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思爱普CFO:人工智能不是昙花一现

WILL DANIEL
2024-06-04

人工智能是科技行业最大的颠覆性技术之一。

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软件集团思爱普(SAP)的首席执行官克里斯蒂安·克莱因(Christian Klein)出席年度新闻发布会。图片来源:PHOTO BY UWE ANSPACH/PICTURE ALLIANCE VIA GETTY IMAGES

在投资界有一种常见的说法,那就是在淘金热期间真正赚到钱的人并不是矿工,而是那些向矿工出售开采所需的镐头和铁锹的企业家。讲述这个故事的投资者通常会提到加州第一位百万富翁的故事,他是一位名叫塞缪尔·布兰南(Samuel Brannan)的商人和报纸出版商,在19世纪40年代和50年代以高价向淘金者出售设备和物资,赚取了大部分财富。有些人甚至会提到李维·斯特劳斯(Levi Strauss),这位德国出生的商人将精美商品进口到旧金山,当然也包括蓝色牛仔裤。施特劳斯从未在采矿上花费一分一秒时间,但他确实从那个时代的淘金热中获得了丰厚的利润。

这种“镐头和铁锹”的说法无疑是有道理的,在当今更关注科技的“淘金热”时代,投资者的决策仍受这种说法的影响,但这也只是故事的一部分。虽然第一批从淘金热中获利的是少数幸运的矿工和那些向他们出售物资和设备的人,但那个时代繁荣所产生的全面影响波及范围广,利润在全球范围内分配。淘金热为第一条横贯大陆的铁路提供了资金,带动加州农业(“绿色黄金”)实现繁荣,加速工业化进程,增加国际贸易,并催生运输和通信创新。

关键在于:对于投资者和全球经济而言,革命性发现或创新都是千载难逢的机遇,其真正的标志往往是长期网络效应;在镐头和铁锹卖家已经赚到钱之后产生的积极的二级和三级影响。18世纪的运河繁荣时期、以及90年代末和21世纪初的互联网时代,都是如此。

随着这十年的人工智能热潮与淘金热的相提并论,投资者多年来一直在寻找这些网络效应的证据,试图将炒作与现实区分开来。许多相当重要的研究和预测都表示,人工智能可以提高生产率,迎来创新时代,甚至可以长期增加国内生产总值,但到目前为止,只有少数几家公司真正从人工智能热潮中获利。

英伟达(Nvidia)和阿斯麦(ASML)等科技巨头出售人工智能革命的“镐头和铁锹”,即人工智能得以运行的底层技术,它们的表现持续优于其他公司,而且似乎有望持续这一势头。但在这些巨头之外,关于人工智能提高生产率和促进经济发展的实际证据却更为微妙。

然而,思爱普可能是人工智能影响日益突出的一个例子。这家总部位于德国沃尔多夫的科技巨头拥有约10.8万名员工,市值达2250亿美元,是全球领先的企业资源规划(以下简称ERP)软件供应商,主要为大型企业提供后台办公引擎。

思爱普的ERP软件正日益转向云计算,有助于供应链管理、会计、人力资源、支出和许多其他业务运营。今年1月,思爱普的主要投资者红杉基金(Sequoia Fund)的投资顾问和分销商Ruane Cunniff LP在致股东的年度信中解释说,“对于在物理世界制造或移动产品的跨国企业来说,思爱普几乎是不二之选。”

尽管思爱普不是一家人工智能公司,也不出售支持人工智能的镐头和铁锹,但却间接和直接地从这项技术的兴起中受益。思爱普首席财务官多米尼克·阿萨姆(Dominik Asam)在接受《财富》杂志采访时解释说,人工智能的繁荣有助于推动公司实现增长,并表示他将致力于利用这项技术提高生产率,削减公司内部成本。

在谈到人工智能的炒作与现实问题时,阿萨姆也表示看好人工智能的前景。他在接受《财富》杂志采访时表示:"这不是昙花一现,也不是炒作,而是科技行业最大的颠覆性技术之一。”

