AI in the Enterprise Lessons from seven frontier companiesContents A new way to work 3 Executive summary 5 Seven lessons for enterprise AI adoption Start with evals 6 Embed AI into your products new models and capabilities. Our Applied Team turns those models into products, like ChatGPT Enterprise and our API. And our Deployment Team takes these products into companies to address their most shapes future products and models. 4 AI in the EnterpriseExecutive summary Seven lessons for enterprise AI adoption 01 Start with evals Use a systematic evaluation process to measure how 
 models perform

DoD Enterprise DevSecOps Reference Design from the DoD CIO – A Summary Content referenced from: https://dodcio.defense.gov/Portals/0/Documents/DoD%20Enterprise%20DevSecOps%20Reference %20Design%20v1.0_Public%20Release security sidecar container CSIAC Webinars - DoD Enterprise DevSecOps Initiative – Nicolas Chaillan presenting https://www.csiac.org/podcast/dod-enterprise-devsecops-initiative/ DoD Centralized Container

development of the architecture precede sprint development. Alternatively, a program can initially use a traditional approach to build the initial increment that meets the baseline architecture requirements processes, and culture often run counter to those in the long-established defense acquisition enterprise. The Agile model represents a change in the way DoD conducts business, and programs must rethink participate in continuous testing activities, and provides feedback on developed capabilities. Enterprise Architect Creates architectures and designs in an iterative manner to ensure that designs evolve

challengers are racing to build and deploy the next layers of AI infrastructure: agentic interfaces, enterprise copilots, real-world autonomous systems, and sovereign models. Rapid advances in artificial intelligence smartphones, IOT devices, robotics, etc. Source: Weiss et al. ‘AI Index: Mapping the $4 Trillion Enterprise Impact’ via Morgan Stanley (10/23) Enabling Infrastructure CPUs Big Data / Cloud GPUs Computing NVIDIA Co-Founder & CEO Jensen Huang @ COMPUTEX 2025 – 5/2567 ‘Traditional’ Enterprise AI Adoption = Rising Priority68 Enterprise AI Focus – S&P 500 Companies = 50% & Rising Talking-the-Talk . Source:

Agile. This frame of reference includes the notions of project, systems, application, investment, architecture, skill set, and accountability. We have, to be honest, made a jumble of these concepts. IT as intangible asset, which I will call – despite some disconcerting connotations of the term – the Enterprise Architecture. The asset view of IT will substitute for the outdated project view in my vision for what modernizations. In the absence of the strangler pattern, we would develop a new system on the modernized architecture and then move the users over to it. The problem is that the users cannot begin using the new

you can find this on the Agile4Defense GitHub page at: https://git.io/JeaOu Enterprise Architecture Enterprise Architecture, the domain of the IT bureaucrats, is the place we must look for the solution overrated. A Better Way – Treat IT as an Enterprise Asset (EA): When we add all of our current IT capabilities together, we arrive at an asset that enables the enterprise to earn future revenues and reduce they have produced. As a result, the code can be developed in a user-centric way and match the enterprise’s needs precisely. Risk is low, because the team is constantly adjusting.  Option 2: Compare

Time in Part 2 Enterprise Architecture: The job of IT leaders is not to execute projects on behalf of the business; it is to steward the asset that is the total of all of the enterprise’s IT capabilities—an robust feedback cycles and flexible decision-making processes, by creating options and grooming enterprise capabilities so that they will be responsive to change, and by demonstrating the value of information Assets: senior IT leadership has the responsibility for stewarding three critical assets: the Enterprise Architecture asset, the IT people asset, and the data asset. These three assets represent the capabilities

Operations to improve outcomes 2. Ch. 9 – Create the Foundations of Our Deployment Pipeline a. Enterprise Data Warehouse program by Em Campbell-Pretty - $200M, All streams of work were significantly behind Releases a. Principle of Evolutionary Architecture – Jez Humble – “any successful product or organization will necessarily evolve over its life cycle.” b. AN ARCHITECTURE THAT ENABLES PRODUCTIVITY, TESTABILITY works at scale 10X or 100X d. USE THE STRANGLER APPLICATION PATTERN TO SAFELY EVOLVE OUR ENTERPRISE ARCHITECTURE i. Coined by Martin Fowler in 2004 ii. Strangler Application 1. Put existing functionality

unprecedented volumes of data across a growing number of sources and formats, data engineering and architecture teams must design systems that not only scale but also deliver real-time access and insights. ensure data integrity, privacy, and governance. To overcome these challenges, data engineering and architecture teams must rethink traditional data infrastructures. The future lies in Real-Time Unified Data scalability across hybrid environments, supporting cloud, on- prem, and edge deployments. Always-on architecture ensuring availability and resilience as business needs evolve. By unifying diverse data workloads

reviews should focus on the relatively small scope of a release and how it aligns to the enterprise architecture. Similar technical reviews can be decomposed to the release level.  DO continuous planning sessions to drive collaboration and strengthen teaming arrangements.  Ensure that once a clear architecture is in place, systems engineers continue to refine it as they learn more from the development