Name: Your Ultimate Guide to the ServiceNow Now Assist AI Platform
Uploaded: 2025-09-18T16:30:19.451Z
Duration: 54 min 36 s
Description: Your Ultimate Guide to the ServiceNow Now Assist AI Platform

Transcript for "Your Ultimate Guide to the ServiceNow Now Assist AI Platform": Hello, everyone, and welcome to our very first NowThen webinar. So thank you very much for signing up and being with us today. We'll get started in just a few minutes or a minute or so just as people come in. Let us know where you're dialing in from today in the chat. Let's see different cities and countries we've got representative. Also, gonna be having a q and a with our superstar guest speaker. So, if you do have any questions throughout the webinar, then, please drop them in the q and a box. You can see them next to the chat. Good evening from London. I'm from London as well. There we go. London in the house. Cool. Alright. Well, I'll start to kick off, London as well. There we go. We just have people from London today. Yeah. So, thank you very much for being here again. This is the first webinar we're we're doing, as now then. And just to give you a bit of background on myself, so my name is Benjamin McCarthy, and I've been working in the Salesforce ecosystem for the past thirteen years. And, I founded a company called SalesforceBen, which is one of the largest media companies just reporting on Salesforce. And, you know, we've we've we've been kinda monitoring the the tech ecosystem and seeing, you know, where the hotspots are. And ServiceNow is something that we've been watching for a very long time, and we also seen the quite quite a lot of my people that have kind of switched from the Salesforce ecosystem to the ServiceNow ecosystem. So we're like, oh, okay. What's happening here? And we're really excited by the ServiceNow ecosystem, all the innovation on the platform, the direction that it's going in, the growth. And so, really, we want to do the exact same thing we've done at Salesforce Ben, which is to support the ServiceNow ecosystem with great content, great journalism content telling you what's going in, a kind of higher level, you know, acquisitions ServiceNow are making, the direction of the business, but then also diving into the technical aspect as well. So understanding from the thought leaders in the ServiceNow community, about, you know, best practices and tips and and how ultimately you can advance your career on the ServiceNow platform. So, we have been launched for a few months now. We have a newsletter, which you can sign up to on the site. We're also publishing about three articles a week on the on the website. We have a lot coming as well. So we're gonna be doing a lot more of these webinars, and also hosting, happy hours around the world. We have one coming up in London, which I'll speak a bit more about later on. So, yeah, that is the introduction. So and today, we're gonna we have a fantastic guest speaker who I'm gonna do in a minute, and we're gonna be speaking about everything that you need to know about the ServiceNow, NowAssist AI platform, which is, of course, extremely relevant. So, welcoming to the stage Amit, who is a five times sales a ServiceNow MVP and certified technical architects as well. Hi, Ben. How are you doing? It's nice to see you here. Yeah. You too. And thank you so much for joining us today. Really looking forward to see see all the insights you've got to share with us. Yep. Cool. Just before we get started, me and Anna are gonna have a little bit of a chat about the the ServiceNow ecosystem. So I mean, first off, Anna, please please if you could introduce yourself, that'd be great. Yes. I'm Amit Gujarathi. I have around eleven plus years of experience to service my ecosystem. I'm a certified technical architect and few times MVP. So currently working in Globant as a solution architect. Okay? And really excited for this session. Thank you. Great. Thank you so much, Anna. So give us a bit more information about about your kind of background and your history of ServiceNow because you've obviously been in the ecosystem for over a decade now. What initially drew you to the platform? And also, what what keeps you sticking around? Like, what are you excited for about future? Yeah. Oh, that's a wonderful question. Actually, I started my career as a Java developer, and what drew me to ServiceNow was how quickly I could build and deliver real business value without getting lost into complexity. Right? Over the year, what's kept me excited is the cost and innovation, especially how ServiceNow grows, okay, and evolve into IT workspace workspace to enterprise. Okay. Why transformation? So, honestly, I it still feels feels fresh. Okay? Because every project brings a new challenge and a new opportunity to make a impact. Yeah. Fantastic. And I think our innovation is just gonna accelerate with with AI as well. So we're definitely heading for a bit of a exciting time. And, you know, over the course of, your your kind of decade plus working with ServiceNow ecosystem, what's the biggest change that you've noticed in in all those years? I'd say the biggest shift, has been how ServiceNow has moved from the IT centric platform to becoming a true enterprise transform transformation engine. Right? In the last few years, we have seen AI automation, employees employee experience, okay, has taken the stage the center of the stage. Okay? Honestly speaking, what excites me more is how organization now sees ServiceNow, not just like a tool, but as a driver for end to end digital transformation. Yeah. No. Definitely. It's it's kind of very well placed in in the market for that. And there there's a lot of, hype around AI now, of course, but, you know, and and I'm sure you're gonna go into the part of your presentation. But, you know, how what what would your advice to be people in the audience where, you know, to cut through the noise? Because we're getting so much information about, you know, AI at the moment. You know, what what should people really be focusing on to drive real value? Yeah. It's a great point because AI is everywhere right now. Okay? I'd say the key to start, with a clear use case that solves a real business problem instead of chasing shiny tools