0:01 I'm Ena freed Chief technology
0:04 correspondent at axios actually had a
0:06 dream last night I was hosting SNL so
0:07 this is probably as close as I'm going
0:10 to get um if you haven't subscribed to
0:13 my newsletter I write our daily AI plus
0:15 newsletter you can go to axios.com
0:18 newsletters sign up for mine Jims miks
0:21 all the good stuff um I'm really excited
0:23 uh that we're GNA have another great
0:25 conversation around where really are we
0:28 in this AI moment huge moment of change
0:29 I don't need to tell anyone that but
0:31 also you know I've been covering Silicon
0:34 Valley for 25 years tremendous amount of
0:36 change I've never seen the actual
0:39 technological change happen as fast but
0:41 then right on top of that we have yet
0:42 another hype layer that I'm very
0:44 familiar with and so it's really hard
0:47 when the technology change is this real
0:49 and at the same time there's so much
0:50 hype so we're going to have a great
0:53 discussion one last uh housekeeping note
0:55 if you haven't signed up for our last
0:57 event of the week um it's taking place
1:00 at the c3.ai booth uh which is close to
1:02 the Congress Center on the prominade
1:04 I'll be interviewing Eric Bolson and
1:07 Nina Singh and today we're gonna talk
1:10 about how investment in infrastructure
1:12 obviously a huge piece of this is
1:14 getting all that massive compute that
1:16 we're going to need and I'd like to
1:18 bring up my colleague John Otto to kick things
1:26 [Applause]
1:30 off good morning everyone uh day four of
1:32 Davos if you can believe believe it
1:34 thanks for for starting uh with us here
1:35 today I'm really excited for for the
1:38 program I'm John AO the GM of axios live
1:40 uh huge thanks to qualcom house our
1:43 venue partner um but programs like this
1:44 are not made possible without the
1:46 support of our Underwriters and and
1:49 partners and so uh like today in this
1:52 morning um mgx and mubadala Investment
1:54 Company have been a huge supporters of
1:56 us today so I'm excited to uh introduce
1:58 to the stage Chief investment officer of
2:02 Technology at mgx Osman come on up
2:05 sir and Deputy Chief Deputy Chief
2:08 strategy officer admad Investment
2:10 Company Mark Andi [Applause]
2:13 [Applause]
2:16 Mark all right um so let's start off big
2:20 picture here mubadala uh supported the
2:23 the launch of mgx and and really want to
2:24 understand a little bit more for the
2:25 audience here what's the relationship
2:27 like what's the the working relationship
2:29 with with both groups thank you very
2:31 very much joh and good morning everybody
2:34 pleasure to be here maybe a a quick
2:36 intro on mobad for those that don't know
2:38 mad we're Abu Dhabi based Global
2:41 Investment Company portfolio size 330
2:44 globally Diversified and the way we
2:46 invest we invest with top tier Partners
2:49 both directly and indirectly in teams
2:51 and sectors and geographies where we
2:54 have deep convictions things like
2:56 technology where we deployed capital in
2:58 semiconductor and software over the past
3:01 10 years and Healthcare Life Sciences
3:04 also in the in the past 10 years clean
3:07 energy and and and what happened over
3:09 the past uh couple of years with that
3:12 inflection point of gen the acceleration
3:16 a lot of thematics in the AI space we
3:21 decided to have a dedicated focused team
3:25 uh vehicle to look at the AI space and
3:28 go at the speed that that space actually
3:32 requires we have have built tremendously
3:36 fantastic relationships Partners access
3:38 depth of expertise across the 20 years
3:41 of capital deployment we've been doing
3:45 but that space in particular requires
3:49 dedication focus and active uh
3:51 deployment I'm sure that my colleague
3:53 Ali is going to speak a lot about mgx
3:56 and the cool stuff that we're doing but
4:00 aside from the the mgx uh story The
4:01 thematic is also driving a lot of
4:03 acceleration on the other thematic where
4:06 mubadala is involved so we continue to
4:09 push on both fronts dedicated the AI
4:12 ecosystem the other areas as well and
4:13 certainly benefit from that close
4:16 proximity and collaboration and ali uh
4:18 talk to us a little bit more mgx is
4:21 strategic AI investment goals for this
4:23 year um help the audience understand
4:26 that a little bit more and um so you
4:28 know I think Mark said it well we
4:30 basically about 18 months ago took a
4:32 step back and really wanted to redefine
4:34 what it meant to be an investor an AI
4:37 first investor or an AI investor uh in
4:40 an AI native environment um and we came
4:41 to the conclusion that you needed to
4:43 have the ability to invest across the
4:46 entire thematic and ecosystem that meant
4:47 you needed to invest across asset
4:49 classes acoss across risk categories you
4:52 needed to be able to bring scale uh to
