we heard from a variety of great panels talking about how we can better utilize data to support the mission and the changing landscape of the digital enterprise the reality is we face a growing list of adversaries new complexities to the workplace with events like cobia 19 and a global enterprise that requires units of work to be routed at the speed of the mission welcome everyone i'm dan pannar from servicenow and i'm joined by my two colleagues tyler robinson and bob osborne bob thank you for joining us today you're the public sector cto for servicenow can you share with us a little bit about your role throughout the global national security agencies and how you are working with them to help identify the importance of digital transformation around automation and modernization sure dan and thanks for having me dan and tyler this is a great uh situation and and this is certainly a forum through which our our customers are very interested today and what does digital transformation mean to each of the different agencies and you know fortunately i'm able to now have visibility into transformation at government agencies around the world so as the cto for for global governments here at servicenow i see most agencies have had a great plan and a good path forward to transforming from legacy technologies into a more experienced based digital transformation and what that looks like but there are various levels of achievement of those visions and goals dan so i think what we see is going forward is a real opportunity to utilize a platform approach to leverage the investment that most agencies have made in legacy technologies and then harness that under a new way of presenting the information contextually to help people do their jobs better so that that's an interesting point that you bring right a great plan and a path forward um so in conversation right that automating and modernizing an agency's digital enterprise uh that that's no easy effort for anyone to undertake uh based upon your conversations with cios globally within our intelligence communities where should cios begin to support this effort and and how can they operationalize uh the processes behind this yeah absolutely tyler as you and i have seen you know over the years everyone goes to conferences and hears great ideas on transformation and and learns about technologies and how technology can help you achieve these different automation capabilities whether it's through something like automating workflow processes or an artificial intelligence injection of insights that we didn't have previously it all looks and sounds great until you go to implement right so it's all about the architecture and how you align the data to be able to take advantage of these intelligent technologies fortunately whether it's you know something like uh automated processes or full-blown ai what we normally see is that the agency is left holding the bag for integrating these technologies and making them work together to achieve the outcomes that the agencies are trying to achieve particularly in the intelligence community there's a lot of great ai tech that's that's floating around there but it's left to the agency to figure out how they're going to utilize this intelligent technology and then aggregate the information to a human to make an appropriate decision one of the great things about a platform approach like we use at servicenow is it's a native capability that's already baked into the platform so the agency doesn't have to figure out what type of artificial intelligence or intelligent technology they want to use how do they integrate it into the environment and then how do they take the output of that artificial intelligence or that supervised machine learning capability to get the outcome that they're looking for in support of human decision making that's all baked into the product so they can focus on what workflows are they trying to support which data sources are systems of record that are trusted that can be aggregated through normalizing that data into a common data repository and then putting the supervised machine learning scripts on top of that to give contextual information to people to make decisions or take actions at the appropriate time in a workflow what this does is elevate the human decision making because we often hear that you know people are being replaced by by bots and all this stuff but it really doesn't work out that way right so we use uh artificial intelligence in this frame if you will to enhance human decision making throughout the processes that are available within an organization a lot of that works being done manually today and if it's a repetitive process we can use a robotic process automation type capability that's also native native to the servicenow platform to eliminate those repetitive tasks that humans typically aren't good at right they make a lot of mistakes and it's time consuming and and people really don't like to do that stuff and we elevate the human decision making to these uh process decision points that are processed supported with contextual information from the intelligent technology which really allows things to be done faster with fewer errors and with more reliability and in the intelligence community that's critical in decision making so if i was to grab some of what you said we're really talking about we're being asked to do more with less and to do more with less we need to really have a cohesive visibility and and function between people process and technology you mentioned a lot about human decision making with with the people and then you talked a little bit about the automation technology um kind of leads me into a question where there's a little bit of a misconception around automation technology people really believe that automating things will become either extremely expensive for the agency and it's going to replace people how do how does the community itself um overcome this misconception yeah that's a great question tyler it and in some cases it's not a misconception right because if if we just go after the shiny object of of a new intelligence technology and we try to integrate it into the environment and then make it work for us to support a mission-based outcome it can get pretty expensive and if we're talking about strict the strict definition of robotic process automation we do replace people doing repetitive tasks but that's not always a bad thing because we don't have enough highly skilled people particularly in the intelligence services to do the type of work that we're asking them to do so what we've taken on at servicenow is this philosophy of technology and service of people and what that really means is allowing people to do their very best work and and by utilizing technology to support the people in in performing that work so as i referenced previously the ability to automate repetitive functions and remove people isn't something done lightly so these are processes that we've uh validated over time within the agency as being a good process and then we can automate that and then observe how the automation conducts that process to validate that it's being done correctly before the human's taken out of the loop if you will but whenever there's a variance we still interject a person again through having an alert or an email or a text come to someone where the human can then again take action on a variance within that process that we've automated but that's a good thing right because now we've sped up that process of reduced errors and now those people can focus on the higher level decisions because when we talk about the aggregation of data particularly in intelligence data there's so much more information than people can actually consume and process and take action on in a given day week or month then then is is possible for people to keep up with so we have to rely on automation and intelligence technologies to help us sift through the oceans of data and only present the nuggets that are relevant to a decision-making um event within a process or to take action based upon what is presented now there's a trust factor here too and we talk about and this is why i mentioned before understanding within our legacy systems that we already have in the legacy data databases which are the systems of record that we trust and those are the systems we pull from and normalize that data for the artificial intelligence in the servicenow platform to be able to provide contextual information to support that human decision making because the more we rely on technology to present information to the supporters decision the more we have to be absolutely sure we know where that data came from so the trust factor is high and and it's never more critical in in defense in national security systems and of course intelligence systems yeah thanks bob and i mean those are just great insights and and we appreciate your insights and expertise now you talked a little bit about how we've been kind of working on these plans and tyler you all mentioned about operationalizing these plans so getting it implemented where are you seeing that i mean are we getting to that step where we're starting to implement now and we're getting to a point where we're going to be you know we really are going to be taking these platform approaches and and moving units of work at the speed of mission i mean are you seeing that in the in the field yeah absolutely for example inscom is talking about not just modernizing legacy technologies but actually transforming into a digital experience and we're helping go even beyond that by having a an experience for each of the individuals who are interacting with the technology that is a more consumer-like experience as well so dan as as we said previously there's levels of maturity or or achievement of the strategic plans that vary by agency right so some are way more advanced and they've they've really made the inroads into having artificial intelligence be a part of how they're doing business today and others are only beginning to embark on that transformation as part of their strategy and a lot of that has to do with what the mission is the criticality of security around that mission and then how resources have been allocated based upon you know the different uh areas that change throughout the year that we all have to deal with within government so i would say that yes absolutely we see agencies who are well embarked upon this transformation uh utilizing a platform approach as part of their strategy to help modernize the experience which really helps with you know recruiting and retention also which is a big challenge for many agencies the more that that people feel empowered and they're doing their best work and they're doing something that's effective and they can see the results of that the more likely they are to stay and be uh satisfied at work and that's another byproduct of having this experience based platform approach to transforming the agency yeah i mean that's an excellent response and um you know i really took a lot from this discussion and i i honestly wish we could keep going because we haven't we're getting a lot of good nuggets here but i think we've really emphasized i mean we've had the plans we're trying to put we're putting the plans in place and the importance of automation uh so we can do more with less uh and help these agencies on a digital transformation journey that they're on and bob i mean do you have any closing remarks before before we end the session today well again dan and tyler thanks a lot for having me on today and to everybody who's joined us but i could talk about ai and automation for days so i'm i'm sad that we have to cut it short but we're available to anyone who wants to have a follow-on conversation and dig deeper into these topics thanks a lot guys thank you bob thank you tyler and thanks everybody have a great rest of your summit thank you you