because there are a lot of things out the market. And if you start chasing each and everything, it will be mess. Focus on measurable outcome, like faster reservation time, better employee experience, or cost saving. So that will be the initial step for any business to grow in this area. Yeah. Definitely. It's it's always a good reminder not to focus on kind of the fun, shiny objects, but the ones that actually drive the business KPIs that we're that we're all here for. So Yep. Yeah. Completely agree. And, you know, we we see this across the core kind of all technology ecosystems, but a lot of companies struggle not necessarily with the tech, but with the adoption. And, you know, we're I think, I don't know if you saw the statistic, but there was a a kind of report done where 35 to 40,000,000,000 has been spent on generative AI projects so far, but only, 5% of them succeeding actually in being adopted. So, what's your advice for IT leaders when they're trying to get teams on board with AI driven workflows? That's a very real challenge. We are facing it day in and day out. Okay? So my advice would be to start small, become a workflow that touches work people daily pinpoints, okay, and show quick wins. Once team sees AI helping them to to reduce time or to reduce the repetitive work, adoption grows naturally. Okay? And, honestly, involving user early listening to feedback and keep things simple makes all the difference. Yep. I completely agree. And, you know, based on everything you've seen from ServiceNow over the past, you know, year, couple of years with AI, what ITSM, use case for AI do you think is, you know, the most impactful? I I feel most of the use cases are creating an impact in the ecosystem, but the features like, chat summary. Okay. Because we have seen it in action that it's reducing the agent, the amount of time agent spends on reading through a entire chat. Okay? There's kind of relation out there. So yeah. Yep. Yeah. No. Definitely. I think there's there's just so many which, which can be quite impactful. And if if you look at the AI landscape in ServiceNow today, you know, obviously, we're still in the early innings, but where do you see this going? You know, where do you think we'll be in a couple of years' time in 2027 with with AI and ServiceNow? Honestly, what excites me is how AI will move from being a helpful assistant to becoming a two DCM making partner. Right? Today, it speeds up task of task and guide agents. But by in few years, I see it predict it will be predicting needs. Okay? Orchestrating workflow across system and almost disappearing into the background as the way we work. Right? Okay? It will be the part of our day to day activity. People will not treat AI as it's something something miraculous. Right? So that's how I feel. So it's how we'll grow in this area. Yeah. Definitely. I think at the moment, it's very we're very kind of conscious of using AI, but I think it's definitely gonna seep so much into the workflow that it's just it's just there kind of, you know, a bit like Jarvis, I guess, from from Marvel films. And, you know, a question just based on, careers now, but you've mentored a lot of professionals over your careers. What skills do you think will make ServiceNow architects and developers indispensable in the AI era? That's a fantastic question. Okay? And we are also trying to find the answer for it, every day. Okay? But I would say two two two things stand out. Okay? First, a strong grasp on core platform fundamentals. Because if you are, how if if your core platform fundamentals are clear, okay, no one can replace you out. Not even AI. Okay? Because AI is only as good as the data and the process it sights on. Okay? The second thing, is the ability to think beyond coding. Okay? You have to leave the developer mindset now. Okay? Skill like problem cell solving, design thinking, and understanding business context, will will play the role in the future. Okay? We should not focus just we should not be a keyboard person. Okay? Just putting our hands on keyboard whenever we get the requirement, but we should be a part of statistics now. Okay? Strategies, how how, organization can be driven through the strategies. And, playing some functional roles, will will add a value to your profile. Yeah. Alright. Fantastic. I think some of the best developers I've worked with are the ones that kind of question me and go, why are you doing that? Because that's silly. This is what I would suggest instead. So yeah. Completely agree there. Fantastic. Well, thank you for the chat, Amit. I hope everyone found that useful. I'll hand over you now to take us through the the core of the presentation, which is the overview of the ServiceNow Now Assist AI platform. So I will hand over to you and come back at the end, for the q and a. So if anyone does have any questions, please put them in the q and a box, and I'll be in there. Thanks. Thanks, Benjamin. I'll start sharing my screen. Please just give me the confirmation if you are able to see my screen. I I hope it's feasible now. Yep. Okay. Perfect. Thanks thanks for the confirmation. So welcome to today's now web now when webinar. Okay? I'm excited to have you here as we spend the next half an hour exploring how ServiceNow Nowasys is reshaping business with the power of AI driven automation. You will discover what Nowasys really is, the value it delivers, key features in action, and a clear roadmap to put AI to work for measurable result. We have got a packed agenda. Okay? And your questions are always welcome. Okay? So stick around. The live q and a will be at the end. Okay? So let's dive in and get started. So as I mentioned earlier, now this will be the agenda for today. We'll be looking at the we will try to understand what now assist is. We'll look at the key trends. Okay. How we can we'll also look into the use cases and best practices and takeaways at the end. So I will I will skip the agenda, and let's start with some compiling data from ServiceNow enterprise AI maturity index 02/2024. The research shows a clear divide between organization that are moving quickly on AI versus those that are still hesitating. First, most those company that have impressed AI early, okay, are significantly