where A A ho indicates the relevant average and median AIPI score for country for relevant income categories. ii,tthe oo mm

# III-

# _III.aGlobal overperformers_

The analysis of the two charts below, one unweighted and the other weighted by population size, reveals important insights about the relationship between the AIPI and the ECI trade, research composite obtained from 125 matching countries at a global level (Figure 3).<sup>18</sup> A strong relationship emerges between AIPI and ECI, with values of 0.79 (unweighted) and 0.70 (weighted), indicating that approximately three-quarters of the variance in AIPI is explained by the variance in ECI, and vice RR<sup>2</sup> versa. The partial correlations ( ) of 0.89 (unweighted) and 0.84 (weighted) further indicate a very high positive linear correlation, and it is statically significant at 0.1 percent. These results highlight the oo strong (and expected) link between economic complexity and AI preparedness, demonstrating that greater economic sophistication—reflected in the diversity and complexity of exports and research output—significantly enhances a country's capacity to adopt and integrate AI technologies effectively, irrespective of population weighting.

**Figure 3:** Global relationship between AIPI and ECI

<!-- Start of picture text --> a) Unweighted analysis b) Population-weighted analysis<br>.6.5.4.3.8.7 r = 0.89N = 125 R2 = 0.79 mli yem bfatgosdnginlbypngtjk azemngcoddzacivmdgirqmmr cogmozcmruzbngabwalaokazbolvengabecubgdhndmarpakzwe sen benkhmlkanamrwatzadomzmbomngha vnmeth arm ugamdaperalbtun blrbihkwtukr egy mkdbgrqatjor ind idnkencri arekgzurygtmpirnrchny russaujam phl mys pan ltusrbcoltharousvkgeolbnchlhrvgrcarg za f prt po svnturl b r a twnkormexauscze hkg nzl sgp hun nor esp dnkjpn itafin fra israutbelcani r l nld swedeu gbrcheusa .3.4.5.6.7.8 r = 0.84N = 125 R2 = 0.70 ml yemi bfatgosdnginlbypngtjk azemngdzacodcivmdgirqmmr cogmozcmruzbbwalaongakazbolvengabecubgdhndmarzwepak sen benkhmnamlkarwadomtzaomnzmbgha vnm arm ethmdaugaperalbtun blrbihkwtukrmkdbgrqat egy jor idnicri nd kenarekgzurypgtmrirny saujamchnrus pan mys ph l ltusrbcoltha svk rougeolbnchlhrvgrcarg zaf prt po svnturl b rtwnkor a mexauscze hkg nzl sgp hun nor esp dnk jpnfinitafisr ra autibelcan r l nld swedeu gbrche usa<br>.2 .2<br>afg afg<br>.1 .1<br>0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>Economic Complexity Index [Trade-Research PCA] (OEC, 2021-22) Economic Complexity Index [Trade-Research PCA] (OEC, 2021-22)<br>AIPI≥0.7 AIPI≥0.7<br>Other Countries Other Countries<br>Overperformers Overperformers<br>Linear Fit Line Linear Fit Line [weighted pop. size]<br>AI Prepardness Index (IMF, 2023) AI Prepardness Index (IMF, 2023)<br><!-- End of picture text --> <u>Source: The AIPI score for 2023 is obtained from the IