AI readiness starts with your people, information and everyday work
AI becomes useful when it improves work that matters. That takes clear requirements, people who can use and challenge the results, dependable information and practical controls. Readiness brings those foundations together so your organisation can choose worthwhile uses, introduce them responsibly and keep them working as things change.
Start with the outcome you want to improve
Faster responses. Fewer avoidable corrections. More time for complex cases. A useful AI initiative starts with a recognisable business outcome and an understanding of today’s performance.
Consider a team handling incoming correspondence. Delays may come from unclear routing, repeated searches and unnecessary handovers as well as drafting. Improving guidance or simplifying the process could deliver value before introducing AI.
Define what needs to change, who owns the result and how you will measure it. Time saved only becomes a benefit when the organisation decides how to use it.
Design the work around people
The people doing the work understand its exceptions, informal steps and recurring frustrations. Involve them in shaping the future process, including what stops, what changes and where human judgement remains essential.
An officer might receive a suggested route and a draft response linked to current guidance. Their role changes from finding and composing everything to checking accuracy, resolving ambiguity and approving the outcome.
That review needs time, knowledge, access to sources and authority to reject an answer. Training, honest discussion about role changes and a clear feedback path help people build confidence in the service.
Keep information useful as work happens
AI readiness needs ongoing intelligent information management. A clean-up creates a starting point, but documents, permissions and ownership keep changing.
Useful information carries context: who owns it, whether it is approved, which version applies, who may use it and how long it should be retained.
Governed automation can flag missing metadata, suggest classifications, identify possible duplicates and route overdue reviews to owners. People resolve conflicting sources and consequential changes. When an authoritative source changes, dependent summaries and shared knowledge need an appropriate update too.
This makes information care part of everyday operations and directs staff effort towards the exceptions that need attention.
Distinguish finding an answer from taking action
Search helps locate information. AI-assisted retrieval and drafting can help interpret it. An agent may also choose steps, use tools and request changes across systems.
Each pattern needs clear boundaries. Finding approved guidance, preparing a response and sending it carry different responsibilities. Specify what the system can access, what it can change, when approval is required and how work continues if something fails.
Start with a manageable scope. Increase autonomy when evidence shows the service can support it.
Build trust through accountable governance
Bring business ownership, privacy, security, records management and compliance into the design. Controls should reflect the consequences of the particular use and the obligations that apply to your organisation.
People and machines can both reproduce bias. Evaluate the combined service against the existing process, including difficult cases, varied language and outcomes that averages may hide.
AI-generated responses, summaries and decisions may also become business records. Define what evidence needs to be captured, reviewed, retained or disposed of under your recordkeeping arrangements.
Choose technology that fits the requirements
Microsoft 365 Copilot, OpenText Aviator, other packaged tools and custom development offer different paths. Compare them against your workflows, information sources, controls and full operating costs. Confirm the exact product, deployment and licensing rather than assuming a capability is available.
Where OpenText Content Manager is already part of your environment, it can provide records and compliance services beneath a connected or agentic workflow. Controlled integrations can support permitted retrieval and filing while keeping records controls in the underlying system.
Interfaces such as Model Context Protocol can connect tools and services. Security, permissions, approvals and logging still need to be designed and tested.
Build a capability you can keep improving
Test the whole process, including exceptions, permissions, review effort and recovery. Give the service an owner, monitor results and revisit assumptions as information, products and requirements change.
The next step should be a practical improvement your organisation can support.