help large enterprises deploy AI responsibly across their core business operations

Anthropic, Blackstone, Hellman & Friedman, and Goldman Sachs announced the formation of a new AI services company

52.5% reduction in hallucinations

The one real underlying asset, Workday's trillion-transaction dataset, is thinner than it sounds; what actually matters at runtime is how data connects to workflows, permissions, and integrations, and every layer of that stack is now a liability.

When customers renew at close to 100% every year, it's usually read as a sign the product is delightful. In Workday's case, it's a sign of something else: leaving is close to impossible.

This dynamic forces a brutal new discipline in how enterprises deploy capital and architect their internal workflows.

Our professionals are using Codex to move from static requirements to working solutions in hours, not weeks. It's enabling rapid prototyping, real-time workflow redesign, and faster iteration across the development lifecycle.

Today, those partners include Accenture, Capgemini, CGI, Cognizant, Infosys, PwC, and Tata Consultancy Services (TCS).

Companies are using Codex across the software development lifecycle. Virgin Atlantic is using it to increase test coverage and increase team velocity - reducing technical debt and improving performance.

The compliance-driven buyers improvising local AI out of retail Mac Minis because the product they need does not exist.

Claude is now being deployed to NEC Group employees around the world

over 100,000 customers now run Claude on Amazon Bedrock

over 100,000 customers now run Claude on Amazon Bedrock

Admins can also manage who has access to use, build, and share agents.

The interest comes as Anthropic's annual revenue run rate has surged to about $30 billion, driven by strong demand from enterprise customers using its AI tools for coding, cybersecurity, and automation.

ChatGPT has 900 million weekly users, which means employees already know how to work with it. For enterprises, that reduces rollout friction and accelerates the point where every employee can delegate tedious tasks.

Building on our consumer strength, enterprise now makes up more than 40% of our revenue, and is on track to reach parity with consumer by the end of 2026.

Microsoft Copilot, which leads paid AI usage among both work-oriented and personal-oriented users, illustrates this dynamic: its prevalence likely reflects bundling with Microsoft 365, a product widely deployed in workplaces through enterprise licensing.

76% among users with employer-provided subscriptions. As we would expect, paid access, especially when provided by employers, is associated with more intensive workplace use.

This level of penetration in such a short period of time is remarkable since Fortune 500 enterprises are not known to be early adopters of technology. Historically, many startups had to initially sell to other startups to get early momentum, and it was only after a few years that a startup would be able to land its first enterprise contract.

Based on our analysis, **29% of the Fortune 500 and ~19% of the Global 2000**are live, paying customers of a leading AI startup.

Based on our analysis, **29% of the Fortune 500 and ~19% of the Global 2000**are live, paying customers of a leading AI startup.

29% of the Fortune 500 and ~19% of the Global 2000 are live, paying customers of a leading AI startup.

Shachar led the Amazon GuardDuty product, scaling the business to over 80,000 customers.

Because of this, teams keep rebuilding the same integration layer. Even within the same company, similar integrations are often implemented multiple times in arbitrary code, leading to security risks, lack of traffic observability, and duplication of work.

They intentionally deploy two or three AI tools for the same use case. Not because of indecision—but by design. Redundancy is policy.

Anthropic says Managed Agents is designed to cut the time it takes to move from prototype to production from months to days, with early adopters like Notion, Rakuten, Asana, Vibecode, and Sentry already using it across coding, productivity, and internal workflow automation.

gpt-oss-20B (high): 0.7%

Gemma 4 models undergo the same rigorous infrastructure security protocols as our proprietary models.

in 2024, 47% of AI solutions were built internally and 53% were purchased; today, 76% of all AI is purchased rather than developed in-house.

in 2024, 47% of AI solutions were built internally and 53% were purchased; today, 76% of all AI is purchased rather than developed in-house.

over 500 business customers were each spending over $1 million on an annualized basis. Today that number exceeds 1,000, doubling in less than two months.

Sarah Anne Bendall

to ensure a competitive marketplace for publishing through enterprise publishing systems

it is this architecture, the one which is in the heads of those writing the code, that is the most important. In adopting this decentralised approach, where the practice of architectural decision-making is much more dispersed, this problem is in many ways, mitigated

The same thing applies with lead assignment rules Salesforce – you can define which users will be assigned leads that come from your website and which users will be assigned leads that come from social media.

Dafür wird der Wissensgraph um geeignete Tools erweitert. DasTechnologiespektrum reicht hier je nach Strukturiertheitsgrad der Daten von Methodender semantischen Textanalyse (vgl. [6]) über das Parsen von regulären Ausdrücken(s. Abschn. 6.4.2) bis hin zum (teil)automatischen Mappen mithilfe von Transforma-tionsvokabularen (z. B. D2RQ in [7], R2RML)

Verbesserungspotenzial im Bereich der Graph-Visualisierung, des Authorings von Ontologien und Regeln und der einfachen Anbindung weiterer Datenquellen.

