Why Your AI Strategy Is Only as Strong as Your Data Foundation
AI is dominating boardroom conversations. From intelligent automation to generative insights, the potential is clear. But what’s less obvious is how to get from idea to impact.
According to Fivetran’s recent analysis, nearly half of enterprises are falling short when it comes to delivering real outcomes with AI. Why? Because even the most sophisticated models can’t deliver value without trustworthy, well-prepared data behind them.
“Data quality, data movement, and business context are what determine AI success - not just the model.”
– Fivetran
This aligns with what we’re seeing across the organisations we support at Flock. Companies are eager to explore AI, but many are facing an “execution gap” - a divide between their vision for AI and the day-to-day reality of their data.
What’s Driving the Gap?
From our experience, it comes down to three common challenges:
Data silos and fragmentation
Business-critical data is scattered across CRMs, spreadsheets, and legacy systems, making it hard to stitch together a usable, unified view.Inconsistent data quality
AI models are only as reliable as the data that fuels them. Inaccuracies, duplications, and missing context degrade output quality and trust.Lack of internal capacity or confidence
Even teams with strong data ambitions often lack the time or resources to align their data infrastructure with their strategic goals.
How Flock Closes the Gap
At Flock Consulting, we help organisations lay the groundwork for AI success - starting with better data.
Our Data Foundations service works with your existing tools and teams to:
Map and prioritise data sources aligned to your business goals
Build a single source of truth that integrates critical data sets
Improve data quality using automation and governance best practice
Create dashboards and insight tools that give business users confidence
We bridge the gap between technical data solutions and business strategy so that when you’re ready to invest in AI, your data is too.
AI should enhance decision-making, not generate more questions. If your team is exploring AI but stuck on the data piece, we can help.