outperforming other across five critical dimension. They are noticeably above in workflow, ahead in strategy and talent management, slightly ahead in investment, and above in governance. Meanwhile, organization that are waiting are falling behind across all these areas. The message is clear at this particular point of time. The time to act on AI is now. Those who move first are creating sustainable competitive advantage that will be difficult for us to catch up in the future. Here's the fundamental truth about any AI implementation. AI is only as intelligent as the platform it's built on. You can have the most sophisticated AI model in the world, but if they are not connected to the right data, workflow, and automation capabilities, they will remain isolated experiment rather than an business transformation tool. ServiceNow combines AI with a powerful automation platform, creating an infinite loop of intelligence and action. This isn't just about getting smart insights. It's about turning those insight into immediate automated business outcome across your entire organization. So let me show you what AI powered business transformation look likes in practice. Okay? So just this is just an overview just to, get some insight on that particular front. So ServiceNow, it now assist can generate code to identify inactive user who aren't locked out. That's a developer productivity in action. Right? It can instantly answer policy questions like, can I bring my doc to my work? Okay? With accurate source response from the HR policies. It generate comprehensive solution and resolution note for resolved cases and provide intelligent some case summarization that capture the essence of complex issue. This isn't futuristic AI. This is AI working today, embedded in real workflow, delivering faster resolution, better employee experience, and reducing the manual work that box down the team. What makes ServiceNow fundamentally different is ServiceNow unique combination of three critical elements, data, AI, and automation. All unifies on the single platform. Most organizations struggle with AI because this element exist, but they exist in silos. ServiceNow bring them together so that every interaction from employee sales service to complex backs of operation to the developer development things becomes smarter, faster, and more efficient. This integration is what transform AI from a cool demo into a genuine business transformation. Let's start with data. So as I discussed earlier, there are three entities. Okay? So we'll be looking into each entity and so that you will get more insights on that particular front. So let's start with data. So is ServiceNow AI driven platform helps organizations streamline operation, boosting both efficiency and productivity. What makes the diff what makes the ServiceNow platform unique is its ability to bring together data, AI, and analytics into organized workflow. It's simply by complex process, deliver personalized and contextless experience, and is designed with a user first approach. You can integrate a number of application. Okay? We have capabilities like workflow data fabric through which you can integrate with SAP, DocuSign, Oracle. You name it, and you can integrate it and bring it bring the data to the platform. The platform is also built to handle large scale operation with speed backed by capability across ITSM, CSM, HRSD, service catalog, and knowledge management. All of this is power powered back by industry leaders on AI front like Nvidia, AI stack, ensuring world class performance. This is a core of ServiceNow AI strategy, bringing data, AI, and automation together to transform how works get done. ServiceNow offers you the best of both worlds when it comes to AI models. For out of the box experience, ServiceNow l m service LMM service provides domain expertise for high model accuracy, faster response time, cost effectiveness, and sustainability. So we now partner with industry leaders like Nvidia, Hugging Space, and IBM to deliver this optimized experience. For customer experience, you can bring your own LLM or you can bring your own JNEI models from other providers like OpenAI, Microsoft, Google Cloud. You can you can you can build your own LLM also. We are doing that particular thing in a project. Okay? And you can integrate with that also, giving you support for external models with the flexibility and broad use case support. This dual approach ensures you get the right AI solution for your specific need and risk tolerance. Now assist transform four critical areas of your business. First, it transforms self-service by giving customers and employees quick personalized help through smart conversational AI. Second, it unlocks productivity and efficiency by letting AI extend handle time consuming repeated task. And it integrates seamlessly with, with entities like, Slack, Microsoft Copilot, and so on. Third, it boosts it boosts developer productivity and creativity by reducing IT backlogs and helping teams create and configure workflows and build custom application faster. Fourth, it accelerate time to value with prebuilt AI powered workflow running on the world's leading automation platform. So there are tons of workflow service now already created. Okay. You can just, you can just tweak it out, okay, and put it to your system without any efforts. Whether you are just starting out, your AI journey or refining your strategy, ServiceNow helps you accelerate success. With Now assist, organization can easily acquire, configure, and deploy capabilities tailored to your business need in just three simple steps. You have to just install the NowAssist, configure it out to your needs, and deploy in workflow. That's it. Pretty straightforward. Now, ServiceNow ensures a fast path to value, delivering result not in month or weeks, but in days while maintaining the highest standard of security, privacy, and compliance. Customer already using ServiceNow analysis are seeing impressive result, including double digit productivity gain and up to 85% issue resolution rate. This showcase the true power of ServiceNow AI in driving that real business outcomes. Isn't it amazing? It's it's quite big. Trust now now this is the most important slide of