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Stop Waiting for Data Perfection

  • sarahfoss8
  • Oct 31
  • 3 min read

Your AI Strategy Can't Afford It


Author: Dharmesh Ghedia, Lead Solution Architect Published: 31st October 2025

4-minute read


In a recent interview with 'The Times', President of Google in EMEA, Debbie Weinstein, delivered a stark warning: “Businesses slow to adopt AI risk being left behind over the next five to ten years.” The message is clear. The time for AI action is now, and businesses that hesitate risk being left behind.


Many organisations are caught in a state of analysis paralysis. They see the potential of AI and agentic solutions, but they hesitate, believing they must first complete a monumental, multi-year data transformation project. 


While a solid data foundation is non-negotiable for scaling, waiting for it to be perfect is a strategic error. This "chicken-and-egg" dilemma, where you need the perfect data foundation to start AI but need AI wins to justify the investment in the foundation, is where momentum dies.


The most successful organisations are accelerating their AI adoption by taking a dual approach. In other words, they're building the plane while flying it.


Here’s how…



Stream 1 

Rapid Value with Prototypes & MVPs



This is your fast track to demonstrating value and building buy-in. The goal isn't enterprise-wide perfection; it's targeted impact. By leveraging powerful platforms like Google Cloud's Vertex AI Studio, your teams can rapidly build and test prototypes using state-of-the-art Gemini models.


Building a simple agentic app no longer takes months. Tapping into your existing data in BigQuery, you can create an MVP to help your marketing team draft personalised campaign content, equip your service team with instant, context-aware answers to customer queries, or democratise access to internal data sets via conversational analytics.


The purpose of this stream is threefold:


  1. Prove the Value: A working prototype that solves a real business problem is the most powerful tool for securing executive buy-in and wider investment.

  2. Win Over Your People: When employees see AI as a helpful "co-worker" that automates tedious tasks, fear is replaced by enthusiasm. Adoption becomes a pull, not a push.

  3. Collect Feedback: Real-world usage is the ultimate stress test. This process will immediately highlight gaps and workflow friction points, providing a list of priorities from your user base to create value in your solution and improve your foundation.

 


Stream 2

Building Your Strategic Data Foundation



Running alongside Stream 1, this stream focuses on building a robust and scalable foundation necessary for long-term success. The crucial difference is that this work is no longer based on assumptions. The learnings and proven needs from Stream 1 directly inform it.


This is where you build your single source of truth, create your data strategy, address your data challenges and so on.


This stream includes:


  • Centralising Data: Architecting your unified data warehouse, such as BigQuery, to break down data silos.

  • Implementing Governance: Using a tool like Dataplex to automatically discover, catalogue, and apply governance policies across your data estate, implementing the necessary access rules, in line with your security and compliance needs and even define your quality monitoring test - all to ensure your AI solutions are built on a bedrock of trust and security.

  • Closing Critical Gaps: Prioritise the data quality and integration issues that your MVP reveals to be blocking real business value. Instead of trying to fix everything, this dual approach provides a clear roadmap to address what matters most first.



A Dual-Stream Approach

This is where the magic happens


The two streams create a powerful feedback loop.


  1. The prototype built on Vertex AI (Stream 1) reveals that customer data is inconsistent.

  2. That insight immediately informs the data cleansing and schema priorities for your BigQuery foundation (Stream 2).

  3. The business sees immediate value, which unlocks the budget and mandate to accelerate the foundational work through an agile and iterative process, driving continuous improvement.


A dual stream approach

By embracing this approach, you stop waiting for the "right moment" and start creating value now. You build momentum, learn faster, and ensure your long-term data foundation is purpose-built to solve the challenges that will truly drive your business forward.


Are you ready to take off from the runway and into flight?


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