Google for twelve years before taking this job. And so, you know, similar scale company, and you take on the biggest, broadest opportunities in your office suites.

And yeah, you might add li more and more features to your s, to your, to your office suite. But, uh, you don't wanna add stuff that's sort of s separate workflow or things that are too specific. You rely on your ecosystem for that, and and that's what Google and Microsoft have done. So they'll both allow you to render a signature inside of a doc that you author in those packages. But no one thinks that's a substitute for DocuSign for all the reasons we've discussed.

And so it it just literally doesn't come up with customers. I I've never heard anybody say, Well, maybe I could use Microsoft Word or Google. That has never happened in my three plus years here.

it's all of the steps leading up to you're gonna experience DocuSign that are fascinating to me. So when you say help prepare a document for signature, there's the drafting, right? Microsoft Word, Uh, honestly, Microsoft Word might be the reason I'm not a lawyer anymore. I was like, I just can't, I can't use this software anymore. Um, there's, there's a Microsoft Word of it. We're gonna redline a bunch of stuff. We have the document. From that point, what do you mean by prepare a document for signature?

What is it? What are the services DocuSign provides?

Let's imagine, um, most c. Some contracts are completely custom-crafted, right? You know, maybe, but most fa- you're, you're, I think you're a lawyer, right? So you most documents, uh, most contracts start with a template of some kind. Maybe it's a template for something really complex, like an M A agreement, or something really simple, like an NDA or anything in between. Could be a master service agreement between a company and another company or a license agreement. But they always start with a template and then they tailor it.

Some of that is done sort of legal tailoring, right? You know, I wanna have different limitation of liability, I want to have different payment terms. And some of it is just, should we say, mass customization? I want to get the data about that customer and some things we've already negotiated. And I want that to flow automatically from whatever the system of record is could be Salesforce, could be Workday, could be SAP, could be whatever. And I want to populate that into the agreement.

So this template that I have gets personalized, customized, and that's also what happens in consumer applications. You know, the the forms that you get from Chase or Wells, or, uh, you know, they are, um, they are mass customized that way. And so that's essentially a data hole. So that's what I mean when I say, um, uh, customized or personalized. It's it's taking a a standard document. Now there are a lot of things that can flow from that.

You know, let's say that you are a national employer, but you need to take into account employment laws in the fifty states. That would be an example of a customization that's a little bit more complicated. Uh, and of course, that gets even worse if you're a global employer and you have to do offer letters in 180 countries. Um, you know, that starts getting pretty complex, but there are rules. We have a system for applying those kinds of rules so that you can have global standards, but still create documents that are tailored to local laws and customs.

This gets me right into the opportunity for AI broadly, which is you're starting to do some of the lawyering a little bit, right? You're saying, y- you're not gonna hire the junior associate to figure out the local law. You're we can actually just programmatically make a contract that abides by the local law.

For that type of application, correct? I think there are two big use cases for us. One is to make ex agreement workflows more efficient, sometimes just by automating them and sometimes by reimagining them. That's a huge part of what we do, and this mass customization is not a new thing. That's been going on for a while, that's sort of advanced mail merge, right? And so we, we,

uh, you said, I didn't we, uh, wanna say it, you said I, I, it.

I mean, it is, it is, it is. Um, but look, it's really, it's really good and it saves a lot of time. And, uh, it's it, you know, a lot of companies live live live Well, if I with that.

could start a business that was charging a premium on mail merge, I would do it too.

Oh my god, yeah. Managing people's address book would be another one that would be very valuable. I'm gonna solve that. But anyway, so making workflows more efficient and now tackling all of the steps in the agreement process, that's part of of of what we're doing, and so we're we're tackling things like, well, ingestion of agreements. If, if, you know, we have a whole queuing system where a sales rep or procurement rep can trigger the sending of documents for legal.

It can get an automatic first review, then it gets assigned to a lawyer, the lawyer does a quick thing, and e everyone has real-time status. That's an example of reimagining legal workflow, which today is totally asynchronous email, unpredictable, non-transparent, right? Now, that's one piece, and I think that's what people have historically focused on with sort of contract management. And then the other piece is I'm gonna take AI and I'm gonna extract data out of the agreements to run my business better.

That's something that was conceptually possible for, um, you know, historically, but it was just too heavy and hard to do with legacy LLMs. And now we can do that in a completely automated way. So I can go to people and say, Hey, you have 5,000 agreements with me. Would you like to know what's in them? Let me highlight how these agreements deviate from agreements with peer. You know, your company X is coming up for renewal in ninety days.

How can I review that? How can I, uh, know what I should be renegotiating? I can give you that using AI automated right off the shelf. It leverages the fact that you already use DocuSign and you've already stored your agreements with us, uses modern AI, and then adds, of course, some workflow and automation on top.

We have to pause here for a short break. We'll be right back.

