IIM Ahmedabad Selection Criteria 2027–29: What Has Changed From Last Year?

IIM Ahmedabad Selection Criteria 2027–29: What Has Changed From Last Year?

IIM Ahmedabad has changed its selection criteria for the PGP 2027–29 batch, and while the institute is still looking at the same broad parameters, the way it evaluates them has changed significantly.

For CAT 2026 aspirants, the biggest changes are not about suddenly giving more or less importance to academics, work experience or gender diversity. Instead, IIMA has simplified the scoring system, replaced the old Academic Category framework with undergraduate disciplines, removed the earlier AC-RC based shortlisting structure and slightly increased the effective weight of CAT in the final selection.

The new policy is also considerably easier to read than last year's criteria. But simpler does not necessarily mean more predictable.

The biggest question for aspirants is therefore not just what has changed?, but who benefits from these changes and who could lose out?

Here is a detailed breakdown of the IIMA Selection Criteria for the 2027–29 PGP batch through CAT 2026, including what remains unchanged, what has been removed, and the likely advantages and disadvantages for different types of candidates.

IIM Ahmedabad Selection Criteria 2027–29: The Big Changes

At a high level, IIMA has retained the same broad ingredients:

• CAT performance
• Class 10 performance
• Class 12 performance
• Graduation performance
• Work experience
• Gender diversity
• AWT
• PI

What has changed is how these parameters are converted into scores and how candidates are compared with one another.

The major changes are:

1. One common academic scoring table for Class 10, Class 12 and graduation
2. Class 12 stream-wise academic scoring has been removed
3. The old Academic Category (AC) system has been replaced by 20 undergraduate disciplines
4. Raw composite scores are now normalized within the candidate's undergraduate discipline
5. The earlier AC-RC based shortlisting system and its upper limits have been removed
6. Earlier minimum academic performance conditions based on 10th, 12th and graduation have been removed from the shortlisting process
7. The CAT cut-offs remain unchanged
8. The 65% CAT + 35% Application Rating split for the initial composite score remains
9. The effective CAT weight in final selection increases from 25% to 26%
10. The final selection formula becomes 50% PI + 10% AWT + 40% normalized composite score

The institute is therefore not changing what it values as much as it is changing how candidates are evaluated against each other.

1. First, What Has NOT Changed?

Before getting into the new system, it is important to understand that IIMA has not suddenly become a CAT-only institute.

The same broad parameters continue to matter:

For shortlisting:

CAT + Class 10 + Class 12 + Graduation + Work Experience + Gender Diversity

And after shortlisting:

AWT + PI + the earlier composite score

The new policy specifically says that the raw application rating is based on the candidate's 10th percentage, 12th percentage, undergraduate percentage, gender and full-time work experience.

So, if you were hoping that a strong CAT score would completely erase your academic profile, that is not what the new policy says.

However, the manner in which those academic scores are calculated has changed substantially.

2. The Biggest Change: One Common Table for 10th, 12th and Graduation

This is arguably the most visible change in the new selection criteria.

For 2027–29, IIMA has introduced one common scoring table for:

• Class 10
• Class 12
• Bachelor's degree

The same table is used irrespective of the academic stream or undergraduate discipline.

So if a candidate has:

• 88% in Class 10 → 8 points
• 88% in Class 12 → 8 points
• 88% in graduation → 8 points

The same thresholds apply to all three.

Why is this a big change?

Last year, the scoring was considerably more complicated.

Class 12 marks were evaluated differently depending on whether the candidate was from:

• Science
• Commerce
• Arts/Humanities

Graduation marks were evaluated differently depending on the candidate's Academic Category, or AC.

For example, the 2026–28 policy had different graduation scoring tables for AC-1, AC-2, AC-3, AC-4/AC-6 and AC-5.

That meant the same percentage in graduation could result in a different rating score depending on the candidate's academic background.

Now?

The academic percentage-to-rating conversion itself is much simpler.

Same percentage → same rating score.

But there is an important second layer to the new system, which means this does not mean all academic backgrounds are treated identically.

That brings us to the next major change.

3. Academic Categories Are Gone. Undergraduate Disciplines Are In.

Last year, IIMA grouped undergraduate degrees into broad Academic Categories, commonly referred to as AC-1, AC-2, AC-3, AC-4, AC-5 and AC-6.

These categories covered large groups of degrees.

For example, the previous system clubbed several commerce, economics, finance and management degrees together under AC-3.

For 2027–29, IIMA has replaced this structure with 20 undergraduate disciplines.

