The Art and Science of AI: Insights from a Chief AI Officer

As we continue to navigate the rapid advancements in Artificial Intelligence, it's essential to understand what it takes to succeed as a Chief AI Officer. In this conversation, we sat down with Richie King, who shared his experiences, insights, and advice for aspiring leaders in the field.

On Becoming a Chief AI Officer

Richie began by discussing the role of a Chief AI Officer, stating that "you need a lot of resilience" to tackle the challenges that come with leading AI initiatives. He also emphasized the importance of being patient and willing to work through complexities. Richie acknowledged that not everyone is aware of the G role, but expressed excitement about the potential rewards. When asked what he's most excited about in the world of AI right now, Richie mentioned the recent release of Uudio (a music generation tool) and its impact on musicians like himself.

The Impact of AI on Music Generation

Richie shared his personal connection to music generation, stating that it has the potential to revolutionize the industry. He noted that creating and playing music is an incredibly challenging task, requiring years of dedication and expertise. However, with AI-powered tools like Uudio, musicians can now explore new creative possibilities. Richie emphasized that while AI-generated music may not replace human talent entirely, it can certainly augment and enhance musical experiences.

The Tipping Point of a New Century

Richie believes that we are at the cusp of a major shift in the world of AI, with far-reaching implications for industries and individuals alike. He expressed excitement about the potential impact that AI can have on Enterprises around the world, citing examples like SAP. Richie noted that the ability to design and influence technology responsibly is critical to realizing this potential.

A Holistic Approach to Leadership

When asked about his advice for aspiring Chief AI officers, Richie emphasized the importance of a well-rounded skill set. He suggested that individuals should educate themselves on various aspects of AI, including technology, business, marketing, and stakeholder management. Richie stressed that a holistic approach is essential to bring these different concepts together effectively.

Aspirations and Challenges

Richie acknowledged that becoming a Chief AI officer requires high aspirations, as well as a deep understanding of the challenges involved. He noted that the role demands a broad range of skills, from technical expertise to leadership abilities. Richie encouraged aspiring leaders to focus on developing their unique strengths and weaknesses, rather than trying to become experts in every area.

Final Advice

In conclusion, Richie offered his final advice for aspiring Chief AI officers: "read and educate yourself in a holistic fashion with all the various aspects of AI." He emphasized that this approach is critical to bringing together concepts from different areas and developing a comprehensive understanding of AI's potential. By embracing this mindset, individuals can position themselves for success in this rapidly evolving field.

The Future of Music Generation

As we look to the future, Richie expressed enthusiasm about the possibilities presented by music generation tools like Uudio. He noted that while AI may not replace human talent entirely, it has the potential to augment and enhance musical experiences. With the right approach and mindset, individuals can unlock new creative possibilities and push the boundaries of what is possible in music.

Conclusion

In this conversation, Richie King shared his insights and advice for aspiring Chief AI officers. From the importance of resilience and patience to the need for a holistic approach to leadership, Richie provided valuable guidance for individuals looking to navigate the complexities of AI. As we continue to explore the potential of AI, it's essential to remember that success requires a deep understanding of both technology and human perspective.