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Welcome back. I'm talking with DocuSign CEO Allan Thygesen about why exactly his company needs to be as big as it is. Let me take a beat here and just ask the decoder question, so I have a better sense of the the company itself. How is DocuSign structured? How many people is it? And how they organized?

DocuSign has a little under 7,000 employees. Um, and you know, our structure has gone through some some transformation. Historically, I would say DocuSign was a, you know, ignoring the very early days of conceiving the product. Uh, it evolved into becoming a very sales-centered company. Sales, you know, all mo- most customers interfaced with with DocuSign through sales. We had a very large sales team, and and that was sort of the most powerful function of the company.

That things flows from there were optimized around that. When I joined and we I, I very quickly realized we needed to completely reimagine our product roadmap. I really wanted to put product at the center of the company and say we we're gonna articulate a new product roadmap and things are gonna flow from there. Um, that's not to say that we're not taking lots of customer input. After all, we we we've got twenty years of experience working in agreements and millions of customers.

It's but we want the we want the product vision and the overall architecting of that to to be the guiding light for then what we, how, how we go to market, how we spend, et cetera. Second area that I focused on was, um, historically, uh, marketing here worked in the service of sales. It was basically about creating qualified leads for sales. But I'm like, well, customers, this is an electronic contracting product. They should be able to just come in and do whatever they want to do directly self-serve to the greatest extent possible.

And you know, I I came from Google, where every advertiser, including people who spend a, you know, a billion dollar plus a year, places their own orders in the system. But at DocuSign, uh, we couldn't couldn't do that. Uh, so that was another area, and really taking all the pieces of the company that worked on on identifying, sourcing, and and bringing new customers on and combining them in one team. And then the third area that I'm I'm really pushing on is, uh, we've always felt like we needed to own the ball.

And when you have a iconic, simple product, then that that you you maybe don't need partners as much. But now, with this broader vision for agreement management, we really need partners to help us go to market and install and, uh, and service the product. And so we're we're very focused on on working with system integrators like the Deloitte's and Accenture's of the world, as well as distributors and resellers. Those are the big changes we've made.

I have to say, 7,000 people is a shocking number. The last number I heard was actually 4,000, which was shocking then. How are 7,000 people organized at DocuSign? Is it sales and marketing? Is it product? How does that work?

Sales and marketing is the biggest area. Uh, we prob- we have about a thousand account executives that cover everything from S and B accounts all the way up to enterprises. We're not a small company. We do over 3 billion in revenue. Our revenue per employee is, you know, pretty pretty much in the median of of the um, of the SaaS businesses. So sales and marketing is the biggest function. Um, and it's it's everything from from pre-sales to account executives to customer success people that help with implementation and support, of course.

Um, uh, product and engineering, uh, we have about, um, a thousand people, uh, in, uh, in engineering, 1,200 have been engineering proper, and then there are product managers and designers and so on. You know, I think if you look at the um number of countries and the complexity of the regulatory and compliance environments we're in, uh, you know, that's a significant effort. And then now with I am, I've pivoted pretty much all of the open investment dollars in the company the last three years have been pivoted into this.

So we've gotten much leaner on the sales and marketing side, and we've got, um, invested more heavily in in in product and engineering.

IAM is the AI product.

That's right.

When you think about shifting that investment focus and then something like self-serve, you were at Google, you were at Google for, I think, twelve years, something like that. Um, you've been the CEO of DocuSign since 2022, so you've been there a minute.

Three years.

How did you think about changing DocuSign? How was it organized before? And then when you got there, how did you think? How do you work through? Okay, here's I'm gonna reorganize it for the opportunities I wanna attack.

I mean, I think the low-hanging fruit was, um, helping the company, um, pivot from just being a um, um, a good machine for acquiring new customers, but not necessarily an amazing retention machine. So focused on customer retention and customer success and adoption. I think we sort of took that a little for granted. That was one area. Second, getting us to be much more efficient, as I alluded to, whether it was through building out digital channels or just streamlining our sales and marketing efforts.

So, uh, that was a a a big immediate push and sort of low-hanging fruit things that were in my control, um, early on. But the biggest change is really the product, uh, vision effort, um, and and pivoting the company to being, um, product innovation led and sort of restarting the innovation engine at DocuSign. Covid was a seminal event in the company's history. Um, not in a good way. I think everybody thinks that COVID as DocuSign as a COVID darling, and that we must have been so great for us because everybody had to use us.

And look, there was some of that temporarily, but if you look at the long run, it didn't change the sort of secular adoption trend of of signing, you know, things electronically. But everybody literally fell asleep. You know, if you're a sales rep and your revenue growth rate without much effort goes from 25% to 60%, um, you're you're in the order taking business. Um, and on the engineering side, we didn't need to develop that much.

Uh, w- you just need to keep the servers running and scaling that. And so I think restarting that, hey, we can build something great, something new, and reclaim that innovation mojo. Um, that was, I think, the most important transformation at DocuSign. It's still ongoing, but I mean, the the pace of product innovation and product release is completely different now. Um, and we actually had to throttle the number of releases we were doing, cause there was so much.

