Plainsight
Data & AI Strategy

It starts with your business.
Not our tech stack.

Plainsight turns business questions into a data, AI and software direction your organisation can follow, not a slide deck that gathers dust.

It doesn't start with tools or frameworks. It starts with the questions keeping your leadership team up at night, then works out where data, AI and software each earn their place, and where they don't.

Talk to us

Sound familiar?

These are the things we hear in almost every first conversation.

The missing layer is rarely technical.

Most organisations already have tools, dashboards, maybe a few AI pilots running. The technology isn't what's failing.

What's usually missing is clarity. Who owns what. Which investments connect to business outcomes. Where data and AI should work together, and where they shouldn't. That's what strategy at Plainsight looks like.

Not a 200-page document. Not a framework that sounds smart in a meeting room but dies in a drawer. Practical direction. Shared language. Decisions that stick because people understand why they were made.

"If people can't explain the 'why,' they won't follow the 'what.' That's where strategies break."

"Five strong guiding principles beat fifty slides nobody opens after the workshop."

What this covers

Strategy isn't just about data. And it isn't just about AI. It's about making your investments count, before and during implementation.

1

Direction

Where should data and AI actually contribute? We work with leadership to connect business ambitions to priorities that are realistic, not trendy. The roadmap comes from your business reality, not a template.

Data RoadmapsAI StrategyUse Case Prioritisation
2

Ownership & Governance

Who decides. Who owns. Where teams can move freely and where consistency matters. Good governance speeds things up because fewer decisions need to be reopened every quarter.

Data GovernanceDecision RightsAI Guardrails
3

Adoption & Change

A solution only matters if people use it. We build strategy with the people who'll live with it, not just the people who approve it. That includes communication, AI literacy, and growing capability internally.

Change & CommunicationAI Lab SetupAI Champions

Our approach

Six interconnected workstreams that span from readiness through to operating model, architecture, and adoption. Not all of them apply to every engagement. We scope what fits.

Workstream 1

AI Readiness Scan

Before building anything, understand where you stand. Through qualitative and quantitative assessment, we establish a robust view of your current AI readiness.

What we cover
  • Strategic direction: clarity of AI vision and alignment with business strategy
  • Data: quality, accessibility, and governance of data assets
  • Tools & technology: current landscape and integration capabilities
  • Governance & compliance: existing frameworks and regulatory readiness
  • Organisation & processes: operating model maturity for AI
  • People, skills & culture: AI literacy and change readiness
Deliverables
  • AI readiness baseline report with maturity levels across all dimensions
  • Insights on AI literacy, adoption patterns, and capability gaps
  • Identified AI champions and priority focus areas
  • Current-state data model and data readiness assessment

How we get there

Workshops before reports. Co-creation over handoffs. We don't disappear for six weeks and come back with a deck.

Understand the real questions. Talk to leadership and teams. Find where friction lives.

What you walk away with

Practical outputs. Not a deck that sits in a drawer.

Your

AI Action Plan

Direction

Where to invest, and why those choices beat the alternatives.

  • Roadmap tied to business value

    Not a list of technical projects. Priorities linked to the outcomes leadership actually cares about.

  • Prioritised use cases

    Scored on value, feasibility, and readiness. With shared agreement on what "ready" actually means for the organisation.

What we believe

These convictions shape how we approach every strategy engagement.

Governance should create movement, not slow it down. If your governance model adds meetings without adding clarity, something is off.

Shadow AI is a signal, not a threat. It means people see value but haven't been given a clear path. Structure solves this. Blocking doesn't.

If people can't explain the 'why,' they won't follow the 'what.' That's where strategies break. A strategy needs to live inside the organisation, not on a consultant's laptop.

Data and AI are not separate conversations. The best AI ambitions fail without strong data underneath. We always think about both, together.

The tool is never the strategy. Fabric, Databricks, OpenAI. They matter. But only in context. The organisation, maturity, and direction determine what fits.

Technology without ownership rarely survives. The most expensive platform in the world is the one nobody trusts or uses.

Strategy sharpens the rest. Wherever you begin.

No fixed order. Strategy gives direction, building creates value, specialists protect it. Start where it matters most for you.

You are here

Strategy

From business questions to a data, AI and software direction your organisation can follow.

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Value

Build

Data and analytics, AI, and custom software. Built with adoption and ownership from day one.

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Continuity

Experts

Specialists who think like teammates. Keep your engine running and your team growing.

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Ready to start from the right question?

No pitch deck needed. Just tell us what's going on.

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