--- title: "AI-Ready Tech Pioneers Share their Single Most Effective AI Readiness Strategies" url: "https://atlan.com/regovern-watch-center/ai-readiness-strategies-pioneers/" description: "Tech leaders reveal what they're betting on - from open specifications and tool consolidation to combining structured, unstructured, and contextual data." keywords: "atlan, data governance, regovern 2025, regovern watch center" --- > Atlan is hosting Context Conference, bringing together the leaders and builders at the frontier of giving AI the context it needs to understand their business. It runs online on October 28, 2026, from 11:00 AM to 2:00 PM ET. Atlan co-founder Prukalpa Sankar opens and closes the day. Leaders from AstraZeneca, BNY and Verizon share why they invest in context and what they get from it. Registrants get early access to The AI Context Gap, a new study from MIT Technology Review Insights. Register: https://atlan.com/context-conference/ A Re:Govern 2025 Watch Center video where tech leaders reveal what they're betting on for AI readiness, from open specifications and tool consolidation to combining structured, unstructured, and contextual data. Watch on the page (email required to keep watching): [https://atlan.com/regovern-watch-center/ai-readiness-strategies-pioneers/](https://atlan.com/regovern-watch-center/ai-readiness-strategies-pioneers/). ## What's inside As tool fragmentation accelerates and AI demands grow, tech pioneers face a critical question: how do you future-proof your architecture for the context layer era? Five leaders share their strategies, from adopting open standards like MCP to making tough decisions about tool sprawl, defining where context should live, and never losing sight of end-user experience. Key takeaways: - Open specifications like MCP, Open Lineage, and Open API enable interoperability as tool specialization increases across the stack. - Tool consolidation matters: companies need to make hard decisions about which tool does what and stick to one universal catalog. - Context should live in one place, not scattered across Unity, Horizon, Confluence, and every other platform where teams naturally document. - Conversational AI requires three components: structured data (warehouses), unstructured data (vectorized), and context (semantic layers plus metadata). - End-user experience determines success: if the last mile isn't intuitive, the magic context layer you built won't get used. ## Speakers - **AJ Pryor**, VP of Data & Analytics, Vimeo. Six months into leading Vimeo's data team, AJ is building foundations to move from historical reporting to predictive and conversational analytics. - **Amie Bright**, VP of Enterprise Data & Insights, GitLab. Amie is driving GitLab toward "AI-ready data," with governance at the center. She believes BI is on its way out and is testing AI chatbots while tackling hallucinations and missing context, preparing GitLab's data for an AI-first future where traditional BI tools fade. - **Cortney Worthy**, Enterprise Data Governance Lead, Dropbox. Cortney is building a certified marketplace by embedding contracts and quality upstream, before data products ship. Her philosophy: education over enforcement. - **Simon King**, VP of Data Operations, Loopback Analytics. Simon is shifting from fastest-possible solutions to productized data operations, replacing tribal knowledge with structured metadata that scales in high-stakes clinical environments. - **Takashi Ueki**, Head of Enterprise Data & Analytics, Elastic. Takashi leads Elastic's mission to democratize trusted data across a remote-first, open-source culture. He champions accountability through ownership and data contracts, building toward AI-enabled discovery and search where governance enables innovation in decentralized, global teams. ## Companies - **Vimeo**: a global video platform serving creative professionals and enterprises, transforming how its teams use data, from backward-looking reports to conversational analytics and predictive AI that enables self-service discovery. - **GitLab**: the world's largest all-remote public company. It is testing AI chatbots and building AI-ready data products where governance replaces centralized control with transparency and context. - **Dropbox**: manages 1 trillion pieces of content for 97% of the Fortune 500. It is betting big on AI with Dash, universal search that connects every app, finds answers in seconds, and turns scattered content into organized intelligence. - **Loopback Analytics**: brings health systems and life sciences together through trusted data. In healthcare, where data quality directly impacts clinical outcomes, Loopback is replacing tribal knowledge with structured context, building productized data operations that scale trust. - **Elastic**: one of the world's largest open source companies, Elastic grew revenue 17% to $1.48B by becoming the Search AI Company. Its platform powers RAG workloads, vector search, and AI-driven security for enterprises building GenAI apps. ## More from Re:Govern 2025 Session recordings: - [CME Group: Context at Speed](https://atlan.com/regovern-watch-center/cme-group-context-at-speed/) - [Mastercard: Context by Design](https://atlan.com/regovern-watch-center/mastercard-context-by-design/) - [Workday: Context as Culture](https://atlan.com/regovern-watch-center/workday-context-as-culture/) - [The Evolution of Trust: Building the Foundations for Future-Readiness](https://atlan.com/regovern-watch-center/evolution-of-trust/) Highlights: - [Why Workday is Building a Semantic Layer](https://atlan.com/regovern-watch-center/workday-building-semantic-layer/) - [Workday's Learnings From its First Talk to Data experiment](https://atlan.com/regovern-watch-center/workday-talk-to-data-learnings/) - [How Workday Connects Context Across Business Tools](https://atlan.com/regovern-watch-center/how-workday-connects-context/) - [Workday's Semantic Layer Strategy](https://atlan.com/regovern-watch-center/workday-semantic-layer-strategy/) - [How Mastercard Designs Context at Scale](https://atlan.com/regovern-watch-center/how-mastercard-designs-context/) - [Mastercard's Federated Architecture for Agentic Commerce](https://atlan.com/regovern-watch-center/mastercard-federated-architecture/) - [How Protocols and Tools are Evolving for Agentic Governance](https://atlan.com/regovern-watch-center/protocols-agentic-governance/) - [How Data Roles are Evolving: From Modelers to Context Engineers](https://atlan.com/regovern-watch-center/data-modelers-to-context-engineers/) - [How Mercury Insurance is creating PII-free workspaces for AI use cases](https://atlan.com/regovern-watch-center/pii-free-workspaces/) - [GitLab's Strategies for Building Reliable Conversational Analytics](https://atlan.com/regovern-watch-center/gitlab-conversational-analytics-strategies/) - [GitLab's Learnings from its First Experiment with Conversational AI](https://atlan.com/regovern-watch-center/gitlab-conversational-ai-learnings/) - [Vimeo's Approach to Data Governance in the Era of Conversational Analytics](https://atlan.com/regovern-watch-center/Vimeo-approach-to-data-governance/) - [Inside General Motors Metadata Lakehouse](https://atlan.com/regovern-watch-center/gm-metadata-lakehouse/) Resources: [Modern Data & AI Governance Blueprint](https://atlan.com/blueprint).