According to recent research with the BPI Network and Growth Officer Council, sponsored by EncompaaS, 60% of business leaders lack confidence in their data-AI readiness. Meanwhile, Gartner predicts that over 60% of AI projects will fail by 2026 without an AI-ready data foundation. This gap between ambition and execution is where true competitive differentiation lies.

The hidden cost of waiting

Our research shows that effective Copilot deployment saves knowledge workers an average of 4 hours weekly. For a 1,000-person organisation, delaying implementation by just 6 months means forgoing 100,000 hours of productivity gains—equivalent to $7.5 million at average knowledge worker rates. While you debate data readiness, competitors are already using Copilot to:

  • Respond to customers 60% faster.
  • Shorten contract reviews 75% quicker.
  • Accelerate product development 30% faster.
  • Spot risks & opportunities weeks earlier.

While waiting for deployment, data degradation accelerates by approximately 2% per month. Duplicate documents multiply exponentially, outdated content accumulates, compliance risks compound, and storage costs grow by 25% annually.

Why many Copilot deployments stall


When preparing for a Copilot implementation, organisations typically take one of three approaches:

  • Plan and prepare: Continue building readiness while carefully managing the risk of delayed value realisation.
  • Internal execution: Use internal resources to drive readiness initiatives, often facing competing priorities and slower delivery timelines.
  • Accelerate with EncompaaS: Establish a trusted data foundation in just eight weeks through automated discovery, business-purpose classification, and proven governance frameworks.

Barriers to successful adoption

Three primary patterns often derail Microsoft Copilot implementations.

  • The data quality paradox. Microsoft Copilot can only leverage it can access. 80% of organisational knowledge is in siloed legacy systems, file shares, and disconnected repositories.
  • The scale trap. Organisations often attempt to process everything simultaneously – millions of documents, decades of accumulated content without prioritisation or strategy. This can lead to rising costs, extended timelines, and stakeholder fatigue before meaningful value is achieved.
  • Insufficient governance and trust. Without proper classification and governance, Microsoft Copilot becomes a compliance risk rather than a productivity tool. When AI surfaces confidential information to the wrong users or provides outdated guidance as current policy, trust erodes rapidly.

The 8-week path to excellence

Organisations that that start with a solid foundation and improve iteratively can see ROI within 8 weeks. The framework:

Weeks 1–2: Foundation and discovery

  • Establish your baseline.
  • Define success metrics.
  • Quick wins to build momentum.

Weeks 3–4: Classification and prioritisation

  • Deploy business purpose classifications.
  • Identify high-value content.

Weeks 5–6: Enrichment and governance

  • Enrich for intelligence.
  • Implement governance automation.

Weeks 7–8: Deployment and optimisation

  • Launch your pilot.
  • Measure and iterate.

Enterprises across financial services, government, and healthcare are achieving 300% ROI within 16 weeks using this approach.

The EncompaaS difference

Traditional metadata (filename, author, date) provides structure. Business purpose classification and metadata enrichment provide intelligence—lifecycle stage, ownership, compliance requirements. This is where Copilot transforms from surfacing documents to delivering trusted decisions.

The competitive imperative

By 2026, only 40% of AI projects are expected to succeed. The real difference between success and failure is not the AI itself, but the readiness of your data—and the difference between an 18-month challenge and an 8-week outcome.

Ready to close your confidence gap? Book a demo with our team to discover how we can assist your organisation.