思爱普案例研究:人工智能的增量收益和潜在隐患

巩固云业务转型成果

在思爱普可以看到的第一项网络效益,可能会证明人工智能热潮的持久力,即企业向云ERP服务(基于云计算技术的企业资源规划)转型。阿萨姆表示,人工智能已经助力思爱普将许多ERP客户从本地部署计算转变为基于云计算技术的计算,这意味着对该公司云业务的巨大需求。

他在接受《财富》杂志采访时表示:“人工智能确实正在改变我们从本地部署计算到基于云计算技术的计算的最后一批怀疑论者。他们明白我们必须转向云计算,而且考虑到创新的发展速度,本地部署模式行不通。这一速度太慢,无法消耗最具生产力优势的系统资源。”

阿萨姆表示,用于ERP的人工智能系统的快速发展意味着公司需要不断更新其内部软件,而这无法在不花费高昂的成本情况下现场完成。瑞银集团(UBS)分析师迈克尔 布里斯特(Michael Briest)在接受《财富》杂志采访时支持这一观点,认为人工智能已成为许多公司ERP软件“实现现代化的催化剂”,思爱普的云ERP业务将从中受益。思爱普4月22日发布的财报显示,第一季度云收入增长了24%,当前云积压(CCB)增长了27%,创历史最快纪录。云积压的增长数字代表来年云收入(客户已签订合同),分析师将其视为衡量潜在需求的指标。

新收入机会

尽管思爱普并不是一家纯粹的人工智能公司,但和现在的许多科技公司一样,也在增加人工智能服务,以提高收入,并防止客户跳槽到竞争对手那里。作为业务重组的一部分,思爱普首席执行官克里斯蒂安·克莱因今年1月宣布,公司将向商业人工智能部门投资11亿美元,并为客户提供更多人工智能解决方案。

该公司目前提供一系列人工智能产品,可以帮助完成从任务自动化到跟踪销售业绩、客户洞察等各个方面的工作。阿萨姆表示,思爱普的人工智能产品还将帮助不同的业务部门(例如会计和人力资源部门)更好地进行沟通,以消除招聘、在职人员工薪名册或员工退休等操作中的失误。“例如,如果一名员工离开公司,你必须确保自动删除其在财务系统中的所有访问权限,否则就会出现控制故障,审计员就会过来说,‘那家伙可能篡改了数据。’”他解释说,并认为人工智能将有助于防止这些问题的发生。思爱普甚至提供了一款名为Joule的“人工智能副驾”,将帮助梳理和解释各种应用程序中的数据。

阿萨姆认为思爱普的客户(以供参考,思爱普的客户创造了全球商业总额的87%)需要大量数据才能有效训练人工智能模型,而只有少数几家关键公司可以提供这些数据。首席财务官表示,思爱普已获得"绝大部分"客户的同意,可以使用他们的数据来训练人工智能模型,这为他们在软件中提供人工智能服务提供了巨大机会。

尽管如此,思爱普还未将其人工智能收入单独划分为一个类别,而且该公司目前的人工智能产品在短期内可能不会对营收做出显著贡献。瑞银集团的布里斯特认为,商业人工智能部门是“真正的机会”所在,但可能只是在短期内带来“增量”收入增长。

他说:“如今,在我看来,这更多的是为了推动云迁移。当然,这也有助于客户决定推进现代化进程。但这是一个独立的收入项目吗?让我们拭目以待。我认为还需要更多的证据。”

不过,从长远来看,阿萨姆看好人工智能提升思爱普业绩的潜力。他说:“我们正在开发这些(人工智能)流程,目前有大约30个用例,另外100个用例将在今年年底开发出来,推向一般市场。随着时间的推移,我们会加快步伐。因此,还需要一段时间,你才能真正发现转变。但当发生转变时,就会非常显著。”