4:54 the table that that is very important
4:56 given the capital needs of the space uh
5:00 and so we we built mgx to be an a first
5:02 and AI thematic fund with the ability to
5:04 invest across semiconductors across AI
5:06 infrastructure including data centers
5:09 comput as a service and eventually token
5:10 as a service and intelligence as a
5:14 service as well as the entire um entire
5:15 Tech stack right so thinking about
5:17 Frontier models obviously looking at
5:19 every layer as well as software
5:20 businesses that ultimately will be
5:22 transformed and so as we think about the
5:24 enablers of this technology you know
5:28 taking a 12 to 18 even 20 24mth view the
5:30 infrastructure and the infrastructure
5:31 buildout is going to be a critical piece
5:32 of the puzzle that's really where we're
5:36 focused today and in terms of like where
5:38 do you see the most opportunities for
5:40 applications and industries how do you
5:43 look at at that from from an investment
5:45 standpoint I think one thing we have yet
5:47 to see um from an application
5:50 perspective is really um is is is really
5:52 where Enterprises are pursuing growth
5:55 and growth opportunities rather than
5:57 efficiency in deploying AI applications
5:58 so we're starting to see a lot of
6:00 enterprising we heard this across I mean
6:02 throughout the week a lot of Enterprises
6:04 have started to look at efficiencies and
6:07 optimizing the way they do things today
6:08 leveraging technology in order to be
6:11 more efficient the reality is we think
6:13 that the opportunity is actually how do
6:15 you bring value forward by looking at
6:17 growth how can you serve your customer
6:19 better how can you unlock customer Roi
6:22 as the enterprise we think that we're
6:24 very early days uh with respect to that
6:27 and and mark so while there is every bit
6:29 in ttention around uh what UA has to
6:32 offer there is also every bit of a a
6:35 global opportunity for for AI so in
6:37 terms of like Global presence and Global
6:39 Focus how does MO look with
6:43 that so we we're in many many different
6:45 geographies Let Me Maybe take them uh
6:48 west to east so the US North America the
6:51 us we are 40% of our portfolio is in the
6:53 US we've been building that portfolio
6:55 for quite a while it's been playing out
6:57 extremely well like I said we build
6:59 great relationship great businesses
7:01 they're performing extremely extremely
7:05 well we continue to perceive the us as a
7:08 great Market to attract Capital it's and
7:10 the reasons are pretty known uh the
7:13 depth of the market the quality of De
7:16 flow the partners that we have the the
7:18 capital markets that are extremely
7:20 attractive but also if you just look at
7:23 that drive on Innovation and technology
7:25 is fueling that productivity drive that
7:28 you see translating into a lot of great
7:31 businesses going going from local to
7:34 Global Etc so there's a lot of exciting
7:37 thematics in the US that we continue to
7:40 underwrite the consumer space the new
7:44 consumer space the the the the young
7:47 Generations coming Upstream uh healthc
7:49 care is Big energy is Big the
7:51 infrastructure as a whole is uh very
7:54 interesting and so forth so we continue
7:56 to look at the us as a prime Market if
7:59 we go a little bit more towards the east
8:02 Asia Asia as a as a whole also we have
8:05 more or less 40% of our portfolio in
8:08 Asia including the UAE UAE at the end of
8:11 the day is in Asia is a big growth
8:13 market for us and I'll speak a bit about
8:16 the UAE in a couple of minutes but Asia
8:17 is a place where we've been deploying
8:21 capital for the past 10 15 years we see
8:24 huge growth opportunity on the back of
8:28 Simply demographics just look at the
8:30 pace of growth population young
8:33 Generations coming online think about
8:35 all the reforms that have been happening
8:39 in call it India other places and how
8:42 it's attracting more and more business
8:46 FDI Capital formation Etc so in Asia and
8:48 Asia is Big we cannot speak about Asia
8:52 as one one country or one geography
8:54 India has been a bright spot for us
8:56 we've been doing quite a lot there and
8:58 we continue to uh deploy capital in
9:02 India China we have a capability that we
9:05 build there for the past 10 years um we
9:07 all know the challenges that are ongoing
9:09 and there's a lot of reforms coming but
9:12 we're extremely well positioned in China
9:15 to be able to scale at the right time
9:18 because we are early positioned whereas
9:21 a lot of our peers or other Capital
9:25 deployers have pulled out from China
9:27 there's a lot of other bright spots in
9:28 in Asia that we're also contemplating
9:31 but let me stop on the uee because uee
9:34 is a very very exciting grow story a lot
9:38 of you know how the U has developed over
9:41 the past 20 30 years and has put
