So first, I'm gonna kick off with who this session is for. It's for the general audience member. It's not specifically for tech or legal people.And I will share more about why I've decided to to go that way, but I, I I I did decide to make this session more informational and more practical. So you can learn about how you can do that in your team or in your company without going into too many details. But to anyone who's interested, I will be posting in the next few days, and I'll try to share more information. So what will we cover today? We will talk about, I've prepared a few talking points because I can sometimes go off topic, but we will be talking about what is the history of legal technology and operations so far, what we have seen in the last decade, and what are there any problems currently in that sector and how, artificial intelligence and automation is helping, the sector evolve and how companies are benefiting from it.

So I'm gonna try and focus on these specific, points. And, again, do let me know what sector what part of the tech community you're, you're coming from so that I know whether I should customize this talk a little bit more or not. So as I said, I've prepared a few slides. They're just very simple. I wanna focus more on the discussion here about, contracts, and AI. I wanna focus on, if possible, if you leave any comments, I will be able to address them, and we can make it into more of a discussion. But let's start with what, where I started from. So, around three years ago, around COVID, companies I was working as a tech consultant, and a lot of companies were looking for ways to automate their contracts.

And they were looking for ways to specifically automate handling and managing contracts. And for me, it was a surprise because a few years ago, there were already a bunch of tools that were doing digital signatures that were automating how you draft and sign and agree with people remotely. So I was surprised that there are that many issues coming from from the sector. And I myself, my experience is in product and operations. So I have seen a lot of issues, but I haven't really seen all the all the reasons why this is happening before we started this research. So during COVID, there was, a lot of unrest, let's say, in the, in economical terms. There were, there was a lot of overhead and a lot of admin on handling contracts, especially in property and construction, where my team started research from.

But then later we found it in healthcare and in finance and in many other sectors. So what we have found kind of the culprit of, why there was so much admin and overhead in legal operations was static documents. And to anyone that has been to my profile or seeing what I talk about, I very often talk about static documents and why that really is an issue. So static documents sounds kind of like a marketing buzzword, but, it's really just the format of the documents that we use to conduct business on a day to day best, day to day basis. So this is your DOCX, your PDFs. Why that is a problem is as technology is developing and it's developing really, really fast, companies find themselves in a situation where majority of their ecosystem is digitally native and now, even AI native, you have AI sales agents and AI representatives and so on.

But the most critical part of your business is really, locked inside these passive documents, passive data containers. Right? So what we are seeing now, especially this year, companies that are looking into implementing the Gentec AI and LMS in their company and they're trying to automate processes and tasks, they're seeing that critical information is being locked in these documents and they uncover an unpleasant truth and this is that all of this has been kind of, focused entirely and it has been entirely dependent on big operations departments.

And this is what many have talked about in the last two years about de bloating the ecosystem. And, it's really not just about laying off, people. It it has to be focused around how these processes are handled. So when it comes to contracts, back on the main topic, because this is probably the most critical static document that is leading to stagnation and issues in the companies, why that leads to to issues and what kind of issues it leads to. So the static documents lead to a lost visibility. So what happens is even though there are many contract management tools out there and a lot of them are using AI, there is a lack of visibility. So these documents, they get signed whether it's DocuSign, Adobe Sign, whatever system for signing, and they get put in a drawer, which is not that different from how contracts have been handled, thirty, forty years ago.

Except now maybe we have a nicer, text editor, and we have shared cloud space instead of a wooden drawer. But it isn't really that much different. And to many of the companies that we speak, the contract stops existing once it's signed. Unless you're an operations or a project person and this contract kind of reappears four or five months down the line when you have some issues with a project, and you have to open and and spend hours trying to scout it for information. So this is where it leads to manual processes, because you're depending on people to track it and monitor it. And once a company starts scaling, people aren't enough to handle handle the volumes of data that has to get combed through. And then lastly, human errors and delays. This is probably the biggest issue and it's people focus on this a lot, but it's a product of the first two, items.

So we have seen crazy things over the last three years, researching how companies are handling this topic. We have seen companies losing millions, from very simple human errors, from, delays that are, seem kind of innocent, but then you find out that, have cost a lot to the company, both in competitiveness and, in revenue. So this is in three main reasons why static documents are are draining companies' profit margins, and are also leading to inefficient operations. And very often, especially if you research this topic, you will see a couple of figures. The reality, and based on our research for the last three years, we've done extensive research, It's very hard to get clean data figures and probably the most cited one, which you will see on also a lot of contract management software websites, you'll see these 9%, from the International Association for Contract Management.