提高生产率和利润率

思爱普也在内部实施人工智能,以节省成本和提高员工生产率,并在宣布重组后,逐步加大人工智能实施力度。阿萨姆表示,最终目标是在未来几年利用人工智能实现“成本增长与收入增长脱钩”,并在不大幅增加员工人数的情况下提高生产率。他对《财富》杂志表示:“坦率地讲,在某些领域,我们正在用机器处理能力取代人类处理能力。如果通胀率没有每年大幅上升,机器处理能力实际上更具可扩展性。”

以差旅及费用管理服务SAP Concur为例,思爱普已经部署了一个人工智能系统来响应费用请求。阿萨姆解释说:“该引擎基本上是在复制或取代以前(由人类)完成的工作,即一些人负责检查违反规定的差旅和费用报销。”

目前,员工成本占思爱普成本基础的69%,因此人工智能降低相关成本可能会带来益处。思爱普首席执行官克里斯蒂安·克莱因在公司季度财报电话会议上也强调了多个利用人工智能在内部节省“数亿美元”成本的机会。

瑞银集团的布里斯特指出,人工智能降低劳动力成本的能力最终可能对整个软件行业产生重要影响。他说:"纵观软件行业,每天晚上几乎有一半的收入以工资的形式流失。相对于资本密集型行业而言,这一比例相当高。很多人才都在这些岗位上工作,如销售、开发、财务和会计,因此,这些岗位都将发生转变。”

对于思爱普而言,布里斯特认为,部分劳动力成本的降低"将带来利润增长,因为其产品粘性很高",这意味着客户不太可能因为相关成本而转向竞争对手。

人工智能给收益真正带来影响尚待时日

思爱普近期的表现和未来计划证明,人工智能可以增加企业收入、降低成本和提高生产率,但这项技术的真正拐点可能尚未到来。对于思爱普而言,瑞银集团的布里斯特警告称,随着人工智能收入的增长,“竞争对手不会停滞不前”。他说:“如今出现一波创新潮,初创公司会被高盈利能力所吸引。随着时间的推移,很多产品因竞争过于激烈而逐渐被其他更具竞争力的产品所取代。”

不过,布里斯特表示,尽管这对思爱普来说可能不是好消息,但"可能对全球经济有利"。毕竟,竞争激烈通常会带来创新、降低成本和提高生产率。

此外,虽然已经有证据表明人工智能对思爱普的业务产生了直接和间接的积极影响,但就连阿萨姆也对《财富》杂志表示,人工智能还需要更多的时间才能像许多急切的投资者所期待的那样提高收益数字。以思爱普的规模而言,即使人工智能能够节省数亿美元的成本或带来数亿美元的收入增长,也只能对其利润产生微小的影响。

他预计,像许多革命一样,人工智能的影响在一段时间内不会太明显,但很快就会完全显现出来。他说:“事情实际上正在发生比人们想象的大得多的变化。”

阿萨姆将人工智能的兴起与互联网泡沫相提并论,当时投资者对互联网的热情促使一些无利可图的科技股疯狂飙升,然后出现崩盘,但最终互联网还是带来了收益。阿萨姆说:“如今,这一生态系统的价值是当时人们认为的数倍。所以我认为这(人工智能)将遵循类似的模式。这就是为什么思爱普全力押注人工智能。”(财富中文网)

译者:中慧言-王芳

在投资界有一种常见的说法,那就是在淘金热期间真正赚到钱的人并不是矿工,而是那些向矿工出售开采所需的镐头和铁锹的企业家。讲述这个故事的投资者通常会提到加州第一位百万富翁的故事,他是一位名叫塞缪尔·布兰南(Samuel Brannan)的商人和报纸出版商,在19世纪40年代和50年代以高价向淘金者出售设备和物资,赚取了大部分财富。有些人甚至会提到李维·斯特劳斯(Levi Strauss),这位德国出生的商人将精美商品进口到旧金山,当然也包括蓝色牛仔裤。施特劳斯从未在采矿上花费一分一秒时间,但他确实从那个时代的淘金热中获得了丰厚的利润。