9:43 everything in place that is needed to be
9:46 able to continue that forward leaning
9:49 journey of innovation of vibrant economy
9:51 and really focusing on the future
9:54 sectors so we in the U give or take at
9:58 20 25% have great presence but the UEI
10:00 is a place where we're significantly
10:02 deploying Capital as well to continue
10:05 help building the the economy the
10:08 country but also simply because it makes
10:10 sense we are coming up on time we're
10:12 going to get the hook but we're in Davos
10:13 let's pretend like we have a crystal
10:17 ball here I what's one big thing you're
10:20 most excited about for this
10:22 year I think from what we're seeing um
10:24 picking up on your point on applications
10:27 the evolution of the application layer
10:29 um I think will be extremely material in
10:31 2025 uh from some of the technologies
10:33 that we're already seeing being rolled
10:34 out over the course of the next two
10:36 months um it will transform the way we
10:39 work today and the embracing of that
10:41 technology and of the application layer
10:43 by the Enterprise again from a growth
10:44 standpoint rather than an efficiency
10:46 standpoint is really what I'm most
10:48 excited about in 2025
10:51 Mark certainly application and things
10:53 coming real but I'll take maybe a
10:54 different spin I think one thing that's
10:57 going to be very interesting is
10:59 partnership and collaboration and we all
11:04 hear that fragmentation isolationist and
11:06 certainly is going to have an impact but
11:09 throughout my entire week at Davos
11:12 partnership is critical not only to
11:14 navigate that complex world because it's
11:17 very clear that nobody can do it alone
11:19 and at the same time as these
11:21 partnership actually form and
11:23 enhance these Partnerships can help
11:26 shape a bit that World of Tomorrow in a
11:28 different way that these Partnerships
11:29 were were
11:31 in the past so very much looking forward
11:34 to it uh that's all the time we have
11:36 Mark Ali thank you so much for the
11:37 conversation today and a huge thanks
11:40 again for the support mgx and mubadala
11:42 Investment Company so uh Eno will be up
11:44 next for our next conversation thanks
11:45 for joining thank you very much thank
12:23 come on up
12:26 Christian so as I said in my
12:28 introductory remarks you know one of the
12:31 things everyone is trying to figure out
12:35 here in Davos is just just where are we
12:37 with this AI Revolution you know I I
12:38 don't know if you heard me backstage but
12:39 I was saying you know there's real
12:42 change here and it's super fast and I
12:44 think businesses are struggling to keep
12:45 up and I'm sure you guys aren't
12:47 contributing to the hype but I think
12:50 there's also a lot of hype on top um I
12:52 thought maybe a good place to start is
12:54 to talk about what are businesses doing
12:58 today with AI with you what's working
13:00 let's start with what's working what are
13:03 businesses doing today with generative
13:05 where where are you seeing the most
13:07 success the most value driven that sort of
13:08 of
13:11 thing I absolutely I mean look u j and
13:13 so first of all I guess it's very
13:16 important Ena to understand 2023 was the
13:18 year of you know we had the first ideas
13:20 of what generative AI can do for
13:22 businesses not for you know triple
13:25 consumers or in our private life 2024
13:26 was then really the adoption of the
13:30 first use cases so that companies feel
13:32 the value uh but you know these are use
13:36 cases in uh take for example HR yeah you
13:39 white thousands of chob profiles chob
13:41 postings every year of course can be
13:44 taken over we closed which is good
13:46 thousands of contracts by the end of the
13:49 year with customers 800 Pages completely
13:52 now automated refre checks compliance
13:54 checks data security over regulation in
13:57 Europe checked by you know Ai and then
13:59 of course
14:03 sh yeah see yeah you know a completely
14:06 new topic and uh now and look these are
14:08 the use cases where customers say you
14:10 know what that is why I absolutely
14:12 willing to also lean in and adopt this
14:15 new AI use cases now of course when you
14:18 now I mean Grandma next next week
14:21 becomes you know 95 uh when I ask my
14:23 kids to write a poem they ask judge gbd
14:26 and get a good result the problem what
14:27 is still is and this is I guess what we
14:30 now have to solve in 20 25 to not only
14:32 feed into the hype is really you know
14:35 these llm modules they have for good
14:37 reasons no access to business data but
14:40 in businesses you need 100% accurate
14:42 results I mean the poem for Grandma can
14:46 be 95% good and 5% okay that's is
14:48 absolutely fine in business you need
14:50 100% accurate results and where many
14:53 companies still struggle with is I have