It was sort of starting to overwhelm our our customers and our sales team. We have so much stuff and there's so many opportunities. Um, and that's an exciting place to be. Um, so

was that your pitch when you when you got the job? Very few people are gonna ever interview to be the CEO of a multibillion dollar publicly traded company. What was what was the pitch? I, I'm gonna restart your product innovation.

it was a dual pitch. Um, I said, Look, what I know I can do is I can come in and make things much more efficient. And of course, I used my digital marketing background from Google to make some suggestions on things that I thought we could do.

Did you make just like the a killer deck?

You know, I didn't get time to make a killer deck. I mean, literally, I got a call from Headhunter on a Thursday night that the board wanted to meet with me for an hour and hear my thoughts on the future of DocuSign. Saturday morning at nine zero, and I was working full-time at that time at a big job at Google, and so I couldn't just take a day off, and I suppose I could have, but I didn't.

And so I basically had Thursday evening and Friday evening to prepare, you know, a short slide deck. And I mean, the reality in these kind of situations, nobody expects, you know, the super polished multimedia thing. What they really are focused on is what's what are the thoughts, right? And you can use ten point for your talk, that's fine. And so I was really focused on, look, I I know I can make the company more efficient. I I know there are there's gold on the retention side, and I believe that the agreement problem is fundamentally unsolved.

But that DocuSign is the best position to capture that opportunity. I mean, we were a big DocuSign user at at Google, still is, they're one of our largest customers. Huge, uh, e-sign, uh, and contract lifecycle management was our advanced contract management project that that enterprises use. And yet I knew we were in the earliest possible phase of transforming how agreements get done, um, and that there was so much opportunity. Um, and so I just articulated my confidence in that.

Uh, I knew enough that I couldn't that it would be I would lose credibility if I was too specific. Um, so that took six to nine months to really say, okay, okay, that's fine. At 50,000 foot level, how do you get to the real vision of what? What's the singular thing we're gonna do? I mean, just as an example of that, it's easy to talk about all the steps in the journey. And I think people naturally gravitate towards the drafting and and negotiating side of agreements, because that's it's almost like what's in movies.

Of course, that's what lawyers do. But we actually started at the end. We said, look, the the foundational piece of reimagining agreements is to have an intelligent repository, to have an intelligent, a place where all your agreements are stored. And to be able to apply AI to that. So we can tell you what's in all your agreements, start comparing them, and then ultimately close the loop to what happens under those agreements. So that's what we built.

Is that what you mean when you say the the problem is fundamentally unsolved? Is that is that? Well, That's a resolution?

that's part of, that's part of it. It, it, we've done. The way I would describe it is we've digitized the asset, right? We've taken what used to be an offline asset, we've turned it into an electronic document, and we move it around electronically, mostly via email. And then hopefully we execute them electronically. And other than that, absolutely nothing has changed in fi for the last fifty years in agreements. And all other aspects of the workflow, they're just as inefficient, just as brittle, just as unpredictable.

There's just as much time lost waiting for some p- somebody in the process. You don't even know who they are or what they're, what, what steps they're on. Once you've signed, the agreements go to a deep dark place. It might as well be a physical filing cabinet in a basement. In fact, it's probably harder to find now than it used to be when it was in the filing cabinet. You know, now it's in some SharePoint drive or email inbox, or who knows.

And so bringing all that together and presenting that information in a in a way that, you know, is is intelligent, bite-sized, appropriate for the for the persona is incredibly valuable. I mean, every CFO wants to know what are the top ten contracts where we have leverage, we things we've negotiated for that we're not getting. Every head of sales wants to know what are their top ten renewals and what are the three things my rep should be renegotiating.

Every procurement, you can just go down the list. It is an obvious pain point that no one has solved. And so that's our opportunity. That was my pitch, and I think I think it was a good pitch. And

yeah, it's it.

and I think the story, and I think the story is much better now than it was two years ago.

Uh, I wanna get into that. I wanna, I wanna talk about how you're implementing that, obviously, as part of it. I wanna talk about whether it's working, which is interesting, but I wanna ask the other decoder question first. Obviously, you're at Google for a long time. Google's decision making, lots to say about decision making at Google. Um, what's your framework for making decisions? What did you take from that experience, and and what do you do at DocuSign?

Look, I loved my time at Google. It's an amazing company, and, um, proud of the time I spent there, and I've always have a special place in my heart. One thing I do not miss is the seven-dimensional matrix of, uh, trying to make decisions. Um, so I I really try to avoid that here and have much greater clarity about who owns the decision, um, who needs to be consulted in all those kinds of decision frameworks. But I'd say one thing that, um, I took away from Google as a very positive lesson is my experience, um, and this is not limited to Google.