这种“镐头和铁锹”的说法无疑是有道理的,在当今更关注科技的“淘金热”时代,投资者的决策仍受这种说法的影响,但这也只是故事的一部分。虽然第一批从淘金热中获利的是少数幸运的矿工和那些向他们出售物资和设备的人,但那个时代繁荣所产生的全面影响波及范围广,利润在全球范围内分配。淘金热为第一条横贯大陆的铁路提供了资金,带动加州农业(“绿色黄金”)实现繁荣,加速工业化进程,增加国际贸易,并催生运输和通信创新。

关键在于:对于投资者和全球经济而言,革命性发现或创新都是千载难逢的机遇,其真正的标志往往是长期网络效应;在镐头和铁锹卖家已经赚到钱之后产生的积极的二级和三级影响。18世纪的运河繁荣时期、以及90年代末和21世纪初的互联网时代,都是如此。

随着这十年的人工智能热潮与淘金热的相提并论,投资者多年来一直在寻找这些网络效应的证据,试图将炒作与现实区分开来。许多相当重要的研究和预测都表示,人工智能可以提高生产率,迎来创新时代,甚至可以长期增加国内生产总值,但到目前为止,只有少数几家公司真正从人工智能热潮中获利。

英伟达(Nvidia)和阿斯麦(ASML)等科技巨头出售人工智能革命的“镐头和铁锹”,即人工智能得以运行的底层技术,它们的表现持续优于其他公司,而且似乎有望持续这一势头。但在这些巨头之外,关于人工智能提高生产率和促进经济发展的实际证据却更为微妙。

然而,思爱普可能是人工智能影响日益突出的一个例子。这家总部位于德国沃尔多夫的科技巨头拥有约10.8万名员工,市值达2250亿美元,是全球领先的企业资源规划(以下简称ERP)软件供应商,主要为大型企业提供后台办公引擎。

思爱普的ERP软件正日益转向云计算,有助于供应链管理、会计、人力资源、支出和许多其他业务运营。今年1月,思爱普的主要投资者红杉基金(Sequoia Fund)的投资顾问和分销商Ruane Cunniff LP在致股东的年度信中解释说,“对于在物理世界制造或移动产品的跨国企业来说,思爱普几乎是不二之选。”

尽管思爱普不是一家人工智能公司,也不出售支持人工智能的镐头和铁锹,但却间接和直接地从这项技术的兴起中受益。思爱普首席财务官多米尼克·阿萨姆(Dominik Asam)在接受《财富》杂志采访时解释说,人工智能的繁荣有助于推动公司实现增长,并表示他将致力于利用这项技术提高生产率,削减公司内部成本。

在谈到人工智能的炒作与现实问题时,阿萨姆也表示看好人工智能的前景。他在接受《财富》杂志采访时表示:"这不是昙花一现,也不是炒作,而是科技行业最大的颠覆性技术之一。”

思爱普案例研究:人工智能的增量收益和潜在隐患

巩固云业务转型成果

在思爱普可以看到的第一项网络效益,可能会证明人工智能热潮的持久力,即企业向云ERP服务(基于云计算技术的企业资源规划)转型。阿萨姆表示,人工智能已经助力思爱普将许多ERP客户从本地部署计算转变为基于云计算技术的计算,这意味着对该公司云业务的巨大需求。

他在接受《财富》杂志采访时表示:“人工智能确实正在改变我们从本地部署计算到基于云计算技术的计算的最后一批怀疑论者。他们明白我们必须转向云计算,而且考虑到创新的发展速度,本地部署模式行不通。这一速度太慢,无法消耗最具生产力优势的系统资源。”

