IB Math AI HL & SL — May 2026 Topic Predictions | Sev7n
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📊 Mathematics: Applications & Interpretation (AI)

IB Math AI HL & SL
Topic Prediction Guide

Paper 1, Paper 2 & Paper 3 (HL) subtopic frequency analysis for IBDP May 2026. Statistics, modelling and technology — every subtopic mapped.

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4Years Analysed
5Topics Mapped
HL & SLBoth Levels
P1·P2·P3All Papers
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Home› IB Math AI HL & SL Topic Prediction May 2026

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You are viewing: IB Math AI Higher Level (HL) All 3 papers shown. Paper 1 (calc, 2 hrs, short Q) + Paper 2 (calc, 2 hrs, extended Q) + Paper 3 (calc, 60 min, modelling). Weightings: P1=30% · P2=30% · P3=20% · IA=20%.
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Paper 1 — Short Response (Free Preview)
Duration: 2 hrs (HL) / 90 min (SL) | Marks: 110 (HL) / 80 (SL) | Weighting: 30% (HL) / 40% (SL) | Short questions only — no extended response | Calculator required throughout — GDC essential
📊 AI Paper 1 is exclusively short-response questions. Unlike AA, there is no Section A/B split — all questions are short. The GDC is used throughout. Statistics and probability carry the heaviest weighting across AI. Paper 1 tends to cover more topics more briefly; Paper 2 goes deeper on fewer topics.

Paper 1 subtopic frequency — Topics 1 (Number & Algebra) + 2 (Functions) preview

IB MATH AI — PAPER 1 (SHORT RESPONSE, CALCULATOR) SUBTOPIC FREQUENCY | May 2021–2024 | SL & HL
Free preview: Topic 1 (Number & Algebra) + Topic 2 (Functions start) · Topics 3–5 + HL extras locked below
#TopicSubtopic M21M22M23M24 FreqAvg MarksHL only?May 2026
TOPIC 1: NUMBER & ALGEBRA — financial maths, sequences, applications
1.1Num & AlgFinancial mathematics — compound interest, depreciation, amortisation, annuities using GDC TVM✔✔✔✔48–12SL&HL⭐⭐⭐⭐⭐ CERTAIN
1.2Num & AlgSequences & series — arithmetic, geometric, sigma notation, applications and modelling✔✔✔✔46–10SL&HL⭐⭐⭐⭐
1.3Num & Alg (HL)Complex numbers — Cartesian form, Argand diagram (HL); used in modelling contexts HL—✔✔—25–8HL⭐⭐⭐ HL
TOPIC 2: FUNCTIONS — modelling with functions, all calculator-based in AI
2.1FunctionsModelling — linear, quadratic, exponential, logistic, sinusoidal — fitting and interpreting✔✔✔✔410–16SL&HL⭐⭐⭐⭐⭐ CERTAIN
2.2FunctionsSinusoidal functions — A, B, C, D in y=A sin(Bx+C)+D; period, amplitude, applications✔✔✔—36–10SL&HL⭐⭐⭐⭐