But that the most effective leaders in tech can go super deep when they need to, and they need to be willing to do that. You know, management is not floating up in the abstract 50,000 foot above the problem and just admiring it and thinking you can just, you know, uh, operate at that level. Um, I think when hard decisions need to be made, one-way doors, things that are complicated, you need to be able and willing to really dive into the details.

And, um, I've always prided myself on that, and and I think that was. That's particularly important at a transformation moment because y- it needs more push from the top to get people to change, right? People naturally wanna do things super incrementally. It's not unique to any one company, that's just how people are. And so if you're trying to get more radical change, you need to push. And to in order to push and not break everything, you need to get deep in the details.

So when we were dec, you know, deciding on the early architecture and what the key launch pieces were gonna be for intelligent agreement management, um, I was in, you know, daily whiteboarding sessions to to help decide what that was gonna be. You know, once we accept that direction, then you step back and you just let the team run. Then you maybe get to a decision point about, okay, well, how are we gonna talk about it? How are we gonna explain to people this newly reimagined DocuSign?

That was a big moment of getting super deep in into deciding how we were gonna message this to the market, how we're gonna relaunch the company effectively. And then you gotta decide, well, how do we take all this capability and find the singular thing that we need to tell customers about to get them to try it and buy it? Cause, you know, all software has ten x the functionality that people use, and finding that singular proposition, um, is super important.

So those are examples of things that I got much more deeply involved in, um, and I think that is essential to being effective. But then you gotta let go.

so let's let's talk about the the technology here. I it's I am, uh, it's intelligent agreement management, that's the the new system, that's where the AI focus is going. You've talked about it already a little bit, right? You can you have this library of documents you've signed, you can extract intelligence from them. I gotta say, I looked at the the website just before we started talking, and how are you marketing this thing? And it a lot of it is DocuSign will tell you what's in the agreement you're signing.

And all of my lawyer red flags just like went off. Like, you should not let the robot interpret the document for you. How? D And one of the reasons is, well, is DocuSign now responsible for the interpretation of this agreement, right? If I sign this and, you know, the AI hallucinated an interpretation of this clause, and then I'm mad, do I do I get to s? Do I get to sue DocuSign?

We literally, I think the reason you're seeing that on the website is we literally just launched this for consumers, um, last week, um, and so it's, uh, the most recent release. It's not generally, um, wouldn't generally be the top thing, but, um, right now it's newsworthy. And things that are consumer facing tend to get more attention, as you know.

Here you are on Decoder.

Um, with all that said, um, I mean, look, w- w- we've had agreement summarization for a long time. We we provide it internally to companies that that prepare documents, that send documents. Um, we waited a long time to launch it for consumers, exactly because of some of the concerns that you raised, right? We we wanted to get to, um, a high level of accuracy. We wanted to make sure that we, um, could position this as something assistive, but that we're not replacing a lawyer.

And you still need to get legal advice, but that people valued that sort of high-level summary. Um, and all of our all of our very robust, uh, testing suggests that people have, um, uh, are more comfortable and have greater confidence, um, and that they at the same time understand that, you know, when something's sensitive, they need to get to a lawyer. Um, so it's look, it's a delicate, it's a delicate thing, right? We wanna, we wanna be the place w- where that people, um, trust the most for, um, receiving and executing agreements.

And so not providing an AI service isn't really an option. And at the same time, you gotta have a ton of of guardrails to avoid putting yourself in position with people who claim that they relied on you or that you are the, um, that you are acting as a lawyer.

Yeah, I'm I'm just curious about the dynamic there. I was I was talking to a colleague of mine just before we started, and I said, Uh, they've got this new product. And I asked him about it. And what she said to me was, Oh, that makes sense. I already take the agreements and paste them into ChatGPT and what? What's happening? But, uh, in that case, right? You don't get to go in front of the judge or file the complaint or even send the threatening letter.

Being like, this is what ChatGPT told me the document I was signing says.

Well, I think I think, you There's some know, the AI's probably

distance there.

they're probably worried about that, whether They they might be the the the

worried about it.

consumer's gonna do.

But. But I think it was But like, that fact pattern is like, Well, that's your fault, right? I signed that, I pushed the button, I indicated consent after having my identity verified in the database. Next to the summary is a different fact pattern. So what are the guardrails that you thought of? I mean, cause it's gonna happen, right? Someone's gonna blame you for a mistake that they made or that the system made. What are the guardrails that made you comfortable with that, or that made you think we're not liable at all?

there's two answers to that. I mean, there there's sort of what got it comfortable legally. Um, I I think we got very comfortable that all the language of the scammers and how it was done graphically and so it was fine. But I don't think that that's the big question. To me, it's more of a moral question, right? Are you, are you doing the right thing for the customers? Feel good about that? And we got to a place where there was no question in our mind that this was, um, better for consumers, uh, and that, um, to continue to uphold trust in our platform as a place to come and execute documents.

