Tools meet pedagogy.
Faculty need support that connects AI to learning outcomes, assessment and the realities of a classroom.
An independent proposal for Adani University
Chief Artificial Intelligence Officer
for Higher Education Institutions
A university-wide role.
A connected AI future.
A strategic bridge between AI capability and institutional reality — connecting academics, people, operations and governance.
I’m Ankit Prajapati. My journey through engineering, teaching, government digital operations and university administration informs a practical proposition: make AI a shared institutional capability.
Read the 60-second decision brief →Read the executive proposal PDF ↗
Karnavati University · Gujarat, IndiaExplore my career ↗
From institutional experience
to a proposed leadership mandate.
Explore with purpose
Your route through the proposal.
01 / The institutional opportunity
AI is entering every department.
Who connects the work?
The proposed CAIO function gives leadership, faculty, students and administrators a shared way to choose, adopt and evaluate AI.
Institutions need academic purpose, people who can use the tools, dependable data and someone accountable for whether the work improves.
Ambition meets operations.
Staff need coherent workflows, clear ownership and support that lasts beyond a demonstration.
Possibility meets responsibility.
Leadership needs evidence of value, defined decision rights and a credible path from pilot to adoption.
02 / The CAIO as a bridge
One mandate.
Many institutional connections.
Select a stakeholder to see the relationship, a practical first action and what progress would look like.
Institutional vision
CAIO
Strategy · Academic alignment
Execution · Governance
Shared ownership.
Measurable institutional value.
Leadership / Strategic alignment
Turn institutional vision into an executable AI agenda.
Connect academic priorities, budget decisions and institutional outcomes through one reviewed opportunity portfolio.
- First action
- Agree the mandate, accountable sponsors and a baseline for the first pilots.
- Evidence of progress
- Named owners, approved success measures and documented scale or stop decisions.
03 / HEI AI transformation map
The whole university.
Explored one function at a time.
24 areas of opportunity. Open any area for its use cases, a proposed first pilot, accountable owner and evidence of progress.
No matching opportunities
Try another phrase or return to all institutional areas.
Explore broadly. Start with evidence.How opportunities become pilots →
04 / Why my journey is relevant
A multidisciplinary path.
An institutional perspective.
Experience across technical and non-technical settings provides a foundation for translating between people, policy and systems.
Learn the system.
B.E. in Electronics & Communication; M.Tech in Communication Systems; embedded-software validation training at STMicroelectronics.
Technical inquiry, testing and disciplined execution.
Understand the classroom.
Academic association at SVNIT Surat, followed by faculty and academic administration roles at Babaria Institute and SVBIT.
Faculty realities, student mentoring and academic processes.
Work with consequence.
GPSC preliminary examination experience and digital operations at Gujarat State Civil Supplies Corporation, including procurement and reporting workflows.
Public-service context, process discipline and accountability.
Connect the institution.
Senior Academic Administrator at Karnavati University, working across accreditation, academic systems, NEP coordination and institutional reporting.
Cross-functional coordination and operational ownership.
Turn ideas into workflows.
PRAMAAN, NIRANTAR and KU-IDMS make evidence, review, ownership and continuity tangible. Explore their evaluation versions below.
Practical AI-assisted development and governance thinking.
The mandate I am proposing: connect institutional strategy, adoption and accountable execution, working with specialist engineering, security, legal and academic teams.
Full career, education & research ↗05 / Demonstrated work
Examine the thinking.
Then operate the creation.
Working evaluation versions expose the logic behind the proposal. They use demonstration data and browser-local workflows; case studies state the maturity of the underlying work.
01 / Evidence & accountability
PRAMAAN ↗
Make institutional evidence traceable through ownership, source, review and correction.
Evidence→Review→Assurance
Interactive demonstration · Related assurance work: implementation baseline
02 / Continuous quality
NIRANTAR ↗
Connect metric ownership, reporting cycles and evidence review to continuing improvement.
Allocate→Monitor→Improve
Working prototype · Illustrative institutional data
03 / Institutional data
KU-IDMS ↗
Bring data requests, assigned roles and approvals into a connected institutional workflow.
Submit→Verify→Approve
Working prototype · Synthetic demonstration records
06 / A proposal for Adani University
Build on the direction.
Connect the capability.
Adani University’s published emphasis on multidisciplinary education, research, industry engagement and ethical leadership provides a relevant setting for this proposition.
The university already describes AI activity in learning, faculty training and evaluation. My proposal is to explore a coordinated institution-wide mandate alongside its existing academic and technology teams.
Independent candidate proposal. It does not imply an existing vacancy, appointment, institutional endorsement or access to Adani Group resources.
Multidisciplinary education
Proposed contribution: connect faculty development, course support and student AI literacy across disciplines.
University vision & mission ↗Research and industry engagement
Proposed contribution: develop reviewed pilots around real institutional problems and research needs.
University overview ↗AI in higher education
Proposed contribution: give adoption a common operating model, accountable sponsors and measurable outcomes.
Published AI initiative ↗07 / From mandate to institutional capability
A purposeful first 90 days.
An evidence-led first year.
A proposed sequence for discussion. Scope, staffing, funding and delivery dates would be agreed with the university after discovery.
Discover / Understand institutional reality
Start with the people, processes and purpose.
Meet leadership and functional teams, map current systems and understand where AI can make a useful, measurable contribution.
Explore a related opportunity →Work to undertake
- Meet leadership, faculty, student and administrative representatives.
- Map current systems, data ownership and institutional priorities.
- Assess readiness, staff support needs and process pain points.
- Record baselines and select an initial opportunity portfolio.
Decision at this stage
Agree the mandate, sponsors, opportunity report and criteria for choosing pilots.
The conversation I am seeking
Let’s make the role
useful to the university.
A founding CAIO mandate can turn scattered AI activity into coordinated institutional capability. I would welcome a discussion on the opportunity, my fit and a structured discovery phase at Adani University.
Ankit Prajapatiankit.shareviews@gmail.com+91 99134 85499Ahmedabad, Gujarat, IndiaProfessional profile on LinkedIn ↗Career profile · PDF ↗