Für eine noch schnellere Verbreitung im Unternehmensumfeld müssen die zugrunde liegenden Technologien jedoch zugänglicher für Nicht-Techniker werden.

Projektgraphen um die Fähigkeit erweitert, dem Projektleiter basierend auf seinen beschreibenden Texten relevante Themen und Technologien zur Übernahme vorzuschlagen.

Darüber hinaus ist ein wichtiger Trend Linked Data im Unternehmensumfeld zu etablieren, um eine neue Generation semantischer, vernetzter Daten-Anwendungen auf Basis des Linked Data Paradigmas zu entwickeln, zu etablieren und erfolgreich zu vermarkten. Im BMBF Wachstumskernprojekt „Linked Enterprise Data Services“ entsteht hierfür beispielsweise eine Technologieplattform, die es Unternehmen ermöglichen soll, neue Dienstleistungen im Web 3.0 zu etablieren.

Der Hauptanwendungspartner für die hier beschriebenen Lösungen war und ist der Sie-mens-Konzern. Die Lösungen wurden durch das KI-Start-up Giance, eine deutsch-chinesi-sche Ausgründung des DFKI, für den chinesischen Markt angepasst und weiterentwickelt.

Unsere Global Enterprise Intelligence (GEI) Platform eignet sich nicht nur zur Beobachtung von Zulieferern, sondern wird auch in ande-ren Bereichen eingesetzt, in denen Firmen beobachtet werden müssen wie z. B. Wettbewer-beranalyse, Partnerbetreuung, Key-Account-Management oder Portfolio- Management.

Knowledge Graph Check & UpdateMithilfe der Neo4J-Graphdatenbanktechnologie werden für die Anwendungen Wis-sensgraphen aufgebaut und ständig um neue Relationen und Eigenschaften der beob-achteten Firmen ergänzt. Die Wissensgraphen dienen nicht nur der Visualisierung der Ergebnisse, sie werden auch zum Entity Linking und zur Erkennung von bereits be-kannter Information verwendet

Der im Projekt „Smart Data Web“ erstellte öffentliche Teil des Wissensgraphen wurde zudem zum Aufbau eines Siemens-internen Corporate Knowledge Graphen genutzt. Dazu wurden relevante Teilmengen des öffentlichen Wissensgraphen extrahiert und in das ge-schützte Siemens- Netzwerk transferiert. Die internen Datenbanken von Siemens wurden nach RDF konvertiert und zusammen mit dem SDW KG in eine geschützte Datenbank geladen. Weiterhin wurden vom Anwendungsfall getriebene Abfragen erstellt, welche in-terne und offene Daten kombinieren. Der Corporate Knowledge Graph (CKG) ermöglicht eine einheitliche, konsistente und elegante Verknüpfung interner und externer Informatio-nen, ganz im Sinne einer „Enterprise-Intelligence“-Lösung. Über den CKG können Infor-mationen, im konkreten Fall zu Zulieferern, aggregiert und konsolidiert abgerufen und für die Einkaufsabteilungen von Siemens dargestellt werden. Dabei werden interne Kennzah-len, z. B. zum Projektvolumen und zu Bewertungen einzelner Lieferanten, mit aktuellen, automatisch gesammelten, firmen-, produkt- und standortbezogenen Ereignissen aus Nachrichten und anderen Textdatenquellen verknüpft, sodass die Anwender eine Gesamt-sicht auf entscheidungsrelevantes Wissen erhalten

Enterprise Knowledge Graphs (EKGs) mightbe considered as an embodiment of LED

Sören Auer

The unified approachhas the advantage, that the enterprise has more control overthe data and quality, and the data querying is significantlyfaster.