That we were the best position to provide, uh, this kind of additional advice and context. In fact, it would be dereliction duty not to provide it, um, and that we needed the best possible job we could to, um, make sure that people understood that this was context. But, um, if this is something that's really sensitive for them, they they should get, they should get a lawyer. Of course, they don't today. They just sign. Uh, so I think we're improving the situation, um, both, but for consumers, but also, by the way, for companies, um, and uh, and so that was our motivation.

Um, and it, it's, it's impossible to eliminate. People are gonna claim things. Um, I think we're doing the right thing. And we felt like we were taking not just the necessary precaution from a legal perspective, but necessarily from a company values and morals perspective, and it just felt right. So we c that's how we got to it.

We need to break here for a quick minute. We'll be right back.

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Welcome back. I'm talking with DocuSign CEO Allan Thygesen about the risks of AI in legal work. The reason for me asking about liability and whether the system's gonna be wrong is that LLMs is a core foundational piece of technology. Still hallucinate, right? This is the flaw with LLMs. You know, I I if you talk to any of the big AI CEOs, if you talk to Sundar Pichai, he will say it's also their feature, right? The reason that they are creative is because they are effectively hallucinating.

And if we unbox that in,

That's a create that's a creative repositioning. But yeah, uh-huh,

you said it, not me. Um, this is the dance, right? You you want an LLM that can do a bunch of creative writing, you need hallucinations. You want an LLM that's gonna do legal analysis on a library of documents that maybe is twenty years old. You really don't want it to hallucinate. How are you constraining the LLM to make sure it does what you want it to do?

I mean, so if we pivot to the folks, um, that, um, use our document to, uh, use our tools to prepare documents, um, you know, there are a lot of, uh, guardrails that we put in. I mean, we have a whole risk scoring, uh, thing. We we, of course, benchmark you versus your existing, uh, templates or, uh, playbooks, as they're often called inside of companies, um, and highlight things that deviate from that. And this is true both for agreements that the company prepares themselves and for third-party agreements that they receive from others.

Cause, of course, most companies are takers of terms, uh, from other companies, right? Um, uh, and and so there's a lot of, uh, workflow there. We also don't, um, fully automate flows. Uh, we we put deliberately humans in the loop at key decision points, um, and I think that will persist for a a very long time. Uh, companies are are very averse to, um, to the the risk of of automation that's going rogue. Um, uh, I I was, uh, we talked about this over Google for a little while, and we there was a lot of efforts at automating the commerce process.

And this is for buying toothpaste, um, and um, both consumers and retailers were very resistant. And even with all the new stuff, I'm I'm, I think it's getting better, but I still think there will be a lot of, uh, hesitancy on those. Are much lower stakes than than agreements. So

But but put that into practice for me, um, just with the products you're talking about today. I am a company, I've got twenty years of agreements in DocuSign. I I wanna know how have my terms changed over time? And I ask DocuSign to generate that intelligence for me. What's the guarantee that it's not just hallucinating, that it? It doesn't go through the first five years in the RAG process and then it just decides to get bored and makes up some contracts that never existed?

look, I think the stakes and the opportunity for hallucination in an extraction scenario are far lower than in a drafting scenario. Um, uh,

Sure, but it's gonna draft a report, right? It, it, you're, you're, you're gonna so let it bring.

I, it'll, it'll do, it'll it, it'll, it'll, yes, it'll, it'll show, it'll, it'll highlight things. Well, I mean, you got to link to the sources, you got to have all, all of that to sort of show your work and the logic of the decisioning. Um, but look, there's there's no amount of automated decisioning that's ever going to be 100% perfect. I think we're getting to an extremely high level of of accuracy. I mean, we have the largest agreement repository in the world.

You know, when we when we got started, this is a very interesting story. So when we got started with I am, we we have petabytes of agreements because of our signed product, but we did not license those agreements specifically for processing in AI. Uh, you know, no one thought of that, and I don't think people would have consented anyway. Um, and so we said, we're not gonna use any of that data. We're only we're gonna require customers to, on a one-on-one basis, consent to, uh, you know, allow us to process, uh, individual agreements.

And we're gonna put in product functionality so that they can opt out at any time. So that meant that when we started, we only had access to public agreements, which is what the big LLMs have as well. And we we had a, you know, very good level of accuracy in our extractions, as rated by human eval. Um, and then we turned it loose on on actual agreements inside these companies, and the accuracy fell fifteen percentage points.

Well, out of a hundred, you know, that turns it from super useful, not perfect, but super useful, uh, first drafts, first table type of thing to wow. I I feel like I have to redo everything this thing does. And we've now worked our way back mostly to to our original starting point, and we think we can go much further. And that's because we now have 150 million private consented agreements in our AI, and we're adding tens of millions every month, which is orders of magnitude bigger than anybody else.

And these are all the complex private agreements that aren't generally publicly available. So I think we have a a hidden huge AI advantage in accuracy. That's not just, you know, no one's ever gonna get to a hundred. So it doesn't take away from your point that there could be cases where, um, you know, you you need to have human eval and oversight. But I'm just saying we're gonna be in a much better place to get to a place where you get the real productivity benefits, um, because we can be much more accurate.

you're not training your own models, right? It it seems it you're you're obviously using foundation models from other companies.