So 9% of the annual revenue of, the company on average is being lost globally. This was a very big research and, it's very well conducted. It's interesting to see if you go into that research, it actually averages 9%. But for some bigger companies, it goes up to 15%, which is a very big percentage of revenue being lost due to contracting issues or contracting inefficiencies. And it's key here to say that contracting inefficiencies, when they quote this and when they did this research, they were focusing on what happens up to signing. So this is all of the issues that happen in the legal and the the sales department up to signing. But nobody talks about what happens after signing. And our research actually points to, even higher higher percentages of, loss and issues that occur in companies. Although it's very hard to track because it's spread across departments.

As I just said, for most companies, contracts stop existing once they're signed, and then usually months or years later, they are recovered usually in the case of issues. Two other figures that are also very, in line with what we have been researching is the loss of efficiency and profitability. They are all interconnected, and especially the efficiency percentage. Indeed, companies that have been implementing automation, to a certain degree when it comes to handling contracts, have vastly better efficiency indexes compared to those who have not. And I'm gonna give a few examples. I think on this next slide, I have put in some examples from our experience because perhaps on the next because I think these examples are great to, explain exactly what, static documents and static contracts leads to.

So we've had a pharma company, a very big pharma company lose over £4,000,000 on a contract, due to lack of oversight. Now without going into too much detail, they found out that this actually happened five times and they found it as they were closing the year in one of their departments. And there was slight difference in the P and L than what was projected, and that's how they uncovered it. It was a year later, and because of the scale of things, it's very hard to, track and see these problems. And once you see these problems, you might, label them as a people issue or a team issue. But in reality, the problem comes from the fact that there's a vast amount of contracts, especially in pharma and big pharma law, a big volume of contracts that is being signed with very dynamic clauses for, to anyone who's handled these kinds of contracts.

It's time and material contracts that have, fluctuating scope. So every month this has to get monitored and there are very specific requirements set and SLAs set in the contract. So you end up with a very big administrative overhead handling that's very often leading to issues, delays and errors. Then we've had in construction, one of the biggest companies in construction. Globally, they they had 25% of their workforce spent on validating paperwork. And then a property maintenance company in Finland, they had, 4,000 board meetings annually. All of these contracts, all of these documents required manual, handling. And so this is just a bit to say about what the problem really is. I've spoken about this in a lot of different, audiences with legal, and with tech. And it's very funny and with business people. It's really funny because legal people, they're very interested.

And for the past two years, there's been a lot of, development in this area. So you will see, for example, Yale, Harvard, universities, they have already, I think, for the from the last five years, they have already programs, specifically, focused on AI, and legal technology. So the first people who are, for example, legal engineers, are coming onto the market now. So legal people, they're very interested in this topic. And a few years ago when we were speaking about how we can use AI and automation to handle contracts, they were they were very interested in in this, but to them it seemed like a far away, idea and it was very scary to experiment with technology. And to this day, we work with a lot of law firms and, for them it's both frightening from the point of view of what is going to happen to their industry. And as at the same time, it's a scary concept to handle if you're not very technically native.

And so for tech people, they're very interested in the tech aspect of automation and how they can automate documents, but they don't wanna get close to legal. So very often we would see, tech companies unsure how to approach this. And then business people, they're the ones who actually get affected by it at the end. And here I'm referring mostly to operations people, project managers, account managers, and even finance department as well. They get practically most impacted by this issue. But for them, it's still unknown where this issue comes from. And and when you look at those three issues separately, you might not consider that that the one the one culprit would be the static documents. So you might think it's different, aspects of it. You might look for different solutions. So I think this is probably the most important thing I wanted to share today.

We've spoken with dozens dozens of companies and law firms and over the past three years and, I think this is the most important thing. If companies can look into how they can, digitalize and automate this aspect of their business, they're going to be very well ahead of their competition. And because I spoke a lot about, the problem, I would like to switch to how you can, how you can, solve this issue. There are many ways to, many ways to approach this. And I'm gonna talk about many different solutions. So, before I jump into the many different solutions that you can look into, I think it's very important to say that a few years ago, 2010, 2012, up to 2015 maybe, blockchain was, the industry that brought the biggest revolution to this sector. So even though blockchain is, not widely used and companies are not really very accepting of blockchain, it is important to note that this, part of the tech world is what brought living contracts nowadays.

So to anyone who doesn't know, in Blockchain, there's this term smart contracts, very popular. It essentially is a piece of code, not a type of contract in the form of a document, but rather mostly usually just code, representing an agreement between two parties that gets executed very often based on conditional logic. We my team has worked a lot with smart contracts and blockchain. They're very interesting and they solve a lot of problems but unfortunately a lot of the corporate world cannot adopt blockchain solutions for various reasons whether it's security, whether it's a regulatory reason and so on. But what happened with smart contracts and blockchain is very interesting because this is what brought us, to think about what if contracts could think, what if they could reason, what if they can adapt, so that they are able to actually execute this. So if we go back here to the previous slide, I think it was this one. We asked ourselves this question and we started researching different technologies.