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Paper 1 — Topics 3, 4, 5 + HL extras (Full Analysis)
Topics 1 (Number & Algebra) and 2.1–2.2 are shown above as free preview. Now showing the remaining sections.
#TopicSubtopic M21M22M23M24 FreqAvg MarksHL only?May 2026
TOPIC 2: FUNCTIONS (continued)
2.3Functions (HL)Piecewise models, logistic functions, log-log and semi-log linearisation, scaling data HL✔✔—✔36–10HL⭐⭐⭐⭐ HL
TOPIC 3: GEOMETRY & TRIGONOMETRY — applied and 3D contexts
3.1Geo & Trig3D geometry — volumes and surface areas of solids, right triangles in 3D, bearings✔✔✔✔46–10SL&HL⭐⭐⭐⭐
3.2TrigonometrySine rule, cosine rule, area of triangle — applied problems, non-right triangles✔✔✔—35–8SL&HL⭐⭐⭐⭐
3.3Voronoi (HL)Voronoi diagrams — nearest neighbour, constructing from perpendicular bisectors, applications HL✔✔✔✔48–14HL⭐⭐⭐⭐⭐ HL
TOPIC 4: STATISTICS & PROBABILITY — dominant topic in AI (heaviest weighting)
4.1StatisticsDescriptive statistics — mean, median, mode, standard deviation, IQR, box plots, cumulative frequency✔✔✔✔48–14SL&HL⭐⭐⭐⭐⭐ CERTAIN
4.2StatisticsCorrelation & regression — Pearson r, Spearman rank, scatter plots, linear regression y=ax+b, interpolation/extrapolation✔✔✔✔48–12SL&HL⭐⭐⭐⭐⭐ CERTAIN
4.3ProbabilityProbability — basic rules, tree diagrams, Venn diagrams, conditional probability, independent events✔✔✔✔46–10SL&HL⭐⭐⭐⭐⭐
4.4DistributionsNormal distribution — P(a<X<b) with GDC, inverse normal, standardisation (z-scores)✔✔✔✔48–12SL&HL⭐⭐⭐⭐⭐ CERTAIN
4.5DistributionsBinomial distribution — P(X=k), P(X≤k) using GDC, mean = np, variance, applications✔✔✔✔46–10SL&HL⭐⭐⭐⭐⭐
4.6HypothesisHypothesis testing — chi-squared test (independence/goodness of fit), t-test, setting up H₀ and H₁, p-value interpretation✔✔✔✔48–14SL&HL⭐⭐⭐⭐⭐ CERTAIN
4.7Stats (HL)Spearman’s rank correlation — calculate, interpret, hypothesis test for correlation HL✔✔✔✔46–10HL⭐⭐⭐⭐⭐ HL
4.8Stats (HL)Markov chains — transition matrices, steady-state probabilities, long-term behaviour HL✔—✔✔38–12HL⭐⭐⭐⭐ HL
TOPIC 5: CALCULUS — basic calculus in applied/modelling contexts (AI is lighter on calculus than AA)
5.1CalculusDifferentiation — polynomials, tangents/normals, max/min, increasing/decreasing in context✔✔✔✔46–10SL&HL⭐⭐⭐⭐
5.2CalculusIntegration — area under curve in context, definite integral with GDC, kinematics (distance from v(t))✔✔✔—35–8SL&HL⭐⭐⭐⭐
5.3Calculus (HL)Differential equations — modelling with DEs, slope fields, Euler’s method, separation of variables HL✔✔✔✔410–16HL⭐⭐⭐⭐⭐ HL
5.4Calculus (HL)Further calculus — L’Hôpital’s rule, improper integrals, limits in modelling contexts HL✔—✔—26–10HL⭐⭐⭐ HL

Based on IB Math AI past papers May 2021–2024 | Calculator allowed throughout | Statistics & Probability = dominant topic | HL rows greyed in SL view

📊 AI Paper 1 mark allocation insight: Statistics and Probability consistently accounts for 40–50% of AI Paper 1 marks (across all sittings). Functions (modelling) 20–25%. Financial Maths 10–15%. Calculus 10–15%. Geometry/Trig 10–15%. HL students: Voronoi, DEs, Markov chains, and Spearman’s rank add 30–40 marks to the HL paper.

🔴 Top 5 subtopics — learn these first

  • Hypothesis testing — chi-squared + t-test. Appears in every paper. Know how to set up H₀, run GDC test, interpret p-value.
  • Normal distribution — P(a<X<b) and inverse normal. GDC essential. Every paper.
  • Regression & correlation — draw scatter plot, find line of best fit, calculate r, interpret. Every paper.
  • Financial mathematics — compound interest, TVM on GDC. Every paper.
  • Modelling with functions — exponential, logistic, sinusoidal. Every paper, often the extended question.

