AI readiness assessment for your team

Before buying more AI tools, agree on the workflow, the data you can use, and who will own the result. Symph's paid Discover diagnostic helps your leadership team decide where to start and what needs fixing first.

Discuss a readiness diagnostic Symph's AI transformation approach

Use Symph's six-dimension readiness check

Choose one business unit and one candidate workflow, such as preparing a sales proposal or answering an internal policy question. Ask its business owner, an employee who does the work, and an IT or data representative to score the same questions independently. Compare the evidence before agreeing on a score.

Copy the questions into a spreadsheet with these columns: dimension, question, score, evidence, gap owner, and next action. Score every question from 0 to 3 using the scale below. If you cannot point to evidence, use 0. This is Symph's planning tool, not a validated benchmark, certification, or permission to deploy AI.

0: Unknown or absent: Nobody can show an agreed answer or working practice.
1: Discussed: Someone has an answer, but it is informal, incomplete, or untested.
2: Defined: An owner and documented approach exist, with evidence from a limited trial.
3: Working and reviewed: The team uses the approach consistently and has reviewed evidence of how it performs.

Strategy and leadership

Can we name the business problem, the people affected, and a measurable outcome for this workflow?
Does a named sponsor have authority to fund the work, resolve trade-offs, and stop a pilot?
Have we agreed what is in scope, what stays outside AI, and how we will judge a pilot?

Evidence to bring: A workflow brief, a named sponsor, and written success and stop criteria.

Data

Do we know which records or documents the workflow needs, who owns them, and how current they are?
Can we show permission to use those sources with the proposed AI tool, including personal or confidential data restrictions?
Have we checked a representative sample for missing, conflicting, or incorrect information?

Evidence to bring: A source inventory, permission records, and a documented sample-quality check.

People and skills

Can the employees who do the work explain where AI would help and where they would distrust it?
Can those employees write a task-specific prompt and check an answer against an approved source?
Do a team champion and a manager have time assigned for practice, questions, and feedback?

Evidence to bring: Employee interviews, an observed practice exercise, and time allocated to a champion.

Workflows

Have we mapped the steps, handoffs, exceptions, and approvals in the current workflow?
Do we have a baseline for time, rework, or quality that we can compare with a pilot?
Have we defined which AI outputs a person must review and how the work continues if AI fails?

Evidence to bring: A process map, baseline samples, a review checklist, and a manual fallback.

Governance and risk

Do employees have written rules for approved AI uses, prohibited uses, and information they must never submit?
Has an accountable owner reviewed potential harm, privacy, security, and applicable legal requirements for this use?
Can employees report an AI incident, and does someone have authority to suspend the use and investigate?

Evidence to bring: An acceptable-use policy, a use-case risk review, and an incident escalation route.

Tools and access

Has IT approved the proposed tool, account setup, vendor data handling, and access permissions?
Can the tool access only the sources and actions the employee is allowed to use?
Can an administrator remove access, check usage, and manage tool or model changes?

Evidence to bring: An approved-tool record, access tests, and administrator procedures.

Read the scores without hiding the gaps

Add the three question scores in each dimension for a score out of 9. Add all six dimensions for a total out of 54. Keep the dimension scores beside the total: strong leadership cannot compensate for missing data permission or an unsafe tool.

Define the starting point (0 to 17 / 54)

Clarify the problem and owners. Map one workflow and its data before committing to a pilot.

Close the pilot gaps (18 to 35 / 54)

Use the lowest-scoring dimensions to assign specific work. Try approved practice exercises while the owners resolve those gaps.

Review a bounded pilot (36 to 54 / 54)

You have more evidence to discuss a supervised pilot. Confirm the safeguards below, agree on evaluation, and keep a human accountable for the outcome.

Regardless of the total, pause use with real company data if data permission, accountable risk review, approved-tool setup, or access restrictions scores 0 or 1. Resolve and document those controls first. Use approved synthetic examples for training in the meantime.

For example, dimension scores of 7, 3, 6, 5, 2, and 7 total 30 out of 54. Start with governance and data ownership. Buying another tool will not resolve those gaps. Re-score the same workflow after the owners complete their actions; do not compare totals from different teams as a league table.

Bring the evidence into a paid Discover diagnostic

The self-check gives your team a shared starting point. In the Discover phase, Symph maps how the team works, where AI fits, and which functions stand to gain most. We scope the paid diagnostic around the questions your leadership team needs answered.

Review how the work happens
Discuss the workflow with the people who do it and compare their accounts with process documents, sample inputs, and existing tools.
Choose candidate uses
Compare possible AI uses against business value, data availability, employee readiness, and risk. Record why a use should proceed, wait, or stay manual.
Agree on the next decision
Define the gaps, responsible owners, and evidence needed before a workshop or pilot. Agree on the diagnostic's deliverables and scope before the engagement starts.

For the first conversation, bring one workflow description, your six dimension scores, an approved sample or synthetic example, and the names of the business and IT owners. Do not send sensitive records through the contact form.

Discuss the paid diagnostic with Symph or read how Discover fits into our AI transformation approach.

Frequently asked questions

What is an AI readiness assessment?

An AI readiness assessment checks whether a team has a useful business problem, suitable data, prepared employees, workable processes, risk controls, and approved tools. It helps identify the gaps to address before a pilot.

Does a high score mean we can deploy AI?

No. This self-check supports planning. Deployment still requires a use-case review, permission to use the data, approved access, evaluation, and accountable human oversight. A total score cannot override a missing safeguard.

Is Symph's Discover diagnostic a paid service?

Yes. The Discover diagnostic is a paid engagement scoped to your team and its workflows. Contact Symph to discuss the questions, participants, and deliverables before agreeing on the engagement.