Yeah, so we we, uh, we started with, uh, with OpenAI and GPT, uh, where we use Azure as our our first public cloud provider. And since then, we've added, you know, other frontier models, and so we score them against each other and use the best of the best. And it's, I mean, it's an incredible innovation pace. And so, uh, and capital investment that's going in, and the cost per per token, right, is cost per unit, if you will, has just been dropping precipitously.

And so for a company like us, for whom that's a cost of goods, that's amazing. I can now go to customers up to a pretty large size and say, just give us one agreement, we'll, we'll, it's, it's included in your price.

yeah. Tell me about the dynamics of the AI pricing per token. Cause, uh, the idea that the prices are falling requires some amount of competition in the market, right? It requires the ability for you to switch. Are you building your system so you can switch from model to model, or are the models different or differentiated enough?

We already have, um, and, uh, look, early on, you have to say, GPT was, you know, head and shoulders ahead of other frontier models. And over time, so we started there, plus our internal models, and we had, you know, five years of experience in in building and using AI models internally. Over time, it just became clear the frontier LLMs were great, OpenAI in particular, and for a little while, they were kind of the only game in town.

But now, uh, there are a lot of choices. Um, we've got excellent results with Gemini, and so we are, um, and other models, and so we are, uh, we have good range of choices. But even if you're with one vendor, the the cost of processing an individual document has plummeted. When we got started at that summer of twenty three, I was very worried that we'd have to have this very complicated pricing structure tied to the number of agreements that you are uploading.

Because the cost to process them and reprocess them all the time for all these things people wanted to do, uh, was felt like it was gonna be prohibitive. And now, you know, up up to a fairly large company, I it just included in your subscription, and it's, um, it's a totally different game. It's, I mean, it's like a factor of a hundred.

So do you think the models are interchangeable? I mean, you're talking about them all getting good and they're getting terrific.

I mean, I don't think they're perfectly interchangeable, but for our purposes, for the c- applications, I mean, obviously, the models have different personalities in the consumer context, and for certain specific workflows, like coding, there's some models that I think have some specific advantages. But for document extraction, um, we're able to get very good results with multiple models, um, and multiple of the top frontier models, uh, and they are advancing at roughly similar rates.

This leads me to to basically the bubble question, right? If you're saying we're delivering a bunch of value, but the cost of the models is so low that I'm just bundling into my existing subscription cost unless the customer's so big that they're using massive amounts of of tokens, how do you expect the model companies to make any money? Right? Like, that's a race to the bottom where if you're not charging additional margin, you're not gonna pass any on to them.

How do you expect that to reconcile?

I mean, look, I am obviously paying writing a large check to, uh, my friends at Google, so it's not that it's insignificant. It's just that the incremental Is, i i value of an additional

But you're getting more usage for the same dollar over time, right?

I'm getting more usage for the same dollar, and I, you know, we, right? Look, they've gotten so much more efficient, the models have gotten better, the hardware has gotten better, the amount of capex that's gone in, that's now being deprecated is is incredible. And so I think some of that is sort of already in the water. Um, but to your point, um, look, I I think they will all, um, you know, add value in different ways, but I do think that the LLM models, um, I it's it's a highly competitive space, and you gotta add value above or below that, right?

I mean, you can see that the strategies, um, you know, OpenAI is now really doubling down on on both their consumer and and enterprise efforts. Google, of course, has investments in the hardware side, on the cloud stack. They use their AI for YouTube and and ads and, you know, the other vendors, and Tropic is being incredibly successful with their coding product. And so you're you're, uh, you're seeing different, um, strategies playing out for leveraging, um, a a a strong position in the foundation model space.

Yeah, I'm I'm curious about it because you have the perspective, right? You run a big enterprise software product. I you know, ChatGPT announced DocuGPT, and the idea that they're gonna come and attack your moat, which is the database of identities and the the flow, like, that seems not a big threat. But I look at that big sweep that you just described, and most of those companies, they think their money is in enterprise use, right? That's the first big set of customers.

They're it's big businesses with budgets that need to get more efficient and increase productivity, and maybe that's happening, and maybe it's not, right? I I think that's still an open question.

It's it's starting to happen, yeah.

Yeah, something's happening. And then you have the big consumer products, and so you see Google and Meta saying, Well, we already have ad technology, Meta's gonna move all of its stuff to GPUs, and we're gonna serve reels ads that way, and it doesn't matter how many GPUs we buy, cause it's already being monetized. Google's the same way. Then you have OpenAI, which announced an advertising product last week, right? We're gonna do ads in ChatGPT. Do you see a path for like, I guess the question in relation to DocuSign is, do you think that industry is stable enough for you to bet on in the long term as it works through all these machinations?

Cause this is the core technology of your growth. And then second, you have experience at Google, you have experience running an advertising business. How do you think that's gonna go?

Yeah, there were a lot of questions in there. Let's start with the Um, um, I think from a DocuSign perspective, so far, it's all been goodness, right? It's dramatically expanded the value that we can deliver to customers, the scope of our services, and in a way where we could leverage the R and D of others, but preserve a really meaningful competitive advantage through our data, through our workflow, through our trust. And I think, um, it's it's been a it's been a huge win.

I am not, I mean, as you alluded to, I I don't believe that the big LLM providers are gonna provide, you know, agreement management solutions. I think they're gonna look for others to build applications on top of their systems, um, like we have. I suppose it's possible that, um, there could be some of that capability that, uh, seeps into standard products, as we saw with, uh, you know, you can do it in a summary, et cetera.

I feel like it's been amazing in opening up new a much broader market opportunity for DocuSign, and we are running as fast as we can to capitalize on that. And I think the cost dynamics so far have been super favorable to us, and I frankly, I expect that to continue. In terms of the other part of your question on the ads side, um, uh, I I think it was always inevitable that, um, OpenAI was gonna get into the ads business.

I think you can't really do a scaled consumer services play without advertising these days, and so, uh, it was just a matter of time before they got there. It'll be delicate to incorporate ads into a, um, assistive AI experience, um, but look, it was delicate for Google to do that with paid search, but they did, and and I think that turned out to be a huge value unlock. So I think that prize is very significant, and I, yeah, I think it, I actually think they're they're late in in, uh, in launching it, they should have done it earlier.

Um, I think the, um, the transformation of having all that context of the full journey you've been on and the ability to fully close the transaction, um, potentially takes that kind of intentful, um, activity to the next level. You can literally almost go through the entire what used to be called the funnel, right, in one platform. That's incredibly valuable, and so, uh, it's a big prize. Um, and that's why I think OpenAI is investing, and that's why Google's fighting hard and keep its position, and why Meta, I think, is well positioned, why there's so many Meta people at at OpenAI.

Um, so I think it was always inevitable. We'll see how it shakes out. I don't have a moral, uh, issue with it, I think it needs to be done well, right? I think it's, uh, you know, I think you can say a lot of things about Google, but I think they did a a pretty good job of of keeping those walls, uh, pretty separate, and and, uh, um, I saw that when I was there, and, uh, you you gotta maintain the integrity of the results people are getting while incorporating advertising experiences that are accretive to, um, to the users, and that's a That's a difficult thing to do.

I was just at CES and you couldn't turn the corner without a marketing influencer jumping out of a bush and saying the funnel was dead, um, because everyone has experienced everything randomly nowadays. That's a different podcast.

That's a different podcast.

Let me let me try to draw a connection between these two ideas, and there's a reason I asked them together. If you are looking at all the big model providers and they are saying our first opportunity is in enterprise, and the enterprise customers are gonna unlock a bunch of value and build products around that.

And they're actually saying that?

Y- m by and large, when I talk to these That does seem folks on the show,

Like what OpenAI and Meta and Google are doing, um, but, um, I mean,

Well, I mean, and Meta's a I I think unique one, maybe the exception that proves the rule, because they have no enterprise business to speak of, so they have nothing

Fair enough.

else to sell. Google, right?

I agree. There's a huge focus on enterprise, um, and we're very focused on enterprise.

Of course, so you see that, and then I'm talking to you. You're building a scaled enterprise product on the back of these models, and you're saying they're almost interchangeable, and the rates are dropping because I can go get pricing terms because I can just switch. That's one dynamic of pricing that's happening in the industry. Then next to it, you have, well, what's the biggest prize in the history of the internet? It's search advertising. OpenAI is gonna attack that, and we're gonna take some of that share away from Google, and Google's certainly gonna defend its territory, and Meta's gonna do whatever Meta's gonna do.

That's where you would decommodify your models, right? You would say, ChatGPT is so much better, it's it's such a better consumer experience that you have no choice because all the users are here, and that might be a zero sum game. Those things are pulling in wildly opposite directions, in my view, right? You have commodity models for enterprise, which is where all the budgets are, and then you have deeply specialized consumer experiences where you can layer in advertising at high rates.

Can you bring those together? It's see that's why I asked if the foundation seems stable, because eventually one of those things is gonna be more lucrative than the other, and you might run out of enterprise model providers, and, you know, that industry might collapse down to one or two that charges high rates.

I think both are so large that you the biggest players are gonna go after both with very different teams. Um, so, um, you know, obviously, very familiar with Google, right? And Google Cloud is a standalone operating unit inside of Google and operates quite separately, and and and necessarily so, right? In fact, I don't think Google Cloud could have become successful if it wasn't pulled away from the traditional consumer services and ad business of Google. And I think OpenAI is a smaller company, but again, I need to replicate that very different MO and go to market that comes in the ads business versus and the consumer side of the house versus the enterprise side.

