Know which faculty programs to run next, and why
For faculty development units and vice deans who run a needs survey every year, then struggle to read hundreds of answers fairly. We group the results, connect them with evidence you already hold and draft a ranked program plan that your committee reviews and approves.
- Timeline
- 2 to 3 weeks to first analysis
- Best for
- Faculty development units planning an annual or semester program
- Usually starts with
- Your latest needs survey and one or two supporting sources

Agent flow
What is an AI training needs analysis?
An AI training needs analysis reads faculty survey results, including every open comment, and identifies the development topics that come up most often and matter most to your goals. It then checks those topics against other sources you hold, such as improvement actions in course reports, student feedback summaries and accreditation recommendations. The output is a draft list of programs with the evidence behind each one, which your faculty development committee reviews, edits and approves.
- Reads Microsoft Forms, Google Forms and Qualtrics results in Arabic or English
- Groups open comments into themes, each with sample quotes
- Breaks needs down by college, department and career stage
- Reports on groups only, never on named faculty members
Typical Training needs analysis we ship
Each one scoped and quoted at a fixed price after a free review of your process.
Survey questions that lead to decisions
Before the next cycle, we review your questionnaire with the unit so it asks about specific skills, preferred formats and timing, not just general satisfaction. Arabic and English versions stay aligned, and each question maps to a decision the committee will actually make.
Every open comment read and grouped
AI reads all free-text answers in Arabic and English, groups them into themes such as assessment design, online teaching or research supervision, counts how often each appears and pulls representative quotes. Staff can open any theme and see the original comments behind it.
Needs by college and career stage
Results are broken down by college, department, academic rank, years of service and full-time or adjunct status. Groups smaller than a size you set are merged so no one can be identified, and differences between new and experienced faculty become easy to see.
Cross-checks with course reports and feedback
Survey themes are compared with improvement actions in course reports, program-level student feedback, external reviewer comments and accreditation recommendations. A need that appears in several sources moves up the list, and one raised by a single source is shown with that caveat.
A ranked program plan with reasons
The draft plan lists each proposed program with its target group, suggested format, best timing in the academic year and the evidence behind it. The committee can reorder, merge or drop items, and the plan keeps a note of every change and who made it.
Checking whether training met the need
After programs run, attendance and evaluation results come back into the analysis. The next survey asks about the same skills, so the unit can see whether confidence moved in the groups that attended and report that progress honestly.
What changes for your team
Hundreds of open comments sit unread in a spreadsheet export.
Every comment is grouped into a theme, with quotes the committee can check.
The new program copies last year's list plus a few loud requests.
Each proposed program cites survey results and supporting evidence.
Breaking results down by college takes days of manual pivot tables.
Breakdowns by college and career stage are ready when the survey closes.
Four steps, one fixed price
- 01
Agree what the analysis must decide
We start with the decisions ahead, such as the annual program, the budget split or an accreditation response, and agree which data sources are allowed and the minimum group size for reporting.
- 02
Prepare the data
Survey exports, course reports and feedback summaries are collected, names and staff IDs are removed where they are not needed, and college and department labels are standardized.
- 03
Run and check the analysis
AI builds the themes and breakdowns, then your unit reviews a sample of comments against each theme and renames or splits any that do not fit.
- 04
Present and hand over
The draft plan and a Power BI or Looker Studio dashboard go to the committee, and the full workflow is documented so your team can rerun it next cycle.
Why needs surveys rarely shape the program
Most institutions already run a training needs survey, and most of its value is lost in the reading. Average ratings are easy to chart, so the summary says that faculty want more help with assessment or technology. The open comments, where people explain what they actually struggle with, stay in a spreadsheet because reading several hundred of them in two languages takes days nobody has. The program that follows often looks like last year's, adjusted for whoever asked loudest.
That gap matters beyond the program itself. Accreditation reviewers, whether from NCAAA, the CAA in the UAE, QAA in the UK, SACSCOC or NAAC, commonly ask how development priorities were identified and whether the institution acted on what it found. An AI training needs analysis gives you a clear answer: every comment read, every theme traceable to its source, and a written link between the evidence and each program the committee chose.
How the analysis weighs different sources
A survey tells you what faculty say they need. Other records show what the institution sees: course reports that repeat the same improvement action, student feedback that points to unclear assessment criteria, an external examiner's comments, or a new policy on e-learning or AI in teaching that everyone must adopt. The analysis lays these sources side by side and shows where they agree, where only one source raises a need and where they conflict, so the committee can weigh them openly instead of by instinct.
The weights are yours to set. One unit may give accreditation recommendations the most weight this year, while another puts faculty requests first. Individual responses are never shown to chairs or deans. Reports cover groups above your minimum size, and raw data stays with named unit staff in your own Microsoft 365 or Google Workspace tenant. We handle the data under GDPR, Saudi Arabia's PDPL, the UAE PDPL or India's DPDP Act, as they apply to you.
From analysis to a program you can deliver
A list of needs is not yet a plan. The draft turns each priority into something the unit can run: a workshop series for faculty in their first year, a short online course on rubric design, peer observation for experienced staff, or a session timed before the exam period when assessment questions peak. Each item suggests a format and timing, and notes whether it could be delivered in-house or would need an external trainer, so the committee can discuss cost and capacity in the same meeting.
Once the committee approves the plan, the programs can move straight into your workshop scheduling and registration, and attendance and evaluation results flow back into the next analysis. Over a few cycles you build a record of what the institution identified, what it delivered and what changed, which is the account quality units need for annual reports and accreditation visits. Every survey template, prompt and dashboard belongs to you.
AI Training Needs Analysis questions
Will chairs or deans see what individual faculty members wrote?
No. Reports show results for groups above a minimum size you set, and quotes are checked so they do not reveal who wrote them. Raw survey data stays with named staff in your faculty development unit, inside your own tenant or a region you choose. If your survey is anonymous, we keep it that way and never try to match answers to people.
Can the AI read survey answers written in Arabic?
Yes. It reads Arabic and English answers, including comments that mix both, and groups them into the same set of themes. Theme names and summaries can be produced in both languages. Your staff review a sample of comments against each theme before results are shared, so misread wording or dialect is caught early.
Does the analysis decide which programs we run?
No. It produces a draft ranking with the evidence behind each item. Your faculty development committee decides which programs go ahead, in what order and with what budget. Because the reasoning is written down, it is easy to see why the committee changed the order and to record that decision in the minutes.
What if all we have is last year's survey?
That is enough to start. The first analysis can run on a single survey export, and we will suggest small changes to the questionnaire so the next cycle produces clearer results. Course reports, student feedback and accreditation recommendations can be added later, one source at a time, without rebuilding anything.
How much does a training needs analysis cost?
It depends on the number of sources, languages and colleges involved. After a free 30-minute audit we send a fixed-price quote in writing before any work starts, with no hourly billing. You can choose a one-time analysis or a repeatable workflow for every cycle, and either way you own the templates, prompts, data and dashboards.
Often built together
AI Faculty Training ManagementRun every faculty workshop from invitation to certificate without the spreadsheet chase.
AI Faculty Compliance and Follow-UpSee which course files are in and which are missing, without chasing every faculty member yourself.
AI Unit Performance DashboardOne live view of unit progress, overdue activities and KPIs, ready before the dean asks for it.
Get a fixed quote for your Training needs analysis
Send two lines about the process you want to hand over. We reply within one business day with what we would build, the tools involved and what it would take.
- 30-minute call, no slides, no pressure
- One fixed price before any work starts
- You own every workflow, account and line of code