14:56 my co-pilot here SCP has its Jewel and
14:58 then we have this and that but you know
15:00 how do I bring this together and because
15:03 only when I have unstructured structured
15:06 data together SCP non SCP data together
15:09 I really understand better with AI My
15:11 Consumer Trends the consumer wishes I
15:14 can thr grow by really detecting earlier
15:17 is this Adidas sneaker now just you know
15:20 more in the in the demand or less and
15:22 then I can adjust my supply chain and
15:25 here we come and here we come to oh and
15:27 here we come to the the agent story and
15:29 I guess that is now the next thing where
15:32 also technology companies like SCP data
15:35 bricks and others need to team up in
15:37 order how can we really build this data
15:39 foundation for AI well and and you hit
15:41 on a really important thing and one of
15:43 the things I've been asking which is if
15:47 the if the llms aren't 100% accurate and
15:49 right now we live in a world where
15:51 they're generally returning information
15:53 to a human being those contracts
15:55 probably someone's giving it a final
15:57 read hopefully but when we talk about
15:59 agents we're talking about more autonomy
16:02 uh is the technology ready to be given
16:05 agentic capabilities and if so what
16:07 types of Agents cuz we've also been
16:09 having a conversation people mean really
16:11 different things when they say agents
16:14 yeah um look it's a good question I mean
16:17 I can share with you two agent agentic
16:19 AI capabilities we are going to launch
16:22 this year I mean first yeah when
16:24 customers using our software to package
16:26 their services their products to price
16:29 it hopefully you know in the right way
16:31 uh to position it at a wi point of time
16:34 so there there's a sales agent you know
16:36 helping you with you know a lot of
16:37 recommendations on what is the best
16:40 price how to package this up how to
16:42 bundle it best to really hit the
16:44 consumer at the right point in time
16:46 that's is a sales agent now the sales
16:48 agent would be great if the sales agent
16:50 can talk to the supply chain agent
16:54 because is this product on stock can I
16:56 deliver on time so that the sales agent
16:59 is not making any kind of promises you
17:01 know which you know the supply chain
17:04 can't fulfill and that is now one of the
17:06 scenarios what we are planning because
17:08 we see there is clear value in it and of
17:10 course is there then still Jewel on top
17:11 who has to orchestrate that that
17:12 absolutely and that's why we are
17:15 investing not in an llm but SCP is
17:17 investing in a knowledge graph in really
17:19 you know having to contextualize the
17:22 data yeah that you can set it in context
17:25 that is very very important and then we
17:27 we need to bring it to adoption yeah and
17:29 uh and that's why we really focus on a
17:33 few use cases not on a 100 but on a few
17:36 push this out and then I I feel this
17:38 will be a big next step in the evolution
17:40 of AI and talk about what you're hearing
17:42 from customers because I think you know
17:44 nobody's saying I don't think we need AI
17:46 or correct me if I'm wrong I doubt
17:48 anyone saying oh we don't need AI but
17:51 what I hear a lot is I don't really know
17:52 I mean they they really don't know how
17:54 to use it they've spent the last two
17:56 years they came to Davos two years ago
17:59 oh my God Chad GP is going to do it they
18:00 had chat jpt right their terrible
18:03 speeches all that the next year they
18:05 were launching lots of Pilots all over
18:07 the place proof of concept I know they
18:12 want to get returns but I also think you
18:13 know the same company that was trying to
18:17 sell them you know a chatbot last year
18:18 is trying to sell them on agents this
18:20 year they haven't even gotten through
18:22 with the last thing H how are
18:24 businesses what are they telling you
18:26 they need from you I mean yeah
18:28 absolutely now I mean look we also have
18:30 to ground ourselves a little bit in
18:33 reality and the reality is I mean 80% of
18:34 our customers are not the large
18:36 Enterprises who are not having a big it
18:38 Department who are not having 100 data
18:42 scientists so what I told our teams is I
18:44 mean we are SC we are running with our
18:46 software the business so we need to
18:48 embed it we need to offer that out of
18:51 the box meaning we have 400,000
18:53 customers 40,000 customers giving us the
18:55 right to train our modules with their
18:58 anonymized data of course and then we
19:00 plug it in yeah so we have all the
19:03 predictions all the automation it's
19:05 coming with the software because often
19:07 times customers just don't have you know
19:10 the team also the Investments yeah to
19:13 take a piece of AI and bring it into the