"WEBVTTKind: captionsLanguage: enyou know there's all these things Rich that change all day long right the tech changes the llm changes the tools change but what shouldn't really change our values like how do we think about how the world looks in an AI age uh and what is important to us when we design AI into our workflows and applications and that is also something that we are continuously evolving hi Philip welcome to the show thank you so much Richie pleasure to be here to with you today excellent so there are a lot of technical seae positions you got Chief data officer Chief technical officer Chief Information officer how's the chief AI officer role differ from these that's a great question so I mean first of all it's a new kind of role right um that we that we also at sap we have established at the beginning 2024 and um at least I mean there are different interpretations right on on what that role entails the way or why we have set it up uh specifically in sap is um to really take a 360 perspective on AI um where for all the functions I mean as one of the largest um Enterprise application vendors right uh specifically out of Europe um we have to take not of course only the adoption internally right for our processes and for our people into account but obviously um how we you know think about the products how we bring AI all into our products we can spend a little bit more time I think about our product strategy in a minute uh and then really uh think this end to endend through right how do we do legal aspects the commercial aspects and as we all know right who also regularly listening to this podcast there's so many things that happen all every day every every week new models come around the corner there's something happening on the regulatory side of the house so the question is really like what is the center of excellence or like the the nucleus in the company that takes all those signals all those Concepts into account and you know fit them together like differently or every single day right and there's a every day there are new opportunities new risks and in this role the way how we interpret it is really take an endtoend view right but at the same time it's also just a relatively small Department because at the end of the day and that's part of our strategy as we embed AI specifically all in our our our Enterprise applications is then to work with all the connected uh board areas right product and engineering technology department the CTO the CIO for internal adoption um our sales and marketing teams uh closely together right to then scale the entire approach uh across the entire portfolio that we have today okay so that sounds like you're working with a lot of different teams as you mentioned uh BR commercial team okay so uh can you you go into any more dep like what do your day-to-day responsibilities look like so first of all as part of this Chief AI officer mandate um we have uh basically all the roles in there right so we have for example part of my team that was the team also before right so AI is not a new thing I was before that I was on the engineering side of the organization right this is also why this cross collaboration and and and and this work is so natural to us as a team because I was actually part of the product engineering area within sap right where all the applications like our Erp our HR applications Finance supply chain procurement applications like conquer field glass rebba success factor some of them you may know are located and and I was I was always the cross engineering guy if you will right looking top to bottom looking at our user experience looking at our process integration our technology adoption with respect to our technology platforms and AI we also did in the in the last couple of years there as well and we moved it out uh directly under our CEO uh Christian Klein and Engineering is still with us where we build platform services like for example Jewel our generative AI co-pilot which all of the applications are adopting where we build what we call the generative AI Hub which is kind of the glue if you will uh where we bring the best of large language models or foundational models together with the real-time data that is stored within sap and nonsp systems a couple of other reuse services for document information extraction data attribute recommendation recommend other recommendation Services uh that are kind of you know reuse services that you can embed uh in multiple uh different applications so we build those that's part of our engineering um um layer that we provide as a as a service platform service to our own applications but then of course we have a dedicated product that partner management team we have a dedicated marketing team we have a dedicated goto market and sales team we have dedicated implementation adoption team that helps customers uh then all the innovations that we are building to adopt them very quickly but also funel the feedback from those customers back very quickly and as you can imagine what does my daily job look like like all of those things now so every day we look at what's what's new on the product side of the house right how can we bring that directly to the customers how can we enable our field with that how can we turn first customers right really to adopt also latest Innovations with that how do how how does this what is the impact on our marketing approach and we are reviewing all of the all of these days every all of these things every single day uh in order really to move really really quickly and in alignment with our customers expectations okay so it sounds like you've got quite a lot of different AI products going on there um I'd like to get into a bit more about um where your role sits within the organization so you said that you report to a lot of different um te or you work with a lot of different teams who do you report to yeah so I report directly to our CEO Christian CL okay and then um who is in your team like who reports to you so within my team there's for example Welter son who joined us last year in September from from Microsoft um who was uh uh there working also in the business application uh space um you know around Dynamics 365 and and and some of the some of their platform services and he runs all of our AI engineering functions both our research that we are doing with universities you know like Stanford and Berkeley and and a few others in Germany like hustle platner Institute or the Technical University in Munich and a few more uh up onto all the services I described already right so really on the technology platform all those reuse Services um that we are building and then we have as I said right we have a dedicated leader a very renowned leader within sap um Yan who reports to uh to myself looking after the go-to market and you know spreading basically across all the regions uh our our enablement material right and and how we position how we how how how we are selling then also Ai and and to to to our customers have dedicated marketing team uh product and partner management as we also is part of our strategy uh we are partnering with many of the companies with Microsoft with Amazon with Google and and many more more Nvidia uh and then on the other side of course we enable all the other partners right so obviously sap is also heavily uh um partnering very closely uh with all the uh global Service and Consulting organizations around the world in order to also scale from an implementation and Consulting perspective as well okay so it's not just working with internal teams you're doing a lot of Partnerships with other companies as well since that external facing sight of role too yes exactly okay so um when you're working with so many different teams I imagine like the communication flow and like just managing the logistics of doing so many different teams is a challenge can you talk me through how you approach that we have kind of for all the various functions we have very close and regular alignment meetings on on give it just one example um already last year specifically when the entire hype right around chat GPT and what what do we now have to do with respect to generative AI uh what what does this mean for us right and what how do we bring this into our how into our applications how can we help right to make HR more productive or shared service centers more productive um sales more productive um Services marketing and we formed a little group uh already last year almost January something uh where we form the small team and it and and thought hard about how do we how do we you know build the first scenarios basically um because our strategy just here to back up a little is really first of all sap does not strive so much for a general purpose technology platform right that helps customers to build AI like you know tools for prompt engineering or retrieval aanda generation or data pipelines yourself right and then you have some smart people who can build those things like a chatbot or or digital assistant or something our strategy is that these things are embedded in the applications and just turn them on and just work out of the box right uh and so the question first was was what were high value use cases that we would develop uh that where customers say like okay that is actually something where I see generative AI embedded into an sap application actually helps me and we we figured those cases out very quickly and just started executing was a small Nimble but very capable team that we've started with in order to to move that forward and it turned over the over the last year it turned out into the standard call we run it on a on a weekly basis when we actually wanted