GTA-based · Serving organizations since 2002

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Useful workflows before expensive licences

Practical AI adoption without losing control of company data

Choose valuable use cases, clean up permissions, establish guardrails and measure results.

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Best fit

GTA organizations with 20–150 employees, or internal IT teams needing added capacity.

Direct answer

What does ai readiness actually mean?

AI readiness starts with business workflows, data permissions and acceptable-use rules—not a licence purchase. Infostructure helps teams identify repeatable work worth improving, select appropriate tools and establish the security and governance needed for responsible adoption.

Business outcomes

What improves when this is owned.

  • Identify a small number of measurable, realistic AI use cases.
  • Reduce shadow-AI and confidential-data exposure.
  • Prepare Microsoft 365 permissions before broad Copilot adoption.
  • Train staff around approved tools and human review.

What the service can include

  • AI workflow and readiness assessment
  • Shadow-AI discovery conversations
  • Microsoft 365 Copilot readiness
  • Data and permission review
  • Acceptable-use policy support
  • Pilot selection and success measures
  • Staff enablement and safe-use training
  • Power Automate and workflow automation guidance

How we approach it

Clear steps, practical priorities.

01

Find value

Start with repetitive, high-volume work where time saved or quality improved can be measured.

02

Set guardrails

Define approved tools, data boundaries, access, review requirements and accountability.

03

Pilot

Test with a focused group, measure the result and expand only when the workflow earns it.

Common questions

Should every employee receive an AI licence?

Usually not at the beginning. Start with roles that have clear use cases, suitable data access and enough training to measure whether the licence creates value.

What is shadow AI?

Shadow AI is the use of unapproved AI tools or accounts for company work. It can expose confidential information and make outputs difficult to govern or reproduce.

Can you help us write an AI policy?

Yes. A useful policy should reflect actual work, distinguish approved and prohibited data, require human review and identify who approves new tools.

See how ai readiness fits into your technology priorities.

Use the scorecard for an immediate starting point, then bring the result to a focused conversation.

Get your score → Book a 30-minute meeting