all. Okay? Because it talks about trust, and no one trust AI at this particular point of time. So trust is the core of enterprise AI adoption. And ServiceNow build it into every part of Now Assist. ServiceNow follows responsible AI principles that are human centered, inclusive, transparent, and accountable. The platform provides building security and governance within domain specific model designed for ServiceNow use cases, ensuring the outputs are relevant, contextual, and trusted. Filter data to maintain accuracy and reliability in generated response. Gen AI governance approval workflow is there. Okay? That keep organization in control. And at on top, it's like carry on the key. A Gen AI admin control center for complete oversights. So this isn't an AI just like any other AI engines, okay, which is working in black box. This is an AI you can audit, control, and trust with with most of your business critical business processes. ServiceNow has put all kind of security guide rails, okay, which will help you out to safeguard your data. Now as it delivers better self-service, improved agent productivity, and higher developer and admin productivity across four key business areas, in app delivery and automation, information technology, customer service, and human resource. Now this raises the bar for user experience and operational efficiency. The beauty of the ServiceNow platform is that the same capability shows up everywhere of wherever your people works, creating a consistency and compound value across the entire organization. In today's presentation, it's difficult to cover everything ServiceNow is to do, so we'll be focusing on a couple of use cases which have with respect to ITSM. Okay? And developers specific use case definitely will go because we are from a developer background. So let's look at the challenges. Okay? So when we look at the traditional IT service management workflow, several challenges become clear. This is a day to day issue which a lot of organization who have not opted for here are facing. So the one major issue is with the self-service solution is that the necessary content often doesn't exist or isn't in isn't sufficient. This make employee bypass the virtual agent and go directly to the live agent. Once the handoff happens, the live agent must review the entire chat history. For instance, a person has done the chat for around 100 messages. Right? They have to read through entire messages to get the context of the chat. A time consuming process. Right? Under pressure, many agents simply ask the employer to repeat the issue, which leads to employee frustration. Next, the search bar also becomes becomes another roadblock. Documentation is often incomplete or outdated, leaving agents empty handed. At that point, ticket gets escalated to the level two agent, which increases the cost, but the transfer is still rarely smooth as details aren't properly documented for the next digit also. Even when a level two agent resolve the issue, documentation is minimal with notes like done or resolved. That's it. Okay? This leaves no usable information for knowledge based writers and prevent future incident from being avoided. The result in sufficient inefficient workflow, higher cost, employee frustration, and missed opportunity to build long lasting knowledge articles. Now let's look at how this problem is addressed with our system. When a virtual agent can't solve the issue and it's handled to an agent, the agent no longer has to scroll through the entire chat history. Instead, chat summarization provide a clear concise summary of the problem. Removing emotion and focusing only on the facts is the most important thing. This allows the agent to quickly understand the issue and either resolve it themselves or seek additional insight. If the ticket needs to be escalated, now I should make the handle hand off seamless. The summary includes the virtual agent conversation, the live agent discussion, and all the work notes so the level two agent receives complete context. When the level two agent resolve the issue, now it's a general meaningful resolution notes. Far more valuable than just done or resolved statements. Right? Agent can enhance these notes with additional comments or simply accept what's generated. This resolution notes then feed into knowledge base article, making them available for future cases. This creates a powerful cycle. The next time a similar case or case or issue arises, the virtual agent may result it directly using the newly created knowledge article, avoiding the need to log an incident at all. The results are clear. Employee solves problem faster with self-service. Agents save time and boost productivity with accurate insight at their fingertips. Organization benefit from continuous knowledge, growth, and process efficiency. Now let's explore this capability in more detail. Now is it for ITSM delivers value to three key constituencies. For employee, it increases the supply of self-service content and make it more engaging through intelligent conversion interaction. For agent, it helps them process information faster and document pertinent information automatically, reducing manual work and improving consistency. For admin, the value is immediate. You can gain value from analysis from the minute you install, not even months. There's no lengthy implementation cycle or complex configuration required. So we'll be looking into all these three profile one by one. So, let's start with the AI search engine. Let's start with the employee profile and the first feature which we want to see is AI search engine. So what is AI search engine? AI search engine is a system wide search simplified. A user can ask what is my tuition reimbursement policy? And Q and A, ASR scans the system. Maybe a single or multiple loyal critical. It needs to scan to find the relevant information. It will not dump that information as is. It will synthesize, and it will combine and contain information so that the user get only what is needed. Even if the original article is of 100 of pages. Okay? It will just find the relevant information to that user. Transparent sourcing. Every answer included a clickable citation that showed the source and where a specific data point came from. So user can verify the basis of the response and avoid AI hallucination because AI hallucination is also one of the key factor when deciding on the which AI practice we have to follow. Faster trusted outcome. The result is quick access to accurate answer and greater confidence in the information provided. The next feature is AS search in virtual agent, which provides natural language q and a powered by knowledge articles with incredibly quick time to value. You can have this running in just fifteen minutes. Trust me. It includes the ability to build and use LLMs tailored to your specific content and context. As shown in the example, when an employee asked, can I book my Airbnb instead of a hotel work trip? Now as I provide a clear policy based ex answer, explain the vacation rentals like Airbnb are not reimbursed from business travel, and they have to raise a request for hotel within a Concord Travel app with the proper source attribution to the domestic travel policy. Isn't it amazing? Right? You don't have to search for things all over the place. The third thing is catalog search. Honestly, when we talk about catalog search, I feel it's the most difficult part of it is to search where that catalog resides. Okay? So the catalog search can now be directly can be done directly in the virtual agent. Instead of navigating through service portal or workspace to find the right catalog item, user can simply state what they want to to do in natural language. For example, a user may ask that he has completed job basic courses recently. Okay? And they want to submit a request for tuition reimbursement for tuition expense. The virtual agent understand the intent, ask the follow-up question in a conversational way, and map the detail to the right catalog item. User can either provide information step by step or submit everything in a single statement. The AM order interprets the request, break it into catalog fields, and submit it automatically, making the process fast, smooth, and human like. Now let's look at the agent profile, what we have for agent with respect to our system. So first and foremost thing and everyone's favorite, chat summarization. Chat summarization provide human like synthesis of context and past troubleshooting, creating continuity between virtual agent and live agent interaction. This help agent seamlessly continue from where the conversation left last left off, reducing the meantime to resolve and improve the overall agent experience. As shown in the example, when Abel tutor joins the chat, you can see on the screen. Okay? He immediately sees a comprehensive summary that Jade keep Cooper can't access her work emails or whatever, issue she is having. Okay? Recommended with the following instruction on KB articles. So the agent this context allows the agent to jump right jump right into problem solving without having to regather the information from the from from Jane Cooper. The the next feature this is also pretty nice feature, which is incidental case summarization. Incident case summarization simplifies everything, cutting straight into the heart of the issue. It quickly highlights what the user needs, what needs to be done so what has been done so far, and delivers it in a sharp snap to the agent. Plus, it's got smarter twist. If, if a person if if your employee is speaking some other language, okay, which is not matching to your tone, okay, You have dynamic language translation also in place. Okay? If the user speaks a different language than the agent, it seamlessly bridge the gap with the real time translation. But that's not all. You cannot take it up to a notch by adding a custom field to the summary. So you don't have to use the ServiceNow provided agent as is. By default, the summaries can pull pull pull from some specific columns. Right? Example, short description description. But with the latest analysis release, you are in control. Want to include select column, want to include, category. You you can include it into the agent and done. Need to create a brand new skill with a custom dataset to to manage certain things out? Completely possible. Okay? It's all about flexibility and making it work your way. The next thing is the resolution note generation. It's a it's it's it's really a save for a lot of organization, I can see. Resolution note generation takes the hassle out of documentation by auto generating resolution note codes and notes when incidents are resolved. It enforces the best practices with automatic field update, hosting agent productivity and streamlining their experience. No more write manual write ups. Just consistent detailed documentation delivered effortlessly. Okay? This is kind of problem statement which we have seen when we did the audit for lot of organization. We found that the incident got resolved, but, if you see at the resolution note, it's somewhere kind of funny. Right? It's done, resolved, get the thing done kind of things. So this help on that particular path. The next is I think I think this is this will be a favorite for most of the organization. Agents can now turn insights into action by creating a knowledge article directly from the instrument screen. This makes the solution instantly accessible to everyone, eliminating the need for future instrument submission. With knowledge and vision, it automatically drops and recommend articles for review, making sales service solution widely available. This not only deflect future incident, but also boost system of time. Every resolution become a reusable resource, empowering users to resolve to solve similar issues on their own. Efforts effortlessly scaling support like never before. We have seen organization who who have they were not having any knowledge bases in place, but now they have knowledge base for most of the things, okay, for all the recurring incident. It's it's pretty amazing. Now our favorite our post of favorite because I come from a developer background. Okay? What we have for admins. Right? For administrator, now assist provides immediate value that can be realized in minutes, not even months. Admin gains the ability to configure and control how AI operates within their own environment, ensuring consistency and governance