to release our first uh scenarios was actually on a daily basis where with all the teams right we went through all the challenges that are there right in order to productize them and put them in front of the customer um and we are still running it ever since so all the we have meanwhile released via this uh alignment call released 39 generative AI scenarios um um in Q4 and q1 alone there are 40 more in Q2 till end of this year there's 100 more that we are that we are releasing and this is how we are aligning that right and every every time somebody comes up with a new challenge right or or a new thing that needs needs to be addressed or that needs to be rolled out because we come up with a new concept on the commercial side of it and we are doing this all in this all in this one single call if you will in order to really let the flow of information flow throughout uh throughout sap as a as a obviously very large company and so far it worked very well okay so it seems like you just doing lots and lots of communication with lots of different teams just to make sure everything's and then also as part of my previous gig just also how do we align architecturally because I think that's also something that I'm very um at least very happy with um you know SCP is a very heterogeneous company right we have many lines of businesses right in the various areas but also as part of my previous role and that helps obviously a lot um I was running what we call cross product architecture so that was a uh approach we have established in the last three years to really get all the various lines of businesses no matter whether it's coner or whether it's success factors or reeba or scps for Hannah to agree on the common technology Foundation a common set of platform services and capabilities that everybody has to adopt in order to come up uh with this with a with a with what we call Sweet qualities right so a set of qualities that are uh equal right amongst um the various application very simple things like that all the mobile apps right uh that the login works the same way all of them are using let's say face ID or have the same look and feel down to okay the identity management is for example harmonized and that was a huge program we did a lot of the last three years and that obviously helps a lot right because now we we could design also the AI foundation for all the applications the same way so when I talk for example about Jewel our generative AI co-pilot this this is not like a jewel for HR or a jewel for finance or a jewel for for supply chain no it's one Jewel that sits at the heart right of the architecture and all the applications are connecting into it and the more applications you connect to it the more powerful uh the assistant eventually becomes okay so that seems like an interesting thing about AI is because you require all this data having a single AI connected to lots of different things is going to be more powerful than having lots of individual okay all right so um I'd like to know a bit about what constitutes success so um how do you know if you're successful in your job so first of all it's all about um there basically three main aspects right that we always consider first of all it's do we deliver the right scenarios for our customers right so that it really uh has the relevance um to uh to you know to be adopted at the end of the day so the ultimate success metric for us is clearly adoptions specifically in the cloud right um I mean you can build the best and amazing most amazing thing in the world nobody actually adopts it you probably buildt the wrong thing so we are entirely Guided by adoption and making sure it can be easily turned on out of the box it's available as a service uh because we figured out over the last couple of years that specifically you know if it's not delivered out of the box not as a service adoption usually is very hard um so that's number one the second one is clearly Rel liability I mean we all know what the limitations uh of large language models are right uh with all those things husin Nations only has been trained on public data up to a certain point in time of course they do not know the current realities of your business like oh where are my sales orders where are my general ler accounts where where is my current uh Goods Goods receipt or where's the delivery right of a certain um of certain Goods etc etc so we need to bring together in a reliable secure and data privacy preserving way uh the real-time data of the of the of of of the SAP systems uh together with the large language models in order to really bring in the contextual knowledge you need in order to make actually the relevant uses cases to happen but of course we want to do that in a very secure uh and and trustworthy way because this is what our customers come to expect from sap for for decades and the last piece I'd like just to mention is also our approach to responsible AI so um sap was one of the first companies um to establish what we call an AI ethics policy back in 2018 and it guided us well through the years so this is really you know there's all these things Richie that change all day long right the tech changes the llm changes the tools change but what shouldn't really change our values like how do we think about the world how the world looks in AI age uh and what is important to us when we design AI into our workflows and applications and and that is also something that we are continuously evolving uh and that's also part of one important success metric um that we're always sticking and staying true to our values uh when we design specifically generative AI uh into into our apps okay so I I like that your sort of main Judgment of all criteria for successes like your shipping AI products and your customers appreciate those um I'm Dr like in more depth can you talk about like uh Japanese specific metrics or targets that are use to evaluate your success as a chief AI officer well we obviously want to get as much customers to adopt our things uh um they're there in total I mean overall what I can just share is we have already mean AI overall is not a new topic for sap um we have roughly 27,000 Enterprise customers right around the world who are using our AI capabilities uh on a on a regular basis and uh yeah of course we our ambition is to heavily uh continue that growth from an adoption perspective in the years to come and specifically with with generative AI okay and it seems like you've got a lot of different uh products and projects on the go um can you talk me through how you prioritize which AI projects are going to be most important prioritization is always on um from from a value perspective so what has the highest value and there could be multiple things right it could be potential Topline impact for a customer right in particular if you think about gen the the usual gen scenarios in sales and services or marketing um so front office related roles could be bottom line improvements cost of good Souls improvements um through through generative AI um or just simply as we target that with Jewel to re think the way how people interact with the system in a way more delightful and easy fashion compared to you know rather classical click through all the uis to accomplish your task um um um fashion and that is usually the way how we how we um evaluate the scenario so when we go through the scenarios we are always looking at it from a what's the return on investment from a customer perspective so like what is really the benefit uh the that that helps the customer to do something faster or easier right or helps them to achieve more with less so those are always the the the questions that we ask already very early in the product life cycle before we go further down the road in order then to implement and spend our resources uh on on on on on those cases and this is how we run it for the most part okay so um the three things you mentioned there were improvements to Top Line so increasing revenue and then improvements to the bottom lines it's cost saving and then uh working better with your software um so I guess it's a customer experience Improvement can you go into more depth just to explain to the audience like uh so what sort of projects are going to help improve Revenue what sort of projects are going to help save costs and uh and yeah what sort of benefits you get from working differently with your software so just give you a couple of examples right that we that we are having um I mean one of the more classical scenarios that we have been just just to draw on a few numbers um that we have been doing for decades is data entry in a system right there's still across all the different business processes there is still like tons of paper and with paper I also don't mean like printed paper but you know email and PDF and digital paper is still paper and and still there's like a plethora right of of processes that require you to tediously manually enter all of those things right into into transactions into into screens right and just transmit basically what's on paper into that system and I think there's a lot there's a tremendous amount of potential to just give you a few numbers alone and and Conquer for example just with B2B in the background we are processing like somewhere between in the range of 60 to 100 million invoices right in a fully automated fashion for example right and it's just in the system fully fully itemized right they're just in there there's no manual eror prone and tedious work just to key those key those in and every body who has filed an expense report exactly knows uh how tedious that sometime sometimes can be and we can save a hell lot of effort with with with and and and and money by that right in a in a high triple digit million uh uh number range um we also look for example into shared service center right think about accounts payables for for example or accounts receivables if you have a large shared service center where you know all the various complaints let's say for example accounts payables right you have all your suppliers and they are complaining because you may have not paid them in the in the contractually uh uh agreed on times because may be of quality issues or what does whatever whatever right blocks the payment to the supplier and you easily depending on your size of the company you can like have hundreds thousands of these cases on a daily on a daily basis yeah and then of course it's starts with simple things like oh how can I catch up within with the threat and the discussion that was already happening via email maybe with that supplier that imagine there's a new person looking at that thread and generative AI instead of reading all that emails helps you to just catch up with that threat in like virtually no time right versus reading 10 20 minutes per case through that email and then you get suggestions what you do with it right you can say like okay maybe you do a do a recommendation maybe give a voucher or give some more time or maybe give certain discount or all those things which I would be then recommended bya Jewel and then once you have to resolve that problem of that ticket it then also of course helps you for example to generate an email and not just a email uh like a standard thank you email or we solve that email but one that is specifically written with the business context in mind so having the reference to the invoice number maybe to the purchase order right so that also the supplier has a good chance to reconcile it again back in their business uh much faster and much easier so it's not about creating a PL with email but really one with with context that usually if you would craft this manually getting all those fields out and so on the email can easily take you I don't know 20 30 minutes to to write and now we can just do it in in seconds right and multiply that with the volume of cases that's a that's a huge timesaver and it's not only a huge timesaver it will also help right to improve either your supplier uh experience right with your suppliers because you're reacting faster you're resolving the cases faster and know accounts receivable side of course also helps with the customer experience because obviously customers will be much happier because you resolve their cases faster too and yeah those are maybe two examples um that that I I can share um I think that are relatable um that maybe that are not too deep in the in the business process world yeah absolutely um it always feels amazingly clunky like how much effort it takes just to either pay money to another business or receive money from a business and so just being able to automate that that just seem like an ideal use case for AI speeding things up um all right so can you talk me through what are the big challenges with your role I think overall one of the big challenges that that we deal with every day is how can we absorb the massive change and the massive transformation that is happening at this to be honest unprecedented speed right I mean we had some some other huge technology disruptions before you know everybody always relate Compares like generative AI what's currently happening with the Internet or What's happen with mobile or the introduction of the microchip and the PC and um the difference is all those Trends were maybe as disruptive but they were not as fast uh as this currently happen because all the infrastructure is there or lots of infrastructure at least is there and it's so exci accessible and you know taking that in and determining what are the right products build but then also helping our customers at scale right not just in a certain Market or for a certain pocket of customers that's simple that's that's usually easy but really scale it uh throughout all the various departments within sap but then also reach all the customers right with with with the same narrative with the same message right and also keeping them uh up to date is is really a challenge I just had a just to give you an example I just had a partner meeting today and they just told that Philip you need to help us to keep up with this with this pace right it's it's just too fast that's on the one hand side it's a it's a good problem to have but it's also a clear challenge right because it's it's it's pretty tricky to everything that happens on the tech side right to immediately absorb build the right products and then enable every customer and tell them look this is this is the way how we how we design it so doing that at scale for like hundreds of thousands uh of of Enterprise customers is a big challenge I'm sure certainly keeping up the pace of AI developments um is a challenge for everyone so I'm wondering uh what's your solution to this do you have any advice on how to keep up with the the that's a fun question but I also have I think I have a little bit of an unconventional answer to for you so first of all I read a lot of things myself um so it helps a little bit that I'm still an an engineer myself um so I go into many things also over the weekend um I'm trying out many things some of those large language models not some of them I try them all of them myself um try to run them locally as much as possible uh think of some of the open source models like llama right or uh the the mistal models um to and and and and then basic and of course read all the read and hear podcasts like data frame for example and and others to keep up to date but also you know relate a little bit like different opinions different point of views on on on on what people think about it and then what I basically do is not just hearing those things and trying to understand it for myself um but I sit down basically every week on on on on on on on the weekend and I write all of that stuff down uh in an email and that goes out to thousands of sap employees it's basically a voluntary subscribe to there's always a link hey if you want to if you don't want to receive this anymore click here if you want to receive it click there uh and luckily I get more click there than click here things and um it meanwhile reaches a couple of thousand uh sap employees on the weekly basis and it's not just a rundown or write down of all those things but also actually it's like it's like a a big action item like hey have you seen this and in this technology there's this new model please please evaluate it deeper it looks good to me I've tried to following things out I think that's helpful for this service I think it's helpful for that service or when there is something uh happening in the market that may relate to some of our products right either on the technology side or on the application side and say like hey dear Pier L1 leader please check this out I think you should do a deeper dive on what that means and whether we can incorporate that of it's of any use uh and it's like a it's both like a rundown or breakdown of all the things that happened in this week plus say and hey here's an action item please come back uh next week and and please let me know if there's something that's that that's useful to you and you know that kind of process helps to not only digest and and by writing it down again but also uh to to Really you know reflect on where does this belong to in the company and and and and figure out who should be on point right to evaluate whether that technology or that tool or whatever is coming out or that research paper also read a lot of research papers obviously um and and then to figure out what what that would mean and if we can incorporate those things within our our Solutions somewhere okay actually I have to say I really like that approach so when you read something interesting you then think well who else in my company is this going to be relevant to so you can say okay this is going to be great for this service or this product and and that way it actually gets used rather than just EX translate right what this whole thing is not just oh here's the rundown think for yourself but here's already I think there's an anchor Point here right there's an there's an IDE concept and I think you really should take a look uh and and that helps a lot that people then really take this more seriously and say like okay well then I take a look and maybe it sometimes also turns out I was wrong that's fine right and and the approach uh doesn't work because it's maybe not yet mature enough um we had this a couple of times people came back and then said well yeah we tried it but um maybe version two let's see um that also happens but but still they they expose themselves to they they gutten know that and obviously this is part for me of this whole organizational learning that needs to happen in order to stay up to date with with what H what is happening uh so if you could go back to when you first started this role uh what advice would you give to yourself I think it's always important to stay hungry and and and and and foolish uh and you know try all try out all these things but you know it also can get daunting sometimes and in particular in this fast-paced environment that we are in and I can only give this advice to to everyone to just just just just continue there there will be also lots of stressful and painful days um but I think overall if you can you can train your resilience in the current times quite well and and so far I I think the the reward the reward uh is much higher um bottom line and yeah if I were just g go back say like yeah know what you're subscribed to know what you're up to but then also have the resilient and resilience and the patience to to to work it through all right super so uh I have to say you weren't telling me G role to be a to yeah you need a lot of resilience is a lot of pain here but uh I like that there's some good rewards with the role as well um okay so uh can you tell what you're most excited about in the world of AI at the moment I think just top of my mind right now is uh I think just last week um the is the the release of how do I pronounce this is U udio or something because I'm also just on my personal level when it comes to AI progress because I'm a kind of want to be musician for 20 years um I think we just reached the next leap in terms of Music generation so that is something that is like it's like extraordinary to see knowing what it takes also you know to play yourself and create and design and playing music for for years um but no I think overall it's just exciting to see really that you know with AI in general I think we are at the Tipping Point of a of of an entirely New Century and being at the having the privilege right to be on the Forefront of of and and you know being able to influence and design also uh both in a relevant but also responsible way this technology for Enterprises around the world right I mean the the largest companies on this planet rely on sap and I think simply the impact that we can create with that again in irrelevant but at the same time responsible way that is this just mindboggling on the impact that this can create in the next years to come so this is this is what what motivates me every day uh because it's it's really really impactful the work that uh that that that we can do okay uh yeah you're right there's so much amazing stuff going on I would also like to Second the idea of having AI generated music it's gonna be a brilliant thing so I was think like it would be kind of nice to be a rock star but also I have zero musical Talent so if if technology can bridge that Gap then there so much the better but I I don't think that everybody would going to be a rock star right because while it's impressive right um the end of the day there's still always some you know music and and this is something where I honestly believe Jenny I will never take this away you know music also programming right these are more like liberal arts than you know just mathematical things and you know there's a big difference between a solid and well- constructed song and a song that touches people and and I to be honest I think this will never go away um yeah okay maybe my wrck our aspirations been dashed once again um all right so do you have any final advice for aspiring Chief AI offices I think the chief AI officer for the most part needs really a heterogeneous set of skills um so I think on the one hand side obviously it helps a lot to you know uh be knowledgeable uh in in Ai and know the technology you don't I don't think you have to be the the top most expert in that domain like 10 years data science right and and then written tens of uh uh research papers like with Google Deep Mind and others um but I think it's in particular the combination of skills right you need to understand the technology well enough in order to understand its implications and what that means where the market is going and combine that with the skills on how to identify the right scenarios do a lot of St holder management come up with the right architecture uh find the right messaging and narrative from a marketing perspective uh uh determine how you can actually also you know from a from a cost but also from a from a from from a revenue or sales perspective right relate that so that you come up with a viable product so all these various Dimensions I think are critical as a chief AI officer to be really successful at the end of the day so it really needs a I think a well-rounded profile right of all these various uh things in order to bring those Concepts um um together so I can um I can only recommend aspiring Chief AI offices to really look at this topic not purely from let's say one angle like let's say technology for example but really read and and and educate yourself in a holistic uh fashion with all the various aspects in order to be successful I think that is critically important to bring all those various Concepts really together in the in in the right manner Okay so really broad set of skills uh it sounds like this gonna be a role for generalists uh but you also need uh some pretty high aspirations I guess if you can bring all those teams together all right super uh thank you for your time philli this is very insightful stuff no thank you so much Richie for having me it was was a pleasure thank you so much for having me on the showyou know there's all these things Rich that change all day long right the tech changes the llm changes the tools change but what shouldn't really change our values like how do we think about how the world looks in an AI age uh and what is important to us when we design AI into our workflows and applications and that is also something that we are continuously evolving hi Philip welcome to the show thank you so much Richie pleasure to be here to with you today excellent so there are a lot of technical seae positions you got Chief data officer Chief technical officer Chief Information officer how's the chief AI officer role differ from these that's a great question so I mean first of all it's a new kind of role right um that we that we also at sap we have established at the beginning 2024 and um at least I mean there are different interpretations right on on what that role entails the way or why we have set it up uh specifically in sap is um to really take a 360 perspective on AI um where for all the functions I mean as one of the largest um Enterprise application vendors right uh specifically out of Europe um we have to take not of course only the adoption internally right for our processes and for our people into account but obviously um how we you know think about the products how we bring AI all into our products we can spend a little bit more time I think about our product strategy in a minute uh and then really uh think this end to endend through right how do we do legal aspects the commercial aspects and as we all know right who also regularly listening to this podcast there's so many things that happen all every day every every week new models come around the corner there's something happening on the regulatory side of the house so the question is really like what is the center of excellence or like the the nucleus in the company that takes all those signals all those Concepts into account and you know fit them together like differently or every single day right and there's a every day there are new opportunities new risks and in this role the way how we interpret it is really take an endtoend view right but at the same time it's also just a relatively small Department because at the end of the day and that's part of our strategy as we embed AI specifically all in our our our Enterprise applications is then to work with all the connected uh board areas right product and engineering technology department the CTO the CIO for internal adoption um our sales and marketing teams uh closely together right to then scale the entire approach uh across the entire portfolio that we have today okay so that sounds like you're working with a lot of different teams as you mentioned uh BR commercial team okay so uh can you you go into any more dep like what do your day-to-day responsibilities look like so first of all as part of this Chief AI officer mandate um we have uh basically all the roles in there right so we have for example part of my team that was the team also before right so AI is not a new thing I was before that I was on the engineering side of the organization right this is also why this cross collaboration and and and and this work is so natural to us as a team because I was actually part of the product engineering area within sap right where all the applications like our Erp our HR applications Finance supply chain procurement applications like conquer field glass rebba success factor some of them you may know are located and and I was I was always the cross engineering guy if you will right looking top to bottom looking at our user experience looking at our process integration our technology adoption with respect to our technology platforms and AI we also did in the in the last couple of years there as well and we moved it out uh directly under our CEO uh Christian Klein and Engineering is still with us where we build platform services like for example Jewel our generative AI co-pilot which all of the applications are adopting where we build what we call the generative AI Hub which is kind of the glue if you will uh where we bring the best of large language models or foundational models together with the real-time data that is stored within sap and nonsp systems a couple of other reuse services for document information extraction data attribute recommendation recommend other recommendation Services uh that are kind of you know reuse services that you can embed uh in multiple uh different applications so we build those that's part of our engineering um um layer that we provide as a as a service platform service to our own applications but then of course we have a dedicated product that partner management team we have a dedicated marketing team we have a dedicated goto market and sales team we have dedicated implementation adoption team that helps customers uh then all