The new UG disciplines are:

The final classification of an academic programme remains at the discretion of the IIMA Admissions Committee.

One important correction

You may see some discussions referring to 22 undergraduate disciplines.

The official PGP 2027–29 admission policy, however, lists 20 undergraduate disciplines in Table 3.

So for an IIMA-focused article or social media post, 20 is the number that should be used based on the official policy.

4. So Why Introduce UG Disciplines If The Academic Scoring Is Now Common?

This is where the new system becomes interesting.

You might initially think:

If everyone gets the same academic scoring table, doesn't that mean IIMA has removed academic-background differences?

Not quite.

IIMA now calculates a Raw Composite Score first.

This consists of:

65% CAT

35% Normalized Application Rating

The Application Rating includes:

• Class 10
• Class 12
• Graduation
• Work experience
• Gender diversity

Once this Raw Composite Score is calculated, it is normalized within the candidate's undergraduate discipline.

5. How Does Undergraduate Discipline-Wise Normalization Work?

This is probably the most important part of the new policy to understand.

IIMA says:

Normalized Composite Score = Raw Composite Score ÷ Average of the top 1% raw composite scores within the applicant's undergraduate discipline

There is also a safeguard:

• At least 5 raw composite scores will be considered
• At most 100 raw composite scores will be considered

for determining the top 1% benchmark for a discipline.

In simple terms:

Imagine two candidates:

Candidate A: Commerce
Candidate B: Management

Both may receive the same academic rating based on their percentages.

But they aren't necessarily being benchmarked against exactly the same group.

Their raw composite scores are normalized against the performance of candidates within their respective undergraduate disciplines.

This is a major departure from the older system, where much broader academic categories could contain several different disciplines.

6. Why Could This Help Some Candidates?

Consider the old system.

Suppose Commerce and Management degrees were placed within the same broad academic category.

If the two groups had very different distributions of academic scores, candidates from one discipline could potentially benefit from or be disadvantaged by being clubbed with the other.

Under the new system, the comparison becomes more granular.

For example:

Instead of broadly comparing:

Commerce + Management

the new system can distinguish:

Commerce, Accounting & Finance

from

Management

That same principle applies to areas that were earlier grouped more broadly.

Arts & Humanities, Social Sciences, Law, Journalism & Media and other disciplines now appear separately in the new framework.

Potential advantage

Candidates whose disciplines were previously clubbed into a broader category may now be compared against a more relevant peer group.

This could particularly help candidates from disciplines that were previously diluted inside a much larger academic category.

7. But There Is a Catch: Normalization Depends on Your Applicant Pool

This is where candidates should be careful about calling the new system universally "better."

We don't yet know:

• how many CAT 2026 candidates will fall into each discipline,
• how strong each discipline's applicant pool will be,
• what the distribution of academic scores will look like,
• what the top 1% benchmark will be for each discipline.

And therefore, the exact advantage or disadvantage cannot be predicted in advance.

Suppose a particular discipline attracts a very strong pool of applicants.

The benchmark for the top 1% could consequently be high.

Another discipline may have a different applicant profile.

That means the same raw composite score can potentially produce different normalized composite scores depending on the discipline in which the candidate is classified.

This is why candidates should be cautious about online calculators claiming to predict an exact IIMA call based on the new policy.

The actual applicant pool is still unknown.

8. Advantage: More Granular Treatment of Academic Backgrounds

This is one of the strongest arguments in favour of the new system.

Under the old system, several degrees could sit inside one broad Academic Category.

The new system breaks the applicant pool into much more specific undergraduate disciplines.

Potential beneficiaries include candidates from:

• Social Sciences
• Law
• Journalism & Media
• Arts & Humanities
• Mathematics
• Statistics & Actuarial Science
• Computer Science & IT
• Management
• Economics
• Commerce, Accounting & Finance

and other more specifically defined disciplines.

Instead of treating very different academic backgrounds as one large group, IIMA is now creating more granular comparison groups.

Why this matters

A candidate's raw academic score is no longer the only thing that matters.

The peer group against which that score is normalized matters too.

That is a meaningful structural change.

9. Disadvantage: Some Candidates Who Benefited From The Old Categories May Lose Out

Every normalization system creates winners and losers.

If a particular academic category previously worked in your favour, moving to a more granular discipline could reduce that advantage.

For example, if candidates from two disciplines were earlier grouped together and one group tended to have stronger academic scores, candidates from the other group may have benefited from the broader comparison.

Under the new system, that effect could disappear.

Similarly, a candidate who previously benefited from the way their degree was classified under an AC may find that the new discipline-specific normalization produces a different outcome.

This is important:

The new system is not designed to guarantee that every candidate gets a better score.

It is designed to change the comparison framework.

10. Another Major Change: The Old AC-RC Shortlisting System Is Gone

This is one of the biggest changes that could easily get overlooked.

Last year's IIMA process had a separate shortlisting structure involving:

Academic Category + Reservation Category

or AC-RC groups.

There were upper limits on the number of candidates that could be shortlisted from different AC-RC combinations.

For example, the 2026–28 policy specified different upper limits for General, NC-OBC, SC, ST and PwD candidates across academic categories.

The earlier system also had additional conditions around academic performance and minimum performance requirements.

For 2027–29:

This AC-RC based upper-limit structure is no longer part of the published shortlisting formula.

Instead, the process broadly becomes:

CAT + Application Rating

↓

Raw Composite Score

↓

UG Discipline-wise Normalization

↓

CAT Cut-off

↓

AWT + PI shortlist

This is a much simpler structure to understand.

11. Minimum Academic Performance Conditions Have Also Been Removed

This could be one of the most important changes for candidates with weaker school or graduation profiles.

Under last year's process, IIMA had additional criteria related to academic performance.

For example, one of the previous criteria required the average of the Class 10 and Class 12 percentages to meet specified thresholds depending on the stream.

The 2026–28 shortlisting criteria also had a minimum graduation percentage condition linked to the 80th percentile of the relevant Academic Category group.

These conditions are no longer present in the new shortlisting framework.

This does not mean academic marks no longer matter.

They still contribute to the Application Rating.

But there is no longer the same additional academic-performance filter sitting on top of the composite score.

12. What Does This Mean For Someone With Low 10th or 12th Marks?

Potentially, this is good news.

Suppose a candidate has:

10th: 72%
12th: 68%
Graduation: 85%

Under the new common table, those translate to:

• 10th → 5
• 12th → 3
• Graduation → 8

The candidate does not get a zero simply because their school marks are lower.

More importantly, the previous minimum-performance conditions that could eliminate candidates based on academic thresholds have been removed.

But don't misread this.

A candidate with weak academics still receives fewer Application Rating points than someone with stronger academics.

And CAT remains 65% of the Raw Composite Score.

So:

Weak academics are less restrictive than before, but they are not irrelevant.

13. What Has Stayed Exactly The Same? Work Experience

There is no change in the work-experience scoring formula.

The maximum work-experience score remains 5.

For example:

12 months: 0.2 × 1 = 0.2

24 months: 0.2 × 13 = 2.6

36 months: 0.2 × 25 = 5

More than 36 months: 5

So if you were hoping for a major change in how IIMA rewards work experience, there isn't one.

14. Gender Diversity Points Also Remain

IIMA continues to award:

3 points to non-male candidates

Male candidates receive:

0 points

This remains part of the Application Rating.

So despite the restructuring, this component has not been removed.

15. CAT Still Carries 65% at the Shortlisting Stage

One of the easiest misconceptions would be to assume that IIMA has reduced the importance of CAT because it has changed the academic system.

It hasn't.

For the Raw Composite Score:

65% = CAT Total Percentile

35% = Normalized Application Rating

The official formula is:

Raw Composite Score = 0.35 × Normalized Application Rating + 0.65 × (CAT Total Percentile / 100)

So CAT remains the dominant component at the shortlisting stage.

16. IIMA's CAT Cut-offs Have Not Changed

The minimum CAT percentile requirements for the 2027–29 batch remain the same as those published for the previous cycle.

IIM Ahmedabad CAT 2026 Minimum Cut-offs

The sectional requirements apply to:

VARC + DILR + QA

These are minimum qualifying cut-offs, not the percentile required to guarantee an IIMA interview call. IIMA explicitly notes that the actual cut-offs can be changed depending on the applicant pool and CAT score distribution.

So don't make this mistake:

95 percentile ≠ IIM Ahmedabad call

It only means you have cleared the published minimum overall cut-off for a General/EWS non-PwD candidate.

Your composite score still determines whether you make the shortlist.

17. The Final Selection Formula Has Changed

This is another important change.

Once candidates have completed the AWT and PI, IIMA calculates the Final Composite Score (FCS).

For 2027–29:

So:

Final Composite Score

= 50% PI + 10% AWT + 40% Normalized Composite Score

18. What Was The Formula Last Year?

For the 2026–28 batch, the final selection formula was:

50% PI

10% AWT

25% CAT

15% Application Rating

The 2026–28 shortlisting and selection documents explicitly separated the CAT and Application Rating components in the final composite.

The new system instead carries forward the 40% normalized composite score.

Since that composite score itself consists of:

65% CAT + 35% Application Rating

the effective final contribution becomes:

CAT:

40% × 65% = 26%

Application Rating:

40% × 35% = 14%

Therefore, the new final selection can effectively be understood as:

19. CAT's Effective Final Weight Has Increased Slightly

This is a subtle but important change.

Last year:

CAT = 25%

This year:

CAT = 26%

So CAT's effective contribution to the final selection has increased by 1 percentage point.

At the same time:

Application Rating

15% → 14%

So the change is not dramatic.

But directionally, CAT matters marginally more than it did last year.

For CAT 2026 aspirants, this is one reason the safest strategy remains straightforward:

Get the highest CAT percentile you can.

20. Is The New System Better For CAT Aspirants?

There isn't one universal answer.

The new system is clearly simpler.

But whether it is better for an individual candidate depends on their academic background and the composition of their undergraduate discipline.

Let's break it down.

Advantages of The New IIMA Selection Criteria

1. The criteria are much easier to understand

Last year's system had:

• different Class 12 tables
• multiple graduation tables
• Academic Categories
• AC-RC groups
• upper limits
• additional academic conditions
• multiple shortlisting stages

The new system is much cleaner.

You can broadly understand the process as:

Academic + Work Ex + Gender Diversity

↓

35% Application Rating

65% CAT

↓

UG Discipline Normalization

↓

AWT + PI

This is a major improvement in transparency and readability.

2. Class 12 stream no longer changes the scoring table

Previously, Science, Commerce and Arts/Humanities candidates were evaluated using different Class 12 scoring thresholds.

Now everyone gets the same table.

This creates a much simpler rule:

Your percentage determines your score, not your Class 12 stream.

That is easier for candidates to understand and compare.

3. Candidates with weaker academics no longer face the same additional filters

The removal of the earlier academic performance conditions could help candidates who don't have a traditionally strong 10th/12th/graduation profile.

They still lose some Application Rating points for lower marks, but they are not facing the same additional minimum-performance conditions that existed under the previous process.

This could give some candidates another shot at the IIMA shortlist.

4. Smaller academic disciplines get more specific benchmarking

The move from broad Academic Categories to undergraduate disciplines could benefit candidates whose academic backgrounds were previously grouped with very different degrees.

For example, disciplines such as:

Law, Journalism & Media, Social Sciences, Mathematics and Arts & Humanities

now have clearer separate identities in the framework.

This could reduce some of the distortion created when multiple disciplines were clubbed together.

5. Multiple undergraduate degrees get a potentially useful benefit

The new policy specifically addresses candidates with multiple undergraduate degrees.

For each relevant undergraduate discipline, IIMA can calculate a normalized composite score.

The highest normalized composite score will be used for shortlisting.

That is a useful provision for candidates with multiple undergraduate qualifications.

6. The final formula is easier to interpret

Instead of separately tracking multiple final-stage components, candidates can now understand the structure as:

50% PI + 10% AWT + 40% normalized composite

And that 40% itself contains:

65% CAT + 35% Application Rating

This is considerably cleaner than the previous final formula.

Disadvantages / Potential Risks of The New System

1. Your UG discipline can now have a meaningful impact

This is probably the biggest uncertainty.

Your raw composite score is normalized within your undergraduate discipline.

Therefore, your outcome depends not only on your own score but also on the applicant pool within your discipline.

If your discipline has an unusually strong applicant pool, the benchmark could be high.

This makes it difficult to predict your chances before the actual CAT 2026 applicant pool is known.

2. Some candidates may lose an advantage they had under the old AC system

The old system created broad Academic Categories.

If your degree happened to be placed in a category where the scoring framework worked in your favour, the new system could change that advantage.

A candidate who would have benefited from the old grouping may not necessarily benefit from the new discipline-wise normalization.

In other words:

A change that helps one academic background can hurt another.

3. It is harder to predict your IIMA call using historical data

This is perhaps the biggest practical problem for aspirants.

A lot of CAT preparation involves questions such as:

What percentile do I need for IIMA?

But the new normalization system makes historical comparisons less straightforward.

The relevant question is no longer just:

What is my CAT percentile?

It also involves:

What is my raw composite score?

Which UG discipline will I be classified into?

What does the applicant pool in that discipline look like?

What will the top 1% benchmark be?

Since those numbers are not known yet, precise call predictions are inherently uncertain.

4. The New System Does Not Mean Academics Have Become Irrelevant

This is another misconception worth clearing up.

The common table makes the process simpler, but academics still contribute:

10th → up to 10 points

12th → up to 10 points

Graduation → up to 10 points

Then:

Work Experience → up to 5 points

Gender Diversity → up to 3 points

So the raw Application Rating can go up to 38 points before normalization.

Academics still matter.

The difference is that the scoring and comparison mechanism has changed.

5. The New Criteria Do Not Make IIMA Predictable

This is perhaps the most important takeaway.

The new policy is simpler to read, but that does not mean it is easier to predict.

IIMA itself states that the cut-offs depend on factors such as the applicant pool and CAT score distribution and reserves the right to change them.

And the new UG normalization adds another variable.

So candidates should be careful with online calculators claiming:

"You have exactly X% chance of getting an IIMA call."

The new system does not provide enough information for that kind of certainty.

IIM Ahmedabad Selection Criteria: Old vs New

Here's the simplest way to understand the transition.

The previous criteria and new policy confirm that the major shift is in how academic backgrounds are grouped, normalized and filtered, rather than a wholesale change in the parameters IIMA considers.

What Does This Mean For Different Types of CAT Aspirants?

If you have a strong academic profile

The new system is not necessarily a disadvantage.

You still receive strong Application Rating points and CAT continues to carry significant weight.

Your biggest focus should remain:

Maximize CAT percentile + prepare strongly for PI.

If you have average academics

The removal of some of the previous academic-performance filters could be positive.

You are still losing points relative to someone with a stronger academic record, but your profile is not automatically constrained by the same additional conditions.

A strong CAT score becomes particularly important.

If you have weak 10th/12th marks

The new framework may give you a better shot than the old system because the additional academic filters have been removed.

But there is no magic reset.

A low academic score still means fewer Application Rating points.

Your CAT performance therefore becomes even more important.

If you come from a non-traditional academic background

This could potentially be one of the more interesting changes for you.

The new undergraduate disciplines are much more granular than the previous broad AC structure.

Candidates from areas such as:

Law, Journalism, Social Sciences, Arts & Humanities, Mathematics, Statistics and other specialized disciplines

may now be compared within a more specific peer group.

But the actual impact will depend on the applicant pool in each discipline.

If you have significant work experience

There is no major change to your work-experience scoring.

You can still get up to 5 points for work experience.

So don't expect the new selection criteria to dramatically alter your work-ex advantage.

The Most Important Takeaway For CAT 2026 Aspirants

The IIMA policy looks complicated because of the new normalization system, but the strategy for a CAT aspirant is actually quite simple.

You control:

Your CAT preparation.

You don't control:

• how many people apply from your discipline,
• their academic scores,
• the top 1% benchmark,
• the final normalization factor,
• the eventual applicant pool,
• or the exact shortlist threshold.

So while it is useful to understand the new criteria, there is limited value in spending weeks trying to reverse-engineer an exact IIMA call probability.

The biggest controllable variable remains:

Your CAT percentile.

And once you get the call, the focus shifts dramatically towards:

PI + AWT.

Final Verdict: Is IIMA's New Selection Criteria Better?

From a process perspective, yes.

The new policy is significantly easier to understand than last year's framework.

The move to:

One academic scoring table

More granular undergraduate disciplines

Discipline-wise normalization

Removal of AC-RC upper limits
Removal of additional academic-performance filters

makes the process considerably cleaner.

But from a candidate's perspective, the answer is more nuanced.

Potential winners:

• Candidates who were disadvantaged by broad academic-category grouping
• Candidates from more narrowly defined UG disciplines
• Candidates who previously failed additional academic-performance conditions
• Candidates with weaker school profiles but strong CAT performance

Potential losers:

• Candidates who benefited from the old AC grouping
• Candidates whose new discipline has a particularly competitive applicant pool
• Candidates who were previously advantaged by the old academic scoring thresholds

And because the new discipline-wise normalization depends on the actual CAT 2026 applicant pool, it is too early to say exactly which disciplines will gain or lose.

The fairest conclusion is therefore:

IIMA has made its selection criteria simpler, but not necessarily more predictable.

For CAT 2026 aspirants, understanding the new framework is useful. But obsessing over the normalization formula won't improve your CAT score.

The controllable part is still the same: prepare well, maximize your CAT percentile, and be ready for AWT and PI if the call comes.

Official IIMA source

IIM Ahmedabad: Admission Policy for PGP 2027–29