阿萨姆表示,用于ERP的人工智能系统的快速发展意味着公司需要不断更新其内部软件,而这无法在不花费高昂的成本情况下现场完成。瑞银集团(UBS)分析师迈克尔 布里斯特(Michael Briest)在接受《财富》杂志采访时支持这一观点,认为人工智能已成为许多公司ERP软件“实现现代化的催化剂”,思爱普的云ERP业务将从中受益。思爱普4月22日发布的财报显示,第一季度云收入增长了24%,当前云积压(CCB)增长了27%,创历史最快纪录。云积压的增长数字代表来年云收入(客户已签订合同),分析师将其视为衡量潜在需求的指标。

新收入机会

尽管思爱普并不是一家纯粹的人工智能公司,但和现在的许多科技公司一样,也在增加人工智能服务,以提高收入,并防止客户跳槽到竞争对手那里。作为业务重组的一部分,思爱普首席执行官克里斯蒂安·克莱因今年1月宣布,公司将向商业人工智能部门投资11亿美元,并为客户提供更多人工智能解决方案。

该公司目前提供一系列人工智能产品,可以帮助完成从任务自动化到跟踪销售业绩、客户洞察等各个方面的工作。阿萨姆表示,思爱普的人工智能产品还将帮助不同的业务部门(例如会计和人力资源部门)更好地进行沟通,以消除招聘、在职人员工薪名册或员工退休等操作中的失误。“例如,如果一名员工离开公司,你必须确保自动删除其在财务系统中的所有访问权限,否则就会出现控制故障,审计员就会过来说,‘那家伙可能篡改了数据。’”他解释说,并认为人工智能将有助于防止这些问题的发生。思爱普甚至提供了一款名为Joule的“人工智能副驾”,将帮助梳理和解释各种应用程序中的数据。

阿萨姆认为思爱普的客户(以供参考,思爱普的客户创造了全球商业总额的87%)需要大量数据才能有效训练人工智能模型,而只有少数几家关键公司可以提供这些数据。首席财务官表示,思爱普已获得"绝大部分"客户的同意,可以使用他们的数据来训练人工智能模型,这为他们在软件中提供人工智能服务提供了巨大机会。

尽管如此,思爱普还未将其人工智能收入单独划分为一个类别,而且该公司目前的人工智能产品在短期内可能不会对营收做出显著贡献。瑞银集团的布里斯特认为,商业人工智能部门是“真正的机会”所在,但可能只是在短期内带来“增量”收入增长。

他说:“如今,在我看来,这更多的是为了推动云迁移。当然,这也有助于客户决定推进现代化进程。但这是一个独立的收入项目吗?让我们拭目以待。我认为还需要更多的证据。”

不过,从长远来看,阿萨姆看好人工智能提升思爱普业绩的潜力。他说:“我们正在开发这些(人工智能)流程,目前有大约30个用例,另外100个用例将在今年年底开发出来,推向一般市场。随着时间的推移,我们会加快步伐。因此,还需要一段时间,你才能真正发现转变。但当发生转变时,就会非常显著。”

提高生产率和利润率

思爱普也在内部实施人工智能,以节省成本和提高员工生产率,并在宣布重组后,逐步加大人工智能实施力度。阿萨姆表示,最终目标是在未来几年利用人工智能实现“成本增长与收入增长脱钩”,并在不大幅增加员工人数的情况下提高生产率。他对《财富》杂志表示:“坦率地讲,在某些领域,我们正在用机器处理能力取代人类处理能力。如果通胀率没有每年大幅上升,机器处理能力实际上更具可扩展性。”

以差旅及费用管理服务SAP Concur为例,思爱普已经部署了一个人工智能系统来响应费用请求。阿萨姆解释说:“该引擎基本上是在复制或取代以前(由人类)完成的工作,即一些人负责检查违反规定的差旅和费用报销。”

目前,员工成本占思爱普成本基础的69%,因此人工智能降低相关成本可能会带来益处。思爱普首席执行官克里斯蒂安·克莱因在公司季度财报电话会议上也强调了多个利用人工智能在内部节省“数亿美元”成本的机会。