the innovations that we are building to adopt them very quickly but also funel the feedback from those customers back very quickly and as you can imagine what does my daily job look like like all of those things now so every day we look at what's what's new on the product side of the house right how can we bring that directly to the customers how can we enable our field with that how can we turn first customers right really to adopt also latest Innovations with that how do how how does this what is the impact on our marketing approach and we are reviewing all of the all of these days every all of these things every single day uh in order really to move really really quickly and in alignment with our customers expectations okay so it sounds like you've got quite a lot of different AI products going on there um I'd like to get into a bit more about um where your role sits within the organization so you said that you report to a lot of different um te or you work with a lot of different teams who do you report to yeah so I report directly to our CEO Christian CL okay and then um who is in your team like who reports to you so within my team there's for example Welter son who joined us last year in September from from Microsoft um who was uh uh there working also in the business application uh space um you know around Dynamics 365 and and and some of the some of their platform services and he runs all of our AI engineering functions both our research that we are doing with universities you know like Stanford and Berkeley and and a few others in Germany like hustle platner Institute or the Technical University in Munich and a few more uh up onto all the services I described already right so really on the technology platform all those reuse Services um that we are building and then we have as I said right we have a dedicated leader a very renowned leader within sap um Yan who reports to uh to myself looking after the go-to market and you know spreading basically across all the regions uh our our enablement material right and and how we position how we how how how we are selling then also Ai and and to to to our customers have dedicated marketing team uh product and partner management as we also is part of our strategy uh we are partnering with many of the companies with Microsoft with Amazon with Google and and many more more Nvidia uh and then on the other side of course we enable all the other partners right so obviously sap is also heavily uh um partnering very closely uh with all the uh global Service and Consulting organizations around the world in order to also scale from an implementation and Consulting perspective as well okay so it's not just working with internal teams you're doing a lot of Partnerships with other companies as well since that external facing sight of role too yes exactly okay so um when you're working with so many different teams I imagine like the communication flow and like just managing the logistics of doing so many different teams is a challenge can you talk me through how you approach that we have kind of for all the various functions we have very close and regular alignment meetings on on give it just one example um already last year specifically when the entire hype right around chat GPT and what what do we now have to do with respect to generative AI uh what what does this mean for us right and what how do we bring this into our how into our applications how can we help right to make HR more productive or shared service centers more productive um sales more productive um Services marketing and we formed a little group uh already last year almost January something uh where we form the small team and it and and thought hard about how do we how do we you know build the first scenarios basically um because our strategy just here to back up a little is really first of all sap does not strive so much for a general purpose technology platform right that helps customers to build AI like you know tools for prompt engineering or retrieval aanda generation or data pipelines yourself right and then you have some smart people who can build those things like a chatbot or or digital assistant or something our strategy is that these things are embedded in the applications and just turn them on and just work out of the box right uh and so the question first was was what were high value use cases that we would develop uh that where customers say like okay that is actually something where I see generative AI embedded into an sap application actually helps me and we we figured those cases out very quickly and just started executing was a small Nimble but very capable team that we've started with in order to to move that forward and it turned over the over the last year it turned out into the standard call we run it on a on a weekly basis when we actually wanted to release our first uh scenarios was actually on a daily basis where with all the teams right we went through all the challenges that are there right in order to productize them and put them in front of the customer um and we are still running it ever since so all the we have meanwhile released via this uh alignment call released 39 generative AI scenarios um um in Q4 and q1 alone there are 40 more in Q2 till end of this year there's 100 more that we are that we are releasing and this is how we are aligning that right and every every time somebody comes up with a new challenge right or or a new thing that needs needs to be addressed or that needs to be rolled out because we come up with a new concept on the commercial side of it and we are doing this all in this all in this one single call if you will in order to really let the flow of information flow throughout uh throughout sap as a as a obviously very large company and so far it worked very well okay so it seems like you just doing lots and lots of communication with lots of different teams just to make sure everything's and then also as part of my previous gig just also how do we align architecturally because I think that's also something that I'm very um at least very happy with um you know SCP is a very heterogeneous company right we have many lines of businesses right in the various areas but also as part of my previous role and that helps obviously a lot um I was running what we call cross product architecture so that was a uh approach we have established in the last three years to really get all the various lines of businesses no matter whether it's coner or whether it's success factors or reeba or scps for Hannah to agree on the common technology Foundation a common set of platform services and capabilities that everybody has to adopt in order to come up uh with this with a with a with what we call Sweet qualities right so a set of qualities that are uh equal right amongst um the various application very simple things like that all the mobile apps right uh that the login works the same way all of them are using let's say face ID or have the same look and feel down to okay the identity management is for example harmonized and that was a huge program we did a lot of the last three years and that obviously helps a lot right because now we we could design also the AI foundation for all the applications the same way so when I talk for example about Jewel our generative AI co-pilot this this is not like a jewel for HR or a jewel for finance or a jewel for for supply chain no it's one Jewel that sits at the heart right of the architecture and all the applications are connecting into it and the more applications you connect to it the more powerful uh the assistant eventually becomes okay so that seems like an interesting thing about AI is because you require all this data having a single AI connected to lots of different things is going to be more powerful than having lots of individual okay all right so um I'd like to know a bit about what constitutes success so um how do you know if you're successful in your job so first of all it's all about um there basically three main aspects right that we always consider first of all it's do we deliver the right scenarios for our customers right so that it really uh has the relevance um to uh to you know to be adopted at the end of the day so the ultimate success metric for us is clearly adoptions specifically in the cloud right um I mean you can build the best and amazing most amazing thing in the world nobody actually adopts it you probably buildt the wrong thing so we are entirely Guided by adoption and making sure it can be easily turned on out of the box it's available as a service uh because we figured out over the last couple of years that specifically you know if it's not delivered out of the box not as a service adoption usually is very hard um so that's number one the second one is clearly Rel liability I mean we all know what the limitations uh of large language models are right uh with all those things husin Nations only has been trained on public data up to a certain point in time of course they do not know the current realities of your business like oh where are my sales orders where are my general ler accounts where where is my current uh Goods Goods receipt or where's the delivery right of a certain um of certain Goods etc etc so we need to bring together in a reliable secure and data privacy preserving way uh the real-time data of the of the of of of the SAP systems uh together with the large language models in order to really bring in the contextual knowledge you need in order to make actually the relevant uses cases to happen but of course we want to do that in a very secure uh and and trustworthy way because this is what our customers come to expect from sap for for decades and the last