19:15 context of the business and this is
19:17 where we are sitting at the Nexus and of
19:19 course we need to take make use of that
19:22 we five years back we developed an iot
19:24 scenario here machine learning scenario
19:26 there and then you have a piece of for
19:28 software there customers really
19:30 struggling with the adoption so that's
19:31 very important that it comes embedded
19:33 and then the second piece is you know
19:35 what I mentioned before is also on the
19:37 data side I mean we also have to say
19:39 there's a lot of Legacy still out there
19:41 there are a lot of data silos I mean
19:43 there's always this imagination oh I
19:46 take my sep nonp structured unstructured
19:49 in a data Lake magic happens and somehow
19:50 I have a meaningful data layer for the
19:53 company that is not the reality and then
19:56 for good reasons the llm modules they
19:58 can't read your financials because this
19:59 would be super bad I would be
20:01 uncompliant if all of my end users
20:04 suddenly could read a group pnl of sap
20:06 so this is something what we have to
20:09 solve yeah and this is where we work
20:11 with our customers on hey how can we
20:13 build a better data Foundation how can
20:16 we harmonize the generative AI use cases
20:18 with your business data and these are
20:20 the challenges what custom customers
20:23 today facing and that's why we also
20:26 working a lot under the hood on these
20:28 things I often think tech companies
20:29 learn the most from what they're doing
20:32 internally cuz you know whether it's dog
20:33 fooding their own technology or using
20:35 others technology and I'd love to hear
20:38 you mentioned one use case uh you know
20:40 contracts and some of that stuff I know
20:43 you've used it some in marketing um I
20:46 assume you're using it for coding for HR
20:49 where where are you getting the most
20:51 value what are some things that might be
20:53 unexpected where saap's internal use of
20:56 AI has been interesting yeah I I mean I
20:59 get my weekly report and uh about the
21:01 effectiveness of our AI on our business
21:05 I mean we have to prove sep once's sep
21:08 very important to also have credibility
21:10 and in development I mean now it's
21:12 budget time I mean if our development
21:14 managers like it or don't like it they
21:17 have a 30% you know efficiency gain in
21:19 there in producing more code with the
21:21 same team and it's absolutely doable we
21:25 were I mean a year back with our AI
21:27 pilot for up up where it was probably 5
21:30 to 10% now we absolutely see the the
21:32 code which we produce or AI prod
21:35 producing can absolutely lead to 30 so
21:36 they have to show you they're doing and
21:39 we and we see it and honestly to make a
21:42 a typical developer excited about these
21:44 tools take some time but you can feel
21:46 now also the excitement yeah that they
21:48 have to you know deliver now more output
21:49 but they also have the tools in their
21:51 hand so that is really software
21:53 development and honestly when you look
21:57 at the workforce of SCP be it in HR be
21:59 it in Cloud delivery be it in sales in
22:01 marketing I mean we are doing a massive
22:04 enablement program now I mean you know
22:07 we cannot you know hire you know 100,000
22:09 you know new employees so you need to
22:11 invest into your Workforce and you have
22:13 to think through what is the profile of
22:15 a developer now and how will it look
22:17 like in three years from now and the
22:20 same in my eyes you have to do in order
22:22 to equip your Workforce for this uh you
22:25 know next age of AI where hasn't a AI
22:27 been as effective as you thought what
22:29 are some areas where you've tried to use
22:31 AI where either it hasn't worked as well
22:33 or you said you know I'm sure you tested
22:35 out things that didn't didn't pan out
22:39 the way you thought I have to say um
22:43 what is sometimes more an obstacle also
22:46 inside SCP is um data protection and my
22:49 lovely data Protection Officer yeah so
22:52 um you know I can accept Okay we can't
22:54 do that but what is then the solution
22:56 yeah so on how to use data yeah for
22:58 testing Etc and then we also see
23:00 Regional differences yeah what is
23:02 allowed in Europe what is allowed in the
23:05 US or what is allowed in Asia and we are
23:07 making investment decisions also R&D
23:09 wise based on you know what is where do
23:12 we feel we are over regulated and where
23:14 is actually also more freedom to drive
23:18 Innovation that is a constant battle
23:21 decision uh discussion we always have
23:24 also inside sap now of course when HR
23:27 and finance make up two or 3% of your
23:29 pel the impact is a bit less
23:32 nevertheless the CFO needs AI for
23:35 steering you have very volatile markets
23:38 maybe tariffs are coming inflation then
23:40 you have you know interest rates