瑞银集团的布里斯特指出,人工智能降低劳动力成本的能力最终可能对整个软件行业产生重要影响。他说:"纵观软件行业,每天晚上几乎有一半的收入以工资的形式流失。相对于资本密集型行业而言,这一比例相当高。很多人才都在这些岗位上工作,如销售、开发、财务和会计,因此,这些岗位都将发生转变。”

对于思爱普而言,布里斯特认为,部分劳动力成本的降低"将带来利润增长,因为其产品粘性很高",这意味着客户不太可能因为相关成本而转向竞争对手。

人工智能给收益真正带来影响尚待时日

思爱普近期的表现和未来计划证明,人工智能可以增加企业收入、降低成本和提高生产率,但这项技术的真正拐点可能尚未到来。对于思爱普而言,瑞银集团的布里斯特警告称,随着人工智能收入的增长,“竞争对手不会停滞不前”。他说:“如今出现一波创新潮,初创公司会被高盈利能力所吸引。随着时间的推移,很多产品因竞争过于激烈而逐渐被其他更具竞争力的产品所取代。”

不过,布里斯特表示,尽管这对思爱普来说可能不是好消息,但"可能对全球经济有利"。毕竟,竞争激烈通常会带来创新、降低成本和提高生产率。

此外,虽然已经有证据表明人工智能对思爱普的业务产生了直接和间接的积极影响,但就连阿萨姆也对《财富》杂志表示,人工智能还需要更多的时间才能像许多急切的投资者所期待的那样提高收益数字。以思爱普的规模而言,即使人工智能能够节省数亿美元的成本或带来数亿美元的收入增长,也只能对其利润产生微小的影响。

他预计,像许多革命一样,人工智能的影响在一段时间内不会太明显,但很快就会完全显现出来。他说:“事情实际上正在发生比人们想象的大得多的变化。”

阿萨姆将人工智能的兴起与互联网泡沫相提并论,当时投资者对互联网的热情促使一些无利可图的科技股疯狂飙升,然后出现崩盘,但最终互联网还是带来了收益。阿萨姆说:“如今,这一生态系统的价值是当时人们认为的数倍。所以我认为这(人工智能)将遵循类似的模式。这就是为什么思爱普全力押注人工智能。”(财富中文网)

译者:中慧言-王芳

There’s a common narrative in the investment community that says the people who really made money during the gold rush weren’t the miners—but the entrepreneurs who sold miners the picks and shovels they needed to prospect. Investors who recount this tale often point to the story of California’s first millionaire, a businessman and newspaper publisher named Samuel Brannan, who made the bulk of his fortune selling equipment and provisions to gold miners at a premium in the 1840s and ‘50s. Some will even bring up Levi Strauss, the German-born businessman who imported fine goods into San Francisco—including, of course, blue jeans. Strauss never spent a minute mining, but was certainly rewarded by the profits that came with the gold fever of his era.

This ‘picks and shovels’ narrative undoubtedly has merit, and continues to inform investors’ decisions during modern day, more tech-focused ‘gold rushes’—but it’s also only part of the story. Although the first to profit from the gold rush were a few lucky miners and those who sold them provisions and equipment, the full impact of the boom of that era was widespread, and the profits were distributed globally. The gold rush helped finance the first transcontinental railroad, led to a “green gold” farming boom in California, accelerated industrialization, increased international trade, and spawned transportation and communication innovations.

The point is this: the true mark of a revolutionary discovery or innovation—a once-in-a-lifetime opportunity for investors and the global economy—is often its long-term network effects; positive secondary and tertiary impacts that come after the pick and shovel sellers have already made their money. This was true in the canal boom of the 18th century, and during the dot-com era of the late ‘90s and early 2000s.