REFERENCES[1] C. Bizer, J. Lehmann, G. Kobilarov, S. Auer, C. Becker, R. Cyganiak,and S. Hellmann. Dbpedia-a crystallization point for the web of data.Web Semantics: science, services and agents on the world wide web,7(3):154–165, 2009.[2] D. Calvanese, M. Giese, D. Hovland, and M. Rezk. Ontology-basedintegration of cross-linked datasets. In Proceedings of the 14th Interna-tional Semantic Web Conference (ISWC). Springer, 2015.[3] X. Dong, E. Gabrilovich, G. Heitz, and W. Horn. Knowledge vault: Aweb-scale approach to probabilistic knowledge fusion. In Proceedingsof the 20th ACM SIGKDD international conference on Knowledgediscovery and data mining, pages 601–610, 2014.[4] P. Frischmuth, S. Auer, S. Tramp, J. Unbehauen, K. Holzweißig,and C. Marquardt. Towards linked data based enterprise informationintegration. In S. Coppens, K. Hammar, M. Knuth, and et al., editors,Proceedings of the Workshop on Semantic Web Enterprise Adoption andBest Practice (ISWC 2013), 2013. CEUR-WS.org, 2013.[5] R. Isele and C. Bizer. Active learning of expressive linkage rules usinggenetic programming. Web Semantics: Science, Services and Agents onthe World Wide Web, 23:2–15, 2013.[6] L. Masuch. Enterprise knowledge graph - one graph to connect themall. 2014.[7] P. N. Mendes, H. Mühleisen, and C. Bizer. Sieve: Linked data qualityassessment and fusion. In Proceedings of the 2012 Joint EDBT/ICDTWorkshops, pages 116–123, 2012.[8] J. Michelfeit, T. Knap, and M. Neˇcask `y. Linked data integration withconflicts. arXiv preprint arXiv:1410.7990, 2014.[9] A.-C. Ngonga Ngomo and S. Auer. Limes - a time-efficient approachfor large-scale link discovery on the web of data. In Proceedings ofIJCAI, 2011.[10] N. F. Noy. Semantic integration: a survey of ontology-based approaches.ACM Sigmod Record, 33(4):65–70, 2004.[11] T. Pellegrini, H. Sack, and S. Auer, editors. Linked Enterprise Data.X.media.press. Springer, 2014.[12] A. Schultz, A. Matteini, R. Isele, P. N. Mendes, C. Bizer, and C. Becker.Ldif-a framework for large-scale linked data integration. In 21stInternational World Wide Web Conference (WWW 2012), DevelopersTrack, Lyon, France, 2012.

In general, a federated approach will be advan-tageous if the enterprise aims to continuously ingest updatesand new additions from public LOD sources.

Nevertheless, acertain overhead for query expansion and entailment regimesis required.

Enterprise Knowledge Graphs

Areas of Integrated Governance

"Off-line" vs "On-line". The RAT's focus is to get to a final state, and then ship it, all at once. During the working process, the thing we're working on is "off-line". It's not in the field and no one is using it

In all cases, the surviving monarchies of Southeast Asia have power and influence that potentially or in reality exceed that described in constitutional terms. This has come about chiefly because of the continuity of the archaic sacred and cultural symbolism of monarchy, which the monarchs themselves have cleverly perpetuated—as well as the patronage derived from their considerable wealth.

塔塔首席數字官C.R. Srinivasan表示：「《發展周期》像是對企業發出的警告，提出了由於革新的出現組織中不同層面開始浮現的『理想與現實』間的差距，他還表示：「這種差距表明，企業決策者和各個部門主管應該主動向企業 CEO提出其面對物聯網和人工智能技術時遇到的困難。」

Inputs: the investment dollars and employee time devoted to innovation, along with the number of ideas that are gener­ated internally each month or sourced from customers, suppliers, and other out­siders. Throughputs: the number and quality of ideas that enter the pipeline after initial screening, the time it takes for those ideas to move from concept to proto­type to reality, and the notional value of the innovation pipe­line. Outputs: the number of innovations that reach the market in a given period, the percentage of revenue derived from new products and services, and the margin gains that are attributable to innovation. Leadership: the percentage of executive time that gets devoted to mentor­ing innovation projects, and 360-degree survey results that reveal the extent to which execu­tives are exhibiting pro-innovation behaviors. Competence: the percentage of employees who have been trained as business innovators, the percentage of employees who have qualified as innova­tion “black belts,” and changes in the quality of ideas that are being generated across the firm. Climate: the extent to which the firm’s management processes facilitate or frustrate innovation, and the progress that is being made in remov­ing innova­tion blockages. Efficiency: changes over time in the ratio of innovation outputs to inputs. Balance: the mix of different types of innova­tion (product, service, pricing, distribution, operations, etc.); differ­ent risk cate­go­ries (incremental improvements versus speculative ventures); and differ­ent time horizons.

an environment unlike anything they will encounter outside of school

institutional demands for enterprise services such as e-mail, student information systems, and the branded website become mission-critical

This has much in common with a customer relationship management system and facilitates the workflow around interventions as well as various visualisations.  It’s unclear how the at risk metric is calculated but a more sophisticated predictive analytics engine might help in this regard.

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

Competitive Enterprise Institute

“An individual building, the style in which it is going to be designed and built, is not that important. The important thing, really, is the community. How does it affect life?” I.M. Pei

Engineers who worked on a lot of open source projects had high levels of creativity

Developers felt more ownership over their work, and pride in it

Open source developers work well together because of their similar ways of thinking

Peer pressure from GitHub—having their name on a project—was a big motivator for engineers to work harder and not let the community of users down.

If they leave, they're likely to keep working on the project, so you're still getting value for free!

Any contributor to our open source projects is already familiar with a bit of software that we use internally and would require less training if they joined the company.

suffers from an over protective legal organization

respecting open source licenses to making it easier for engineers to open source code and ensuring we’re giving back to the open source projects we depend on