while maximizing the value delivered to both employees and agents. The last person in our slide, okay, which is where we see additional use case like prompt management. This is the first use case. Now for those of you who have used things, I think most of you have used things like chat GPT or other LLM. You would realize the quality of your output that you get from the LLM tool is directly a factor of how well the prompt is written. This is where ServiceNow has done a lot in terms of prebuilding, pretraining, preconfiguring the prompt, and the skill that you need, out of the prompt. That's it. Sometimes, there are requirements where you may want to tailor the this the prompt. Okay? You want to create certain prompt or you want to just update the prompt, what the agent or skills are having out of the box. Okay? It's basically easy with the feature like prompt generation. You just have to give the natural language input. Okay? Whatever units we've done from that particular skill or from that particular now agent, and the prompt generation tool will generate the proper prompt for you. Isn't it amazing? Because prompt is the heart for any AI capability out there. Next, code generation. A lot of people will be excited about this. Code generation takes scripting to the next level. Whether you whether you are a power user, admin, or developer, you no longer need to dig through documentation or worry about inconsistent coding style. With text to code, simply describe your intent, and the system generates complete standardized script for you, identifying the right table, columns, and function. It save times, ensure consistency, and streamline the entire development process. As you can see on the screen, we have just given the prompt what you can see on the green line. Right? Get a list of incident created in the year 2023 by user. This is this. And that's it. You can simply put your business statement or or story itself, okay, in some cases. Okay? And ServiceNow will take care of the entire scripting. You don't have to worry which particular table you have to look into. You don't have to worry which columns it should target and all those things out. So it's not it take care on its own. And that's also with this proper, comp proper service, no best practice standards. So how it helps is, like, you will have a standard coding practice also in force in your organization because everyone will have their own coding style. Right? Okay? Through this, you can standard those things also. The next flow generation. This this is some the next two features seems to be somewhat unrealistic, okay, at start. But when I used it out, I was pretty honest with that. So the flow generation with analysis makes building for flows effortless. Simply define your intent, and it automatically identifies the necessary table, columns, and steps to create a complete flow for you. It's a perfect starting point, saving time and simplifying customization. The example demonstrate how developer describes a complete business process. If you see on the screen, they have just defined this entire entire process what they want to have in the flow. Okay? For example, when an orders order laptop request is submitted, we require manager approval. And upon approval, create the shipping label for the new hire address and create a processing task to the IT equipment support team. Now if you are developer, okay, it will take couple of hours for you to complete this task, but now you can do it in minutes. Okay? And now as it builds the entire workflow automatically complete with visual flow representation and all the necessary logic. You want to define some error handling also on top of it, you can do that also. Just make sure whenever the flow gets generated, you have to have a you have to do a sanity check on top of it. Okay? Don't just put it to the prod, okay, without testing. The last feature for for developer or for admins is I will call it it it can be for citizen developers also to some extent. Okay? Let's talk about app generation. It's a game changer. For those with the developer mindset, you know how tight consuming building an app can be. But with ServiceNow, it's now breeze. Here's how it works. You simply start a conversation in the analyst panel analysis panel and just say, hey. I want to build an app. And analysis, take it from there. It will ask you the purpose of the app, the question to include on the screen, and the choice choices user need all through a back and forth conversation. And guess what? No coding required. Your app is ready. Okay? But it it doesn't stop there. The magic of analysis doesn't just help you to build the app. It can also work within the app itself. For example, if you if, for example, if you like let's take a example. If your app needs to generate and send emails with a specific tone, you can invoke analysis and craft it just right way. Okay? Whether it's creative, formal, or soft, it's full circle solution. Analysis help ServiceNow help you create the app, and the app can leverage ServiceNow to perform smarter function. How cool is that? You can you can build tons of application, using this thing out. So this were all the features across employee agents and developer. You can start using it out from now onwards. Okay? You can start exploring. At least start exploring because it's buzzing in the market. Okay? Everyone is looking out for this kind of solution because of of the the time to value the cost to value the issue is quite huge once you start using it out. And coming to the last part of us presentation is you want us put AI to work, but where to begin? This will be the question buzzing in everyone's mind right now. Right? Okay? And I have I have very, simple, workaround for this particular problem. Okay? So as you know, AI is the future. But where do where do you even get started? Okay? Integrating AI into every part of your business can feel overwhelming. Who you trust with your data? Right? How do you handle outdated system that takes years to integrate? And let's face it. Most AM audit don't fully understand the unique needs of your business. Right? It can feel disconnected from your tool, employees, and customer who rely on it every day. To tackle this challenge, you