With this decade’s artificial-intelligence boom drawing comparisons with the gold rush, investors have been looking for evidence of these network effects for years as they try to separate hype from reality. Plenty of respectable studies and forecasts predict that AI can boost productivity, usher in an age of innovation, and even increase GDP over the long-term—but so far, only a few companies have really profited from the AI boom.

Tech giants like Nvidia and ASML that sell the picks and shovels of the AI revolution, the underlying technology that allows AI to operate, continue to outperform and seem on track to continue doing so. But on-the-ground evidence of AI’s supposed productivity-enhancing and economy-boosting impacts outside of these giants has been more subtle.

SAP SE could be one example of AI’s growing prominence, however. The Walldorff, Germany-based tech giant, which has roughly 108,000 employees and a market cap of $225 billion, is the world’s leading provider of enterprise resource planning (ERP) software, essentially providing the back office engine for large businesses.

SAP’s ERP software, which is increasingly moving to the cloud, helps with supply chain management, accounting, human resources, expenses, and a number of other business operations. And as Ruane Cunniff LP, the investment advisor and distributor of Sequoia Fund, a major investor in SAP, explained in its annual letter to shareholders in January, “for multinational enterprises that make or move something in the physical world, SAP is just about the only game in town.”

Although SAP isn’t an AI company, and they aren’t selling picks and shovels that enable AI, they are benefiting from the rise of the technology, both indirectly and directly. In an interview with Fortune, SAP CFO’s Dominik Asam explained that the AI boom has helped drive growth at his company, and said he’s dedicated to using the technology to enhance productivity and cut costs in-house moving forward.

When it comes to the questions over hype versus reality when it comes to AI, Asam is bullish too. “This is not like a blip or hype, but really one of the biggest, if not the biggest disruption in the technology industry,” he told Fortune.

An SAP case study: The incremental gains and potential pitfalls of AI

Cementing the cloud transition

The first network benefit that can be seen at SAP which may provide evidence of the staying power of the AI boom is corporations’ transition to the cloud for ERP services. Asam said that AI has helped SAP transition many of its ERP customers from on-premises computing to cloud-based computing, which means considerable demand for the company’s cloud business.

“AI is really converting the last skeptics we had from the journey from on-[premises] to cloud,” he told Fortune. “They understand we have to go to the cloud, they know that the on-prem model doesn’t work, given the velocity of innovation. They will be too slow, they will not be able to consume the most productive systems.”

The rapid pace of advancement in AI systems for ERP means companies need to be able to continually update their internal software, and that can’t be done on-site without serious costs, Asam said. In an interview with Fortune, UBS analyst Michael Briest backed up the idea that AI has been a “catalyst for the modernization” of many companies’ ERP software, benefitting SAP’s cloud ERP business. And SAP’s April 22 earnings report showed cloud revenue growth of 24% in the first quarter, and current cloud backlog (CCB) growth of 27%, the fastest on record. The CCB growth figure represents cloud revenue for the upcoming year for which clients have already signed contracts, and it is seen as a measure of underlying demand by analysts.

New revenue opportunities

Although SAP isn’t a pure AI play, like many tech companies these days it’s added AI services to bolster revenues and keep customers from jumping to the competition. CEO Christian Klein announced SAP would invest $1.1 billion on its Business AI unit in January as a part of a business restructuring and offer more AI solutions for customers.

The company now provides a range of AI products that can help with everything from the automation of tasks to tracking sales performance, customer insights, and more. SAP’s AI offerings will also help different lines of business—accounting and human resources, for example—better communicate to eliminate errors in operations like hiring, payroll, or employee retirements, according to Asam. “For instance, if an employee is leaving the company, you have to ensure that all access rights in the finance systems are automatically deleted, because otherwise you have a control failure and the auditor will come and say, ‘That guy could have manipulated the data,’” he explained, arguing AI will help prevent these issues. SAP even offers an “AI co-pilot” called Joule that will help sort through and explain data across its various applications.

