By: Charmé van der Westhuizen - New Business Development Manager at IPT

When business leaders ask me where to start with AI, I often find that the pressure to act has arrived before the plan. They have seen what Microsoft 365 Copilot can do, employees are already experimenting, and the organisation does not want to fall behind.

I advise them to pause long enough to assess the environment properly. AI readiness gives a business an honest view of what is in place, where the gaps sit, and which work should happen before investment grows.

Microsoft’s AI Readiness Assessment considers seven pillars, covering business strategy, governance and security, data foundations, organisational culture, infrastructure, AI experience, and model management. A licence or one technology decision cannot create readiness.

Begin with the work you want to improve

The first step is to define the business outcome. “We need AI” provides no direction, while “improve productivity” is usually too broad to guide a sound decision.

I would start with a process that teams understand and where the friction is visible. The business should know who owns that process, what slows it down, which information it relies on, and how improvement will be recognised. Microsoft’s scenario library can help organisations connect Copilot to real roles and workflows.

A focused use case gives the first phase a sensible boundary and is easier to evaluate than a rollout driven mainly by enthusiasm.

Look closely at the data

AI works with the information available to it, so that information needs to be reliable enough for the intended task and accessible only to the right people.

For Microsoft 365 Copilot, readiness includes reviewing content across SharePoint, OneDrive, and Exchange. Microsoft advises that Copilot and agents respect existing permissions and sharing settings. Old access rights and overshared content remain part of the environment they use.

I would ask where the relevant data sits, who owns it, whether it is current, and whether access still reflects people’s responsibilities. A business that cannot answer those questions is likely to carry existing weaknesses into its AI rollout.

Review security and governance

Every AI initiative needs clear ownership. Someone must decide which tools are approved, what information may be used, where human review is required, and how activity will be monitored.

Microsoft’s secure deployment guidance emphasises remediating oversharing, using guardrails, and preparing for regulatory obligations. In South Africa, POPIA belongs in this discussion whenever AI may process personal information.

Governance should fit the use case and give employees practical rules. It also needs to evolve as the organisation introduces new workflows, agents, and data sources.

Check the technical foundation

Readiness depends on whether the existing technology environment can support the intended use reliably. Identity management, licensing, integration, device security, and support capacity all shape what can be deployed responsibly.

For Copilot, the organisation should understand its Microsoft 365 configuration and whether its security and governance capabilities are being used properly. Additional capability cannot clean up permissions or establish accountability without deliberate configuration and ongoing oversight.

Prepare people for adoption

Technical preparation will deliver little value if employees do not understand where AI fits into their work. People need role-relevant guidance and time to practise, with a clear route for questions or concerns. Managers need to understand how AI changes a workflow, where judgement remains essential, and how responsible use should be handled within their teams.

Adoption also needs attention after launch. Feedback can show where users are struggling, which processes need adjustment, and whether the selected use case is producing useful results.

Decide how progress will be judged

Before deployment, agree on the evidence that will show whether the use case is working. Microsoft’s Copilot measurement guidance covers readiness and adoption, productivity impact, and business value.

The measure should reflect the work involved. A business might look at turnaround time, repeated effort, access to information, or consistency within a process. Choosing the evidence upfront makes it easier to judge whether AI is delivering value rather than relying on licence activation or usage figures alone.

An AI readiness assessment gives the organisation a clear starting position and a prioritised path forward. It can show what is already sound and where attention is needed before wider deployment.

If you do not know where to begin, contact IPT for an AI readiness assessment. We will help you evaluate the business case, data environment, governance, security, technical foundation, and adoption requirements, and turn that view into practical next steps.