need to have an AI strategy tailored to your business need. Okay? Start just start by asking yourself three key questions. Okay? The first and the foremost thing is is should you build or buy a solution? Okay? So my personal take on this particular thing is it's always better to buy a solution because, honestly, it takes time, okay, to build the entire AI solution. Okay? And when you have things which you can simply plug and play, you should go for that option first so that you will get the value relation early. Which option deliver the best value and faster result? Right? You have to look into the governance also. Okay? And what specific problem are you solving with the AI? The first and the foremost thing when you jump onto AI is need you need to have a proper use cases where exactly you want to put AI first. Okay. Where exactly is your key pinpoint. Okay. The key area of which you want to automate or which you you want to, ease out the work or ease out the repeat just get rid of repeated task. Also, think about how AI can enhance the way your people work and how you will manage and control AI you implement. The key to success, there is the right technology, consistent practice, and strong policy. With the right approach, EI can transform your business seamlessly and effectively. With this, I'm done with my presentation. I hope that it was beneficial to you guys. I'll stop sharing my screen, and I'll request Benjamin to take it further. Thanks so much, Anna. I wasn't an expert in ServiceNow AI before, but I definitely am now. So that was great. Thank you so much. Thank you. Yeah. Great. Alright. Well, if anyone has any questions, feel feel free to put them in the q and a box. I can see some coming in now. So we'll give it a sec. But just just one for me, Amit. If if people on the call, you know, haven't dived into AI yet, maybe they haven't got, buy in from the business yet and they they wanna start kind of experimenting. What's what you know, are there any paths people can take to to kind of get stuck in from a technical perspective? Yeah. I would recommend I I would recommend starting simple. Okay? Become one or two high impact use cases like incident deflection or agent assistant, which all which is generic to most of the organization. Right? Okay? Show quick wins, measure the outcome, and build confidence step by step. Honestly, I feel the beauty of analysis is that it's embedding in the platform. Okay? So you can start small and scale without heavy lifting. So this was a key for any any organization out there. Yep. 100%. That 95% of people who spent $3,540,000,000,000, if they started that way, then they might have not not wasted so much money. Great. Let's, so we have a question here from Amit Singh. Thank you, Amit Singh. A lot of focus on the good things about AI at the moment, but no one talks about the challenges, data security, governance, and disaster recovery. So what's what's your view coming from two big AI tools, you know, ServiceNow and Salesforce Ben? Maybe I can get the Salesforce Ben side of things, but, you know, what what's your kind of take on it about the maybe, the negatives and and the things people might have to do before they go, you know, go down the AI path with data and technical debt and and things like that? Yes. I I I think I think, first and foremost thing, it's it's really difficult to understand the security aspect of anything. Right? Okay? And, when it comes to AI, definitely, data is the key entity. Right? So platform like ServiceNow, right, where everything is residing on single platform. Okay? You don't have to tweak with multiple system out there. Right? One system for LLM, one system for data, the other system for automation. You don't have to do that. Right? So that's where and ServiceNow itself puts a lot of security guardrails out there. Okay? So they work on zero trust policy. Okay? So they don't compromise your data anywhere. Okay? On top of it, you have an option. Okay? It's an hidden option out there in ServiceNow, but we have a capability where you can completely opt out from data sharing itself. Okay? So if you can enable that particular option, your data will not be shared to any LMM out there. Okay? It will stay with your organization itself. So this kind of guidance boost, confidence in in customers, okay, with with respect to AI. But I I want to hear from the Salesforce side also how you how how you want to take it up. Yeah. I mean, it's very it's very similar. You know, Salesforce Ben, ServiceNow, and say and sales have a lot of similarities to, you know, sales also have the Einstein trust layer, which again is the same. It doesn't pass any personal data over to any of the LLMs. I I I think there there is a kind of growing concern in the sales ecosystem as well that, you know, there are a lot of data issues, there's a lot of technical debt issues. And when I've spoken to people in the past that have actually implemented AI, I've kind of put these questions to them. I'm like, how you know, what are people meant to focus on if they need to kind of focus on AI and clean up everything, you know. And and, really, the only answer is you have to focus on both. You know, it's not the best answer. Everyone's, you know, strapped for time as it is, but, I I think, you know, you have to get to grips with how AI works. You know, it's such a new technology. You know, one one guy that I spoke to said, the testing phase needs needs to be about four or five times as long as the implementation. Because the implementation actually in some instances instances doesn't take too long, but of course you need to I don't know if you've heard the term red teaming before. It was quite new to me. There's the there's the process of trying to talk to an agent and try and get it to say something inappropriate. You know, because of course your customers are gonna be using this and you wanna make sure that it's as foolproof as possible. So, yeah, it's a really tricky one because there are there are downsides to AI. You can't just go, you know, as I think you've you've said, Trevor, presentation. I mean, you can't just go all in and and not think about some of the fundamental, you know, technical capabilities that you you need to fix