Maharashtra to procure AI infrastructure for Higher & Technical Education
The Maharashtra government has approved the procurement of Artificial Intelligence infrastructure for the Higher and Technical Education Department to strengthen data analytics and dashboard systems under the National Education Policy (NEP) 2020.
A project implementation committee chaired by the Additional Chief Secretary (Higher & Technical Education) cleared the proposal. The department will acquire the infrastructure via the Government e-Marketplace (GeM) or an e-tender, following existing rules. Estimated annual outlay: Rs 22 lakh.
What this means for universities, colleges, and directorates
Ernst & Young LLP has been appointed to support dashboard enhancement and analytics work tied to the state's 150-day action plan and longer-term reforms. The plan includes setting up analytics cells at the ministry, university, and directorate levels to improve decision-making, monitoring, and policy insights.
Two initial AI use cases
- AI Query Assistant for HTED dashboards: HTED dashboards already consolidate institutional, academic, and administrative data. The AI layer will allow natural-language queries, real-time interpretation, and decision support for policy formulation and monitoring.
- AI Query Assistant for HRMS: Applied to the Human Resource Management System covering service records, postings, and promotions. Expected outcomes include intelligent search, automated responses, and better workforce analytics.
Practical benefits you can expect
- Faster answers to routine questions (enrolment trends, seat utilization, exam outcomes, scholarship disbursals).
- Less manual reporting; more time for academic planning and student support.
- Clear, consistent metrics for policy reviews and audit readiness.
- Improved visibility into staffing gaps, promotion cycles, and transfers.
How institutions can prepare now
- Audit and clean key datasets (student records, program structures, examination data, faculty rosters). Fix duplicates, missing fields, and inconsistent codes.
- Define access rules by role. Lock down sensitive fields (personally identifiable information, performance reviews) and document data-sharing protocols.
- Create simple data dictionaries so the AI understands field names, calculations, and update cycles.
- Nominate an "analytics point person" per institution to coordinate queries, feedback, and training.
- Plan short, focused training on asking effective questions, verifying outputs, and escalating anomalies.
Smart questions to ask your department or vendor
- Which datasets feed the AI today, and how often are they refreshed?
- What safeguards protect sensitive HR and student data? Are queries logged and auditable?
- How are inaccuracies reported and corrected? Who approves data model changes?
- What service levels (uptime, response time) and support channels are in place?
- Will APIs be available for secure integration with existing MIS or LMS tools?
Procurement and rollout notes
Acquisition will proceed through GeM or an e-tender, with oversight from the departmental committee. Deliverables are expected to include the AI layer on existing dashboards, HRMS integration, training, documentation, and processes for ongoing governance.
Budget reminder: Rs 22 lakh has been sanctioned on an annual basis for the AI infrastructure and related services.
Resources
- National Education Policy (NEP) 2020 - Official Document
- Government e-Marketplace (GeM)
- Upskilling for educators: AI and data courses by job role
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