📊 AI Paper 1 exam technique

  • Every question allows GDC — master your calculator menus (Statistics, TVM, Solve)
  • Interpretation matters as much as calculation — “what does r = 0.92 mean?”
  • For hypothesis tests: always state H₀ and H₁ clearly, and conclude in context
  • For modelling: define variables, state the model, interpret the gradient/parameters
  • Short questions = quick marks — don’t overthink. If it’s long, you’re doing too much.
  • HL: Voronoi diagrams need accurate construction — practise with compass/ruler
📈
Paper 2 — Extended Response Questions (Calculator)
Duration: 2 hrs (HL) / 90 min (SL) | Marks: 110 (HL) / 80 (SL) | Weighting: 30% (HL) / 40% (SL) | Extended response only — longer questions, multi-part, real-world contexts | Calculator required throughout
📈 AI Paper 2 goes deep on fewer topics. Extended questions require you to apply multiple concepts in a sustained real-world context (e.g. a full modelling investigation, or a complete statistical study). The final part of each question is typically challenging and tests synthesis. Interpretation of results in context is always assessed.

What dominates AI Paper 2

  • Modelling with functions — large extended questions fitting models to data, interpreting, extrapolating
  • Statistical investigation — complete hypothesis test from data to conclusion, regression analysis
  • Financial mathematics — multi-step loan, investment, depreciation calculations
  • Differential equations (HL) — modelling real scenarios; populations, cooling, spread of disease
  • Graph theory (HL) — minimum spanning trees, Chinese Postman, Travelling Salesman
  • Kinematics — velocity, acceleration, displacement in real context via calculus

Paper 2 exam technique

  • Read the context carefully — real-world setting defines what answers mean
  • Always state your model clearly before using it (define variables)
  • Show GDC working: write down the equation/test you ran before stating the answer
  • For stats: write H₀, run test, state p-value, compare to significance level, conclude in words
  • For modelling: interpret gradient, y-intercept, and parameters in the real-world context
  • If stuck on a part: use the answer given in the question and move forward — method marks available

Paper 2 key topics & mark allocation — May 2021–2024

IB MATH AI — PAPER 2 (EXTENDED RESPONSE, CALCULATOR) KEY TOPICS | May 2021–2024 | SL & HL
Extended multi-part questions | Real-world context always present | Interpretation = marks | SL: HL-only topics greyed
#TopicSubtopic / Context M21M22M23M24 FreqMarksMay 2026
STATISTICS — dominant in Paper 2 extended questions
4AStats ExtendedComplete statistical study — sample data, regression, correlation, hypothesis test + interpretation in context✔✔✔✔420–30⭐⭐⭐⭐⭐ CERTAIN
4BProbabilityProbability extended — conditional probability, expected value, combined distributions in real context✔✔✔—312–18⭐⭐⭐⭐
FUNCTIONS — modelling extended questions
2AModellingExtended modelling investigation — fit model to data, find parameters, predict, evaluate model appropriateness✔✔✔✔420–28⭐⭐⭐⭐⭐ CERTAIN
NUMBER & ALGEBRA
1AFinancial MathsLoans, mortgages, investments — multi-step with TVM solver; find monthly payment, total interest, balance✔✔✔✔412–18⭐⭐⭐⭐⭐
HL ONLY — ADDITIONAL TOPICS IN PAPER 2
HL.1Graph Theory (HL)Minimum spanning tree (Prim/Kruskal), Chinese Postman, Travelling Salesman — weighted graphs HL✔✔✔✔414–20⭐⭐⭐⭐⭐ HL
HL.2DEs & Modelling (HL)Differential equations in extended real-world context — population growth, cooling, spread of disease HL✔✔✔✔416–24⭐⭐⭐⭐⭐ HL
HL.3Advanced Stats (HL)Bivariate analysis — non-linear regression, log linearisation, residuals; Spearman test extended HL✔✔—✔312–18⭐⭐⭐⭐ HL
🔒

Paper 3 is HL only

AI SL students sit Paper 1 and Paper 2 only. Paper 3 is exclusive to HL. Switch to HL to see Paper 3 guidance.

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Paper 3 — Extended Modelling Problem (HL Only)
Duration: 60 minutes | Marks: 55 | Weighting: 20% (HL) | 1 extended modelling or problem-solving investigation | Calculator allowed | Real-world data provided — apply AI tools to analyse and model
🔬 AI Paper 3 is one big investigation — different from AA Paper 3. AI HL Paper 3 presents a single extended real-world investigation with data. You apply statistical or mathematical tools progressively through 10–15 sub-parts. It tests how well you can select appropriate methods, apply GDC tools, and interpret results meaningfully. It rewards students who can think like data analysts.

What AI Paper 3 tests

  • Apply statistical tools to a new real-world dataset
  • Select appropriate hypothesis tests and justify the choice
  • Fit regression models and evaluate goodness of fit
  • Interpret results in the context of the investigation
  • Build up a complete mathematical model across multiple sub-parts
  • Draw conclusions and identify limitations of the approach

AI Paper 3 strategy

  • 60 minutes for ~55 marks — about 65 seconds per mark
  • Read the investigation context carefully before answering anything
  • Each sub-part often uses the result of the previous part
  • If a calculation fails: state your method, use an approximation, move on
  • Interpretation marks = easy marks — always explain what your result means
  • GDC fluency is critical — you cannot afford to be slow with statistics menus

Paper 3 historical themes — May 2021–2024

IB MATH AI HL — PAPER 3 THEME HISTORY | May 2021–2024 | HL ONLY
1 extended investigation per paper | Real data provided | Multiple methods applied progressively | Calculator required | Modelling + stats focus
YearInvestigation ThemePrimary Topics Key Methods UsedHL-Only ContentMay 2026 Signal
M21Environmental data analysis — temperature and species population modelling over timeStats, Modelling, CalculusRegression, hypothesis test, DE modelling, slope fieldsDEs + Advanced StatsEnvironmental/ecological data likely again
M22Sports/physical data investigation — fitting models to performance data, predicting outcomesStats, Functions, ModellingMultiple regression models, chi-squared, normal distribution, prediction intervalsAdvanced StatsReal-world data modelling very likely
M23Financial/economic modelling — loan repayment, investment growth, inflation modellingFinance, Functions, StatsTVM, DE for continuous growth, regression on economic data, Spearman correlationDEs + SpearmanFinancial modelling could recur
M24Medical/epidemiological data — disease spread, vaccination modelling, statistical analysis of health dataStats, DEs, ModellingSIR model using DEs + Euler, hypothesis tests on medical data, normal/binomialDEs + MarkovReal-world health/population data likely
🔬 May 2026 AI Paper 3 prediction: The theme rotates between environmental, social science, health and economic data. Any domain is possible. What is consistent: (1) a complete statistical analysis including hypothesis testing, (2) fitting at least one regression or growth model, (3) a calculus or DE component, (4) interpretation at every stage. Prepare: all hypothesis tests (chi-squared, t-test, Spearman), all regression types including non-linear, DEs (SIR model, Euler’s method), and graph theory (in case it appears in the investigation context).

About IB Math AI

IB Mathematics: Applications and Interpretation (AI) is the applied mathematics pathway. It emphasises statistics, modelling and the use of technology. AI HL is rigorous and demanding in its own way — the gap between AI SL and HL is significant, with HL adding graph theory, differential equations, Markov chains, Voronoi diagrams and advanced statistics.

Also studying Analysis & Approaches? See the AA prediction page →

AI HL vs SL — key differences

  • Paper 1: SL = 90 min / 80 marks / 40% | HL = 2 hrs / 110 marks / 30%
  • Paper 2: Same extended format, more marks at HL, HL-only questions
  • Paper 3: HL only — 60 min / 55 marks / 20%
  • HL-only content: Graph theory, Voronoi diagrams, Markov chains, DEs, Spearman test, complex numbers, log-log linearisation
  • Teaching hours: 150 hrs SL vs 240 hrs HL

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