The Submittal Lifecycle Skill: Building One End-to-End AI Workflow

https://getarchit.com/the-ai-policy-bot-for-architecture-firms/Architecture firm leaders often lose valuable time answering the same internal questions about PTO, reimbursements, remote work, AI use, and company procedures.The episode explores how retrieval-augmented generation keeps answers grounded in approved company information, provides confidence scores and source links, and reveals gaps in existing documentation. They also demonstrate ArchIT’s Policy Bot in Microsoft Teams and explain how the same approach can become a searchable knowledge base for firmwide policies, SOPs, design standards, and institutional knowledge.

https://getarchit.com/the-submittal-lifecycle-skill-building-one-end-to-end-ai-workflow/In the final episode of our submittal series, we combine three AI-assisted workflows—intake, review, and resubmittal tracking—into one complete Submittal Lifecycle Skill for architecture firms.See how test cases uncovered an intake sequencing bug and a missing-document guardrail, why human approval gates remain essential, and how firms can begin with supervised document processing before adding integrations, dashboards, or scheduled automation.

https://getarchit.com/the-ai-enabled-submittal-process-part-3/Submittal review does not end when an architect returns a package marked “revise and resubmit.” Someone still has to track the open item, receive the next revision, compare it with the original submission, confirm whether every comment was addressed, update the project record, and prepare the response to the contractor.That final stretch is essential, but much of it is also repetitive and time-consuming. In Episode 3 of Design Under Influence, Alex Osenenko and Boris Rapoport demonstrate how AI can assist with tracking and resubmittals while preserving the most important control in the process: the human gate.

https://getarchit.com/the-ai-enabled-submittal-process-part-2/Submittal review is not difficult because of one isolated comparison. The burden comes from repeatedly moving between specifications, drawings, schedules, product data, review templates, prior decisions, and correspondence - often under tight deadlines and within a fee-compressed phase of the project.In Part 1 of our AI-Enabled Submittal Process for Architects series, we showed how AI can support submittal intake: identifying the package, extracting metadata, checking administrative completeness, preparing a log entry, and routing the item for review. Part 2 begins after intake is complete and the package has been routed to the appropriate design-team reviewer.The objective is not to have AI practice architecture or make the architect's decision. It is to prepare and organize the evidence so the responsible professional can spend more time applying judgment - and less time searching, comparing, formatting, and drafting.

https://getarchit.com/ai-enabled-submittal-process/What looks like a straightforward workflow quickly becomes a significant administrative burden. Files must be located, downloaded and identified. Project information must be extracted. Contractor-review information must be checked. Deadlines must be reconciled. Log entries must be created, and the package must be routed to the correct person.Each individual action may be small, but the volume creates constant context switching, compresses project fees and introduces opportunities for important details to be missed.Architects did not enter the profession to become human routers. That is where thoughtfully implemented AI can help.

https://getarchit.com/ai-agents-understand-the-cost/Should we deploy AI across the entire company?For a 20-75 person architecture firm, that can be an important step forward. Properly deployed, AI can reduce administrative work, help teams find information faster, improve consistency, and give architects more time to focus on clients and design.But as firms move beyond basic chat tools and begin using AI agents, another issue quickly emerges:Cost.

https://getarchit.com/why-organized-data-is-the-foundation-for-ai-success/AI tools are only as effective as the data behind them. In this episode of Design Under Influence, we explore why organizing your files and workflows is the critical first step toward successful AI adoption.

https://getarchit.com/the-ai-adoption-blueprint-for-aec-firms/AI is already transforming architecture, engineering, and design firms — whether leadership realizes it or not. In this episode, we break down a practical framework for secure AI adoption in AEC organizations, including AI policies, data classification, cybersecurity concerns, AI agents, and how firms can improve efficiency without compromising sensitive information. Learn how forward-thinking firms are balancing innovation with security while using AI tools like Microsoft Copilot, ChatGPT, and Gemini to streamline workflows, improve proposal quality, and save hundreds of labor hours. If your firm is exploring AI implementation, automation, or secure operational workflows, this episode provides actionable insights to help you adopt AI strategically and responsibly.

https://getarchit.com/ai-in-aec-stop-chasing-tools/Artificial intelligence is rapidly becoming part of daily operations in architecture, engineering, and construction (AEC). New tools appear constantly, promising to automate BIM workflows, improve project coordination, or generate proposals faster. For many small and mid-sized firms, this creates pressure to adopt everything quickly in order to avoid falling behind. But focusing only on tools often leads to confusion and wasted effort. The real value of AI does not come from using the newest platform—it comes from improving how the business operates.

https://getarchit.com/secure-ai-adoption-for-aec-firms/AI Is Already in Your Firm—Whether You Planned for It or Not Artificial intelligence is no longer a future consideration for architecture, engineering, and construction firms. It is already embedded in daily workflows, quietly shaping how proposals are written, meetings are documented, designs are reviewed, and decisions are made. The real challenge for AEC leaders is no longer whether to adopt AI—but how to do so responsibly, securely, and intentionally.