first. But I think it's important that people focus on both. You know, start exploring AI, start understanding the concepts, start playing around the tools. But, of course, you know, focus on the fundamentals as well. I completely agree. And, basically, you should as I mentioned earlier also, you should not, start shooting the shining star at the initial phase itself. Right? Okay? The maturity goes step by step with with the equipments. Okay? If you're comfortable with that, okay, then you you start upgrading the things. Okay? Not a lot of times what happens, people will have some unrealistic, I will say unrealistic, demands from the AI, okay, and which will start creating a mess for them, right, at the early stage. So you should start small and and then keep on go growing with that. Yeah. That's amazing. So there's a couple of questions from McCarthy here. I hope I've said that correctly. Kind of related questions. One of them is how can smaller organizations adopt AI while keeping costs under control? But the other ones are the other question is what are best practices for piloting analysis with a limited budget? So, yeah, any tips there, Amit? Oh, honestly, that's the beauty of it. Right? You can see value almost immediately. Right? Okay? Since now assist is natively built into ServiceNow, organization don't need to have heavy setup of integration. Okay? And on the value relation side, definitely, you have to first pick what is the pinpoint. Okay? Which particular area you will get the most cost versus value ratio. Okay? And that's how you start with it. For instance, if if you if you put some, analysis on AI agents. Okay? So for instance, a agent who was able to resolve around 100 incidents in a day, now he's able to resolve 200 incidents. Right? So you can get the rate of rate of we have works force workforce out there. Right? Okay. So that's how you have to first get where exactly if you put the cost, you will get the most value out of it. Okay? This will the first step. And the second is, like, if what particular area you want to target. You will not start rolling out the developer capability than the first day. Right? Okay? Because you developer meant to write code. Okay? You don't want to, make their life easy at at the initial stage. Okay? Once you start saving money out of it, okay, then only you can roll out the things and make life easier. First, try to create profits. Okay? And then try to make life easier for others. So, yeah, that's that's how you think of it. Always think in terms of cost versus value ratio, okay, with every use case. Yeah. Definitely. I think, I I know kind of observability is kind of the next stage of AI as well because Salesforce Ben brought us into, I think, so that is now announced, is it called Mission? No. AI control tower Yeah. Which I think also helps with monitoring the agents, you know, because one concern which I get from McCarthy is, you know, maybe AI agents going out of control and, you know, it hurts racking up the charges and you get a huge bill at the end. So yeah. Yes. Consideration there as well. When it comes to service, now everything is pretty transparent. Okay? You can have governance on everything out there. Okay? You can get the statistics. You can have a review or monitor on on top of your monitoring mechanism on top of it. So you will you you you can trace it out to a single agent also. Right? Means how each agent is performing and how it's adding the value to to everyone's life. So, yeah, that's the that's the key sense of ServiceNow assist. Yeah. And that's it. Thank you, Amit. I think those are all our questions. I'll give it a few moments. But are you gonna be at any ServiceNow events over the the next few months, Amit? Sorry? Are you gonna be going to any ServiceNow events, any of the, world forums? Or yes. The first and foremost thing, in the next we have started with ServiceNow meetup season right now. Okay? So a lot of ServiceNow meetups are happening down every region in India. Okay? At the same time, there are few events driven from a, ServiceNow University are also happening across few regions in India. Right? For example, Hyderabad. So I'll be attending those things up. Pretty pretty amazing learnings over there. So yeah. Nice. Very cool. We're looking forward to the, the World Forum in London, which is in the October, October 16. Might be getting that wrong, but, yeah, it's at the XL, so I think it should be it should be a pretty big event. We're also hosting a happy hour after that event right next to the XL. So if anyone on the call is coming to London, then, yeah, please feel free to to come for that. October 15. Thank you, Mohati. You can see my colleague Simon has just put a link, so feel free to sign up to our happy hour there. I think, yeah, those are all our questions. So, yeah, time to wrap up. Amit, thank you so much for that fantastic presentation. It's really a pleasure speaking to you and learning more about your background. And, yeah, I think we can all agree that, you know, there there is a lot of pipe around AI, but it definitely is real and it's here to stay. So, we need to get on board as quickly as possible, I think. But, yeah, any any last words before we leave the webinar? This is just a start. Right? We have just we have just discussed on now assist, but we have AI agentic AI also in place in ServiceNow. Right? Okay. Which is the next level of things. Okay? So, yeah, AI is booming like anything. Okay? And it it's really important that you get on the boat as soon as possible, right, before it leaves. Okay? There's a boom right now. Okay. Everyone's looking for it. Okay? So just try to be on the AI ship. Yeah. Great. Thank you so much, Amit. And thank you very much for everyone for signing up and spending your time with us. We really appreciate it. Any feedback you wanna send, please feel free to get in touch with us on the form on our website. And we are also always looking for, collaborators. If you would like to write for us or or host a webinar with us, then feel free to get in touch as well. So, Amit, once again, thank you so much for for presenting for us today, and thank you for everyone for attending. And we will see you very soon. See you later. Thank you.