piece I'd like just to mention is also our approach to responsible AI so um sap was one of the first companies um to establish what we call an AI ethics policy back in 2018 and it guided us well through the years so this is really you know there's all these things Richie that change all day long right the tech changes the llm changes the tools change but what shouldn't really change our values like how do we think about the world how the world looks in AI age uh and what is important to us when we design AI into our workflows and applications and and that is also something that we are continuously evolving uh and that's also part of one important success metric um that we're always sticking and staying true to our values uh when we design specifically generative AI uh into into our apps okay so I I like that your sort of main Judgment of all criteria for successes like your shipping AI products and your customers appreciate those um I'm Dr like in more depth can you talk about like uh Japanese specific metrics or targets that are use to evaluate your success as a chief AI officer well we obviously want to get as much customers to adopt our things uh um they're there in total I mean overall what I can just share is we have already mean AI overall is not a new topic for sap um we have roughly 27,000 Enterprise customers right around the world who are using our AI capabilities uh on a on a regular basis and uh yeah of course we our ambition is to heavily uh continue that growth from an adoption perspective in the years to come and specifically with with generative AI okay and it seems like you've got a lot of different uh products and projects on the go um can you talk me through how you prioritize which AI projects are going to be most important prioritization is always on um from from a value perspective so what has the highest value and there could be multiple things right it could be potential Topline impact for a customer right in particular if you think about gen the the usual gen scenarios in sales and services or marketing um so front office related roles could be bottom line improvements cost of good Souls improvements um through through generative AI um or just simply as we target that with Jewel to re think the way how people interact with the system in a way more delightful and easy fashion compared to you know rather classical click through all the uis to accomplish your task um um um fashion and that is usually the way how we how we um evaluate the scenario so when we go through the scenarios we are always looking at it from a what's the return on investment from a customer perspective so like what is really the benefit uh the that that helps the customer to do something faster or easier right or helps them to achieve more with less so those are always the the the questions that we ask already very early in the product life cycle before we go further down the road in order then to implement and spend our resources uh on on on on on those cases and this is how we run it for the most part okay so um the three things you mentioned there were improvements to Top Line so increasing revenue and then improvements to the bottom lines it's cost saving and then uh working better with your software um so I guess it's a customer experience Improvement can you go into more depth just to explain to the audience like uh so what sort of projects are going to help improve Revenue what sort of projects are going to help save costs and uh and yeah what sort of benefits you get from working differently with your software so just give you a couple of examples right that we that we are having um I mean one of the more classical scenarios that we have been just just to draw on a few numbers um that we have been doing for decades is data entry in a system right there's still across all the different business processes there is still like tons of paper and with paper I also don't mean like printed paper but you know email and PDF and digital paper is still paper and and still there's like a plethora right of of processes that require you to tediously manually enter all of those things right into into transactions into into screens right and just transmit basically what's on paper into that system and I think there's a lot there's a tremendous amount of potential to just give you a few numbers alone and and Conquer for example just with B2B in the background we are processing like somewhere between in the range of 60 to 100 million invoices right in a fully automated fashion for example right and it's just in the system fully fully itemized right they're just in there there's no manual eror prone and tedious work just to key those key those in and every body who has filed an expense report exactly knows uh how tedious that sometime sometimes can be and we can save a hell lot of effort with with with and and and and money by that right in a in a high triple digit million uh uh number range um we also look for example into shared service center right think about accounts payables for for example or accounts receivables if you have a large shared service center where you know all the various complaints let's say for example accounts payables right you have all your suppliers and they are complaining because you may have not paid them in the in the contractually uh uh agreed on times because may be of quality issues or what does whatever whatever right blocks the payment to the supplier and you easily depending on your size of the company you can like have hundreds thousands of these cases on a daily on a daily basis yeah and then of course it's starts with simple things like oh how can I catch up within with the threat and the discussion that was already happening via email maybe with that supplier that imagine there's a new person looking at that thread and generative AI instead of reading all that emails helps you to just catch up with that threat in like virtually no time right versus reading 10 20 minutes per case through that email and then you get suggestions what you do with it right you can say like okay maybe you do a do a recommendation maybe give a voucher or give some more time or maybe give certain discount or all those things which I would be then recommended bya Jewel and then once you have to resolve that problem of that ticket it then also of course helps you for example to generate an email and not just a email uh like a standard thank you email or we solve that email but one that is specifically written with the business context in mind so having the reference to the invoice number maybe to the purchase order right so that also the supplier has a good chance to reconcile it again back in their business uh much faster and much easier so it's not about creating a PL with email but really one with with context that usually if you would craft this manually getting all those fields out and so on the email can easily take you I don't know 20 30 minutes to to write and now we can just do it in in seconds right and multiply that with the volume of cases that's a that's a huge timesaver and it's not only a huge timesaver it will also help right to improve either your supplier uh experience right with your suppliers because you're reacting faster you're resolving the cases faster and know accounts receivable side of course also helps with the customer experience because obviously customers will be much happier because you resolve their cases faster too and yeah those are maybe two examples um that that I I can share um I think that are relatable um that maybe that are not too deep in the in the business process world yeah absolutely um it always feels amazingly clunky like how much effort it takes just to either pay money to another business or receive money from a business and so just being able to automate that that just seem like an ideal use case for AI speeding things up um all right so can you talk me through what are the big challenges with your role I think overall one of the big challenges that that we deal with every day is how can we absorb the massive change and the massive transformation that is happening at this to be honest unprecedented speed right I mean we had some some other huge technology disruptions before you know everybody always relate Compares like generative AI what's currently happening with the Internet or What's happen with mobile or the introduction of the microchip and the PC and um the difference is all those Trends were maybe as disruptive but they were not as fast uh as this currently happen because all the infrastructure is there or lots of infrastructure at least is there and it's so exci accessible and you know taking that in and determining what are the right products build but then also helping our customers at scale right not just in a certain Market or for a certain pocket of customers that's simple that's that's usually easy but really scale it uh throughout all the various departments within sap but then also reach all the customers right with with with the same narrative with the same message right and also keeping them uh up to date is is really a challenge I just had a just to give you an example I just had a partner meeting today and they just told that Philip you need to help us to keep up with this with this pace right it's it's just too fast that's on the one hand side it's a it's a good problem to have but it's also a clear challenge right because it's it's it's pretty tricky to everything that happens on the tech side right to immediately absorb build the right products and then enable every customer and tell them look this is this is the way how we how we design it so doing that at scale for like hundreds of thousands uh of of