23:42 changing and that is where AI can help
23:44 but of course when you look at the pure
23:46 cost I would say also for our customers
23:48 it's typically supply chain it's
23:50 typically Asset Management I mean this
23:52 is where a lot of the CeX and the Opex
23:56 is going in and obviously customers also
23:59 tend to invest exactly in that areas so
24:01 the business itself has got to be also
24:04 changing the way you sell you know one
24:05 of the things I was talking to you know
24:07 some folks at Microsoft and Mark
24:08 bennyhoff and I were actually talking on
24:10 stage you know historically a lot of
24:12 enterprise software software is a
24:15 service per user per month pretty pretty
24:17 well understood model doesn't really
24:19 work in the day where you know we're
24:21 going to have agents one human being
24:24 could be controlling you know 10 100
24:27 agents uh how do you imagine sap will be
24:30 sold differently a couple years from now
24:32 and priced and what other Beyond just
24:34 pricing because that's a packaging thing
24:36 you've you know there was a time we
24:38 bought software in a box and it was a
24:40 one-time license and you tried to sell
24:42 an upgrade so my guess is you can
24:44 navigate that one but how else do you
24:46 see your business
24:49 changing I mean commercially it's
24:51 absolutely a fair question I mean my
24:53 investors asking me the same question um
24:55 do you really want a price per user when
24:58 you want to make this process you know
25:00 lot more productive and will'll be there
25:02 actually less users at the end and I
25:05 feel it was a very good decision that we
25:06 right from the start said for Jew for
25:08 our AI use cases it's consumption it's
25:11 output based because I would say it's
25:13 also then a hard a tough ask also some
25:16 in this um you know environment to say
25:19 oh I charge you a 30% pre premium on top
25:21 of your user price and it was also very
25:23 good for us to learn to have really an
25:26 educated discussion with the customer
25:28 about the value of these AI use cases
25:31 and price them outcome based consumption
25:34 based and so that was for us absolutely
25:36 the right decision so we are already on
25:39 outcome output based pricing of course
25:41 our Solutions the software is still
25:43 subscription based I would say the
25:45 tendency there is also to come to more
25:47 outcome based but you also have to see
25:50 many cios yeah they all love to hear
25:52 about outcome based and but you also
25:54 need to have Security in your it budget
25:57 yeah when you you know overshoot your it
26:00 budget by 20 or 30% your job is also at
26:03 risk so I would say look I mean outcome
26:05 based is absolutely the way to go
26:08 consumption on AI if this will now
26:10 radically change on the software side I
26:12 don't know we only have about a minute
26:14 left what aren't we talking enough about
26:18 here in Davos what is missing from the
26:20 conversation I mean you said it right
26:22 you know I mean at the end you know I
26:24 mean I I would love to say buy a piece
26:27 of AI and technology and you know get
26:30 the value in l i mean that is not not in
26:33 the Enterprise base how it works you
26:36 need to understand how will my business
26:38 will run in the future how is my
26:41 business model changes how how do I want
26:42 to automate a certain business process
26:45 and then drive the change from the end
26:48 user coming and then apply the AI in the
26:50 right way and so I I guess this is
26:52 something what also the technology
26:54 companies need to take care of there's
26:55 always an end user there's always a
26:58 change needed on the business side and I
27:00 get guess this honesty we also have to
27:01 give our customers because otherwise we
27:04 are playing into a hype and we are here
27:07 with aend AI and our customers are here
27:09 and I always remind our teams the Gap
27:12 there is always a certain Gap you know
27:15 until customers can adopt but the Gap
27:17 needs to be well managed and cannot be
27:18 you know like a two or three year time
27:21 frame and that I guess is very important
27:23 that also here in daros we talk about
27:25 how to change the business how to change
27:28 my Workforce in order to apply AI with
27:30 the wide output all right well I want to
27:33 give you one suggestion for an agent sap
27:35 is very involved in the San Jose Sharks
27:38 they play at sap Center don't go there
27:40 my founder gives me a hard time with
27:42 they are not playing really well yeah uh
27:43 they do have a great young player mlin
27:46 celebrini is great anyway we're gonna
27:47 have to leave it there hopefully we'll
27:49 have better news on both the AI and
27:52 hockey fronts next year Kristen Klein
27:53 from sap [Applause]
27:57 [Applause] [Music]
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