Asam argued that SAP’s customers—which, for reference, generate 87% of total global commerce—would need huge amounts of data in order to train AI models properly, and only a few key firms can provide that. But SAP has the consent of the “lion’s share” of its customers to use their data to train AI models, and that gives them a big opportunity to provide AI services in their software, according to the CFO.

Still, SAP doesn’t yet break out its AI revenues into their own category, and its current AI offerings may not dramatically contribute to the top line in the near-term. UBS’ Briest argued that the Business AI unit is “a genuine opportunity,” but probably only for an “incremental” revenue increase in the near-term.

“In my view today, this is more about pulling along the cloud migration. And of course, it helps customers decide to modernize. But is it a separate revenue item? We’ll see. I think more evidence is required,” he said.

Long-term, however, Asam is bullish about AI’s potential to lift SAP. “We are developing these [AI] processes as we speak. We have about 30 use cases now…another 100 will be developed for general market introduction throughout the end of this year. And overtime, we will ramp that,” he said. “So this will take some time until you will really see it inflect. But when it inflects, it can be very big.”

Productivity gains and margin expansion

SAP is also implementing AI internally in order to save costs and increase worker productivity, and those efforts were ramped up after its restructuring announcement. Asam said the ultimate goal is to use AI to help with “decoupling cost growth from growth in revenues” in coming years, becoming more productive without dramatically increasing employee headcount. “In some areas, we are replacing, frankly, human processing power with machine processing power, which is actually more scalable if you don’t have the kind of significant inflation increase every year,” he told Fortune.

Take the example of the travel and expense management service SAP Concur, where SAP has implemented an AI system that responds to expense requests. “That engine is basically replicating or replacing the work of what formerly has been done [by humans], where some people have been checking the travel and expense claims against the rules,” Asam explained.

Employees currently make up 69% of SAP’s cost base, so a reduction in related costs due to AI could be beneficial. SAP’s CEO Christian Klein also highlighted multiple opportunities for using AI to save “triple digit millions” internally in the firm’s quarterly earnings call.

UBS’ Briest noted that AI’s ability to reduce labor costs could end up being important for the entire software industry as well. “When you look at the software industry, half the revenue pretty much walks out the door in salaries every night. That’s high relative to capital intensive industries as a percentage of revenue. And a lot of the talent is in these roles, sales, development, finance, and accounting, which will be transformed,” he said.

For SAP, Briest argued that some of the labor cost reduction “will accrue to the bottom line because they have a very sticky product”—meaning customers are unlikely to transition to a competitor due to associated costs.

AI’s true impact on earnings is still to come

SAP’s recent performance and future plans provide evidence of AI’s ability to boost corporate revenues, reduce costs, and enhance productivity, but the true inflection point for the technology may still lie ahead. For SAP, UBS’ Briest warned that “competitors won’t stand still” as AI revenues rise. “There’s a wave of innovation, and startups will be attracted to your high profitability,” he said. “A lot of it will get competed away over time.”

But while that may not be great news for SAP, it is “probably good for the global economy,” Briest said. After all, more competition typically brings innovation, lower costs, and improved productivity.

Also, while there is already evidence of both direct and indirect positive impacts on SAP’s business, even Asam told Fortune that it will take more time for AI to boost earnings numbers in the way many eager investors are anticipating. Even when AI is driving hundreds of millions of dollars of savings or revenue growth, it would only amount to a tiny change to SAP’s bottom line, given the company’s size.

He expects AI’s impact, like many revolutions, won’t be felt too dramatically for some time—but then all at once. “Things are actually inflecting to something much bigger than what people ever thought,” he said.

Asam compared the rise of AI to the dot-com bubble, where investor enthusiasm for the internet drove some unprofitable tech stocks to insane heights before a crash, but ultimately the internet delivered the goods. “Today, that ecosystem is worth multiples of what people thought it would be worth back then. So I think this [AI] will follow a similar pattern,” Asam said. “This is why we at SAP are really fully betting on that.”

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