Enterprise customers is a big challenge I'm sure certainly keeping up the pace of AI developments um is a challenge for everyone so I'm wondering uh what's your solution to this do you have any advice on how to keep up with the the that's a fun question but I also have I think I have a little bit of an unconventional answer to for you so first of all I read a lot of things myself um so it helps a little bit that I'm still an an engineer myself um so I go into many things also over the weekend um I'm trying out many things some of those large language models not some of them I try them all of them myself um try to run them locally as much as possible uh think of some of the open source models like llama right or uh the the mistal models um to and and and and then basic and of course read all the read and hear podcasts like data frame for example and and others to keep up to date but also you know relate a little bit like different opinions different point of views on on on on what people think about it and then what I basically do is not just hearing those things and trying to understand it for myself um but I sit down basically every week on on on on on on on the weekend and I write all of that stuff down uh in an email and that goes out to thousands of sap employees it's basically a voluntary subscribe to there's always a link hey if you want to if you don't want to receive this anymore click here if you want to receive it click there uh and luckily I get more click there than click here things and um it meanwhile reaches a couple of thousand uh sap employees on the weekly basis and it's not just a rundown or write down of all those things but also actually it's like it's like a a big action item like hey have you seen this and in this technology there's this new model please please evaluate it deeper it looks good to me I've tried to following things out I think that's helpful for this service I think it's helpful for that service or when there is something uh happening in the market that may relate to some of our products right either on the technology side or on the application side and say like hey dear Pier L1 leader please check this out I think you should do a deeper dive on what that means and whether we can incorporate that of it's of any use uh and it's like a it's both like a rundown or breakdown of all the things that happened in this week plus say and hey here's an action item please come back uh next week and and please let me know if there's something that's that that's useful to you and you know that kind of process helps to not only digest and and by writing it down again but also uh to to Really you know reflect on where does this belong to in the company and and and and figure out who should be on point right to evaluate whether that technology or that tool or whatever is coming out or that research paper also read a lot of research papers obviously um and and then to figure out what what that would mean and if we can incorporate those things within our our Solutions somewhere okay actually I have to say I really like that approach so when you read something interesting you then think well who else in my company is this going to be relevant to so you can say okay this is going to be great for this service or this product and and that way it actually gets used rather than just EX translate right what this whole thing is not just oh here's the rundown think for yourself but here's already I think there's an anchor Point here right there's an there's an IDE concept and I think you really should take a look uh and and that helps a lot that people then really take this more seriously and say like okay well then I take a look and maybe it sometimes also turns out I was wrong that's fine right and and the approach uh doesn't work because it's maybe not yet mature enough um we had this a couple of times people came back and then said well yeah we tried it but um maybe version two let's see um that also happens but but still they they expose themselves to they they gutten know that and obviously this is part for me of this whole organizational learning that needs to happen in order to stay up to date with with what H what is happening uh so if you could go back to when you first started this role uh what advice would you give to yourself I think it's always important to stay hungry and and and and and foolish uh and you know try all try out all these things but you know it also can get daunting sometimes and in particular in this fast-paced environment that we are in and I can only give this advice to to everyone to just just just just continue there there will be also lots of stressful and painful days um but I think overall if you can you can train your resilience in the current times quite well and and so far I I think the the reward the reward uh is much higher um bottom line and yeah if I were just g go back say like yeah know what you're subscribed to know what you're up to but then also have the resilient and resilience and the patience to to to work it through all right super so uh I have to say you weren't telling me G role to be a to yeah you need a lot of resilience is a lot of pain here but uh I like that there's some good rewards with the role as well um okay so uh can you tell what you're most excited about in the world of AI at the moment I think just top of my mind right now is uh I think just last week um the is the the release of how do I pronounce this is U udio or something because I'm also just on my personal level when it comes to AI progress because I'm a kind of want to be musician for 20 years um I think we just reached the next leap in terms of Music generation so that is something that is like it's like extraordinary to see knowing what it takes also you know to play yourself and create and design and playing music for for years um but no I think overall it's just exciting to see really that you know with AI in general I think we are at the Tipping Point of a of of an entirely New Century and being at the having the privilege right to be on the Forefront of of and and you know being able to influence and design also uh both in a relevant but also responsible way this technology for Enterprises around the world right I mean the the largest companies on this planet rely on sap and I think simply the impact that we can create with that again in irrelevant but at the same time responsible way that is this just mindboggling on the impact that this can create in the next years to come so this is this is what what motivates me every day uh because it's it's really really impactful the work that uh that that that we can do okay uh yeah you're right there's so much amazing stuff going on I would also like to Second the idea of having AI generated music it's gonna be a brilliant thing so I was think like it would be kind of nice to be a rock star but also I have zero musical Talent so if if technology can bridge that Gap then there so much the better but I I don't think that everybody would going to be a rock star right because while it's impressive right um the end of the day there's still always some you know music and and this is something where I honestly believe Jenny I will never take this away you know music also programming right these are more like liberal arts than you know just mathematical things and you know there's a big difference between a solid and well- constructed song and a song that touches people and and I to be honest I think this will never go away um yeah okay maybe my wrck our aspirations been dashed once again um all right so do you have any final advice for aspiring Chief AI offices I think the chief AI officer for the most part needs really a heterogeneous set of skills um so I think on the one hand side obviously it helps a lot to you know uh be knowledgeable uh in in Ai and know the technology you don't I don't think you have to be the the top most expert in that domain like 10 years data science right and and then written tens of uh uh research papers like with Google Deep Mind and others um but I think it's in particular the combination of skills right you need to understand the technology well enough in order to understand its implications and what that means where the market is going and combine that with the skills on how to identify the right scenarios do a lot of St holder management come up with the right architecture uh find the right messaging and narrative from a marketing perspective uh uh determine how you can actually also you know from a from a cost but also from a from a from from a revenue or sales perspective right relate that so that you come up with a viable product so all these various Dimensions I think are critical as a chief AI officer to be really successful at the end of the day so it really needs a I think a well-rounded profile right of all these various uh things in order to bring those Concepts um um together so I can um I can only recommend aspiring Chief AI offices to really look at this topic not purely from let's say one angle like let's say technology for example but really read and and and educate yourself in a holistic uh fashion with all the various aspects in order to be successful I think that is critically important to bring all those various Concepts really together in the in in the right manner Okay so really broad set of skills uh it sounds like this gonna be a role for generalists uh but you also need uh some pretty high aspirations I guess if you can bring all those teams together all right super uh thank you for your time philli this is very insightful stuff no thank you so much Richie for having me it was was a pleasure thank you so much for having me on the show\n"