That's a lot to take on for a young company. It's an incredibly capable team, and they have, you know, huge amount of IP and so, um, but, uh, that is a very ambitious undertaking to do both. And Tropic seems to have decided to to focus exclusively on the enterprise and are really executing incredibly well, and we're using their cloud code product and it's fantastic, and so huge kudos to them. And then there'll be a host of other players that, um, you know, I think, become either more more enterprise or more consumer focused.

But, um, I think Google, Meta, OpenAI are probably the three that are trying to do both.

Are you structuring your contracts with these vendors to be long term, short term? How how do you think about that?

Yeah, the contracts in that space tend to be relatively long term. You know, th- th- they we and they want, um, you know, three plus year commitment type deals. Uh, you you can't. I mean, as much as people want wanna say, Oh, I can just swap one for the other, that's not really how things work if you're doing enterprise deployments. So, there's a significant investment in porting to a platform and and and the vendor, of course, wants to see the benefit of your growth and the upfront investment they're making in helping you come onto their platform.

And so so they're multi year, they're three plus year deals, sometimes longer.

When do you think you'll have a feature set that's so robust using these tools that you can actually charge a premium to all of your customers?

Well, we kinda do that today. I mean, we we went from being a sign provider, we're charging a substantial premium for moving to this AI assistant suite. Um, because the value, I mean, and I can provide that value instantly, right? You sign with DocuSign, and I can turn on, I can give you AI insights into your agreements day one. In fact, we deploy our new s our new products as fast as we deploy. Signing we're deploying under twenty days, which is kind of unheard.

If you follow enterprise software, that's kind of unheard of, right? Um, and frankly, a lot of that is just human stuff because the product's ready day one. Our customer agreements right now average around nineteen months in length, but they are longer with big customers and tend to be shorter with smaller customers. That's a typical pattern. I expect that our agreements will get longer over time, but we already charge a substantial premium for getting access to the AI features, and customers have been very willing to pay.

We have over 25,000 customers live on this new AI platform in under eighteen months. So

I'm always curious about that number, right? I hear these usage numbers from all the companies that deploy AI tools, and underneath it is sort of the well, it just showed up one day and we're counting that person as an AI user, right? Like, AI overviews are there, everyone knows them. It's like, I don't know about that, like, they just started

Fair enough.

in my face, so I don't want

Fair enough.

them or not. Are you actually measuring happy customers using the tools because they want to, or because the button is there and everyone just clicks it?

Both. Uh, I mean, look, we we turn we we give you a license for, you know, however many users you you want. Um, and uh, um, we obviously track, you know, what's consumption of that license, what are people doing, how often do they access, um, the repository, how many searches they do and extractions they do, how many document sendings and ex- and document executions do they do. Um, and we keep a very close eye on on that as sort of fundamental health metrics.

Um, so I think product adoption leads to renewal and retention, right? And so, um, we we are very focused on that. Um, and, no, not everyone uses the AI features, but we're seeing really robust, um, usage. And, uh, you know, we're on s constantly looking for ways for more of the users discover what's possible. I mean, this is one of the endemic problems with enterprise software. You build this stuff, but how do people actually figure out what's possible?

And, you know, the good news is we have something that has a near universal value prop and can be deployed easily, and we can peep peep. There are all kinds of magic moments where, Oh, did you know you could do this? We're we're making that available. So, you know, as you send a document or as you sign a document, Hey, would you like a agreement summary? You'd like to know how this agreement pairs? Hey, did you know that we have all of them and you can see all this stuff?

Um, and that's, um, it's a new world. It's Yeah. I exciting.

do love that. The future of all software is some combination of, like, ultra smart, clippy and tooltips. It's it's if there's something there, someone should have a book

well, yeah. on it. All Hopefully, right, you're an we're providing more value than that. Yes.

Uh, you're an enterprise software CEO, you you've come, you've faced the gauntlet. So I'm gonna ask you the hardest question of all. You use your own tools. You started off by saying you use your own tools. What is your biggest frustration with DocuSign, and how would you fix it as a product, not I as a company?

don't I don't think I don't think our mobile experience, um, is good enough. I would expect that, um, everything should automatically flow, we should predict, um, the next steps. And, you know, it all works. Obviously, millions of people sign with DocuSign daily, so, uh, and often on their phones. Uh, but I think there's still some some room for improvement there, and so I'm pushing the team on that.

Well done. You you actually answered the question that most enterprise software CEOs don't, so I commend you for that. Alan, this has been great. Thank you so much for being on Decoder.

Thank you, Bill. I really appreciate you having me.

I'd like to thank Alan for taking the time to join Decoder today, and thank you for listening. I hope you enjoyed it. If you'd like to let us know what you thought about this episode, or really anything else, drop us a line. You can email us at decoder at the verge dot com. We really do read all the emails. You can also hit me up directly on Threads or Blue Sky. We're also on YouTube. You can watch full episodes at DecoderPod, and we have a TikTok and an Instagram.

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