I will mention a few of them, but, right now I can say some of the open source one. For example, Accord project is very popular. It is very easy to set up. If you're technically native and you are able to experiment with it, Accord project is a great way to test and see, how you can automate contracts. And there are many other tools. So we asked ourselves what would that contract be? What would that document look like if it could run itself? And below you can see a few main things that we found after our research. After we created a few prototypes and did many workshops, we found and these are kind of conservative figures.

We found that a document that can have embedded logic into it, can execute a lot of the tasks that we're currently handling for contracts. And that when I mention tasks, I don't mean auto renewals because this is a very obvious one. And I don't mean informing the parties that signatures have been collected. What I mean by that is reading the terms in the contract. So the natural language, the human text, analyzing it, creating objects and logic behind it. So a whole new layer to that document, which I I like to I like to say to non tech people that it's like a digital layer to your human text. And to tech people, this is, objects that are translated from your natural language, that can execute this text that you have written out. So for example, if rent is five days late, you can apply a 5% fee, notify the tenant, collect the payment.

If it is not collected, you can issue a late fee and you can contact the tenant automatically and so on and so forth. And this could be amplified in scale. So for example, farm industry, it's a very complex industry and you have very complex milestone based or time and material based contracts there. When it comes to when we are talking about execution, we are referring to how are you calculating the work that is being delivered every month? How are you comparing it to the terms that have been originally agreed automatically? How can you assess, if certain, conditions have been met so that you can actually, issue, for example, a report that says that this month has been completed for agreement, and so payment is actually due and also calculating how much that payment should be.

So all of this that is currently being done by people and that is leading to these, quite literally million, pound issues. So one is the faster execution and this is great. The other thing is 45% less admin. This is what we have found on average. And I'm making, a point here that in some industries like the insurance industry, our workshops point to up to 70% of automation of administrative, tasks. And this is on top of, the fact that these companies are already using some sort of technology, obviously, for example, in insurance for processing claims. But the amount of admin that it takes back and forth between different parties, whether it's via email, whether whether it's comparing different versions of a contract or terms that have been agreed when you're renegotiating, This is the amount of admin and the sense of admin that we're discussing.

And then two main things that we have found that instantly boosted, and changed how, let's say, contract or legal operations, have been performing is, first of all, real time tracking. And this is the most important one of events and milestones. This is the whole reason why the document itself should have that digital layer on it or in technical terms, these objects and events so that the contract itself can monitor and track whether these things have been, actually reached. And then payments and invoicing, mainly because it's the main part of most contracts. They're based on, conditional payments and this is what most people are tracking. So what we do and what we have found is if we can also make adaptive actions and those actions being issuing payments, collecting, creating invoices, draft invoices and official invoices and organizing the numbering. This is the sort of admin, and overhead that we can and not overhead only because it's a main part of the operations of the business that we can automate.

So these four things that we have found that could fundamentally change if you can use programmatic contracts. I am making a side note here because I realized maybe not a lot of people know or have heard the terminology programmatic contracts. This is a term that we, coined we put for these, contracts that we're referring to because three years ago when we started working in this sector, smart contracts were different thing. They still are very different. And the easiest way to explain to people what these contracts are are programmable automated contracts, which kind of blended into programmatic contracts. Not to be confused with programmatic and advertisement, but, this is just an FYI. So, so we we found that we can do this with these sorts of contracts. Now we used a lot of prototypes and we used a lot of, shortcuts to get to this, because technology was still very much developing.

Some of the things that we can do today were not possible six months ago or even twelve months ago. So I do have to make a point about, about this. Technology has vastly developed and this leads me to the next point of how you can implement it in various different ways that don't necessarily mean using a platform. Because, I as I said, I've spoken on a lot of events and very often people who are interested, they they wonder how they can do it without trying the whole platform. Maybe they work in a big company. They want to trial it with something smaller. They don't wanna commit to a whole platform, and there are ways to do that. So the path to automation and implementing AI when it comes to legal, in a safe way. So there are made a few main components.

I I believe some of them I have already covered. On the one hand, you have the human text. This is your legal templates that your in house or, external legal team has created for you. So these are preapproved clauses. You can even, fragment them in objects and clauses. This is your legal text. Then you have your data pool. This is your ERP, CRM, depending on the structure of your company. What we have found, maybe not so surprisingly, even in, financial industry, many big companies are relying still on Excel tables. So if this is your data pool, it needs to be a clean Excel table table and it needs to be, labeled and categorized.

This is kind of the main problem of implementing AI. So you need this data pool whether it's it could be just a HubSpot or a Salesforce software as well. And then the third thing is the AI, the model that you're going to use to automate this, this legal work. And you could use, and everyone is talking about agentic AI. You could use AI agents, but you do need an environment where all these three elements can combine and you do need to train that model for yourself. So this falls under the DIY method and I would say this is very much appropriate for enterprises. Let me see how much time I have. Okay. I have to speed up a little bit. The DIY method is very much appropriate for enterprises.

You could use, an AI model that you can extend and you can train on your data locally. You can create, clause library and you can create a sort of dictionary to what, each of those clauses and elements in your contract refers to. And then it's very easy to use this sort of dictionary to train the model so that every time you sign a contract, it knows that this label of this field is connected to a certain type of automation. Now this DIY method does include, you having in house tech people. So it's either gonna be engineers or really tech savvy people that can combine, technologies. So you need the AI model, you need, API setup, you need an environment, and probably you need some form of tool like Zapier to connect to your different systems. So this is, again, custom coded rules, a lot of internal effort.

It's more flexible, but it requires a lot of upkeep, and anyone who's ever gotten a legacy project would know that this is not necessarily the easiest way. I know the CEO of Klarna, went public this year, I believe, or it was end of last year and said, that, SaaS business models are dead and that, companies should develop everything in house. And as a person who's worked on a lot of in house projects, I can say I am not too confident in this, but if you choose to go that way, there are many, options as the ones that I quoted. And again, another note for a card project. And then there are platforms that are more suitable for SMBs, and more suitable for testing because the d I one one is resource intensive. So So platforms. You have many different platforms that you can use. If you have an in house legal, you can look at platforms like Harvey, like, Ironclad. They're great.

They have very sophisticated, trained AI models, that can help your legal teams, construct these agreements. I'm not sure how much they cover post signing automation. I know they cover to a certain extent. I'm not sure how much they go into operations. Then for very, small teams and maybe even solo entrepreneurs, I'm not sure if there are any of those among you guys. I would say Juro, Pentadog, there are these platforms very easy to onboard yourself onto. The unfortunate thing here is that these documents here do remain static. It's the same thing with DocuSign. I believe they have now extended beyond just signatures and they offer a sort of management of those documents, but it's still, PDFs and DOCX.

So you are as flexible as the platform allows you to really. And these platforms, what they have is they have pre built logic, so usually in the forms of workflows, that they have pre built for you. It's a UI based configuration, so it's a bit easier. They're tested, mostly and you can check and you can verify what their existing customers that they are being used. So it's easier sell to your legal teams or decision makers, whoever it is in your company that makes that decision. Our platform, just a side note, falls under the platform, section. We do focus on drafting signing, but specifically post signing automation. And we do create these sort of these agreements that I am referring to right now that are part text, part code, and it's entirely customizable.

At this point, we are, just about to release a demo version where you can create these on the go entirely from scratch. Right now, we are working with components in our platform. And the goal at the end, whether you're going with DIY or platforms, is to turn your contracts into active systems. This is very important if you want your company to, really be able to move with the, this AI flow or with this AI, let's say, evolution. Because as long as your main critical documents and deals are, are locked in these PDFs and docs, it's very hard to let AI penetrate, connect, and speak to your to this information so that it can actually create living workflows. You will always be dependent on people And, I, I can talk a lot about this, but maybe we should move into, why that matters in the in the on the high level.

I've mentioned different industry. I've mentioned different companies and what they do, and what you can do as well and what, methods you can use to get there. But most importantly, I wanna say beyond getting faster execution, less admin, having your people do a little bit more than emailing about documents and following red lines and, in my personal opinion, very wasteful resources. Beyond that, there's a new era of companies that are coming and we are seeing this trend for the past maybe a year, year and a half. More and more people, solo entrepreneurs, small teams are creating technology because it's becoming easier and easier to create and deploy technology, production ready technology. But one aspect of the sector that remains very stagnant is this legal and operations sector. And this is the reason why a lot of these companies are still not scaling at the level that they should be.

But what we will see in the next few years is there's gonna be a sort of democratization of how this happens, and you're we're gonna see a lot more companies being able to implement these sorts of, automations in the admin and operations sector, which will significantly lower their cost of production.

And why this matters for you is whoever you are, whatever company you work in, the cost of services is gonna go really low. It's going to be much easier, for new companies to come in and be more competitive, compared to you. A lot of the bloating comes from operations department. It doesn't necessarily come from R and D always. So if you do want to stay competitive, if you do if you do want to do more meaningful work, especially if you're in the sectors that are dealing with this, I strongly encourage you to look into ways to, to automate some aspects of this. It can be very small and you can grow it, in time, or you can start with a platform. You can start with one team, of your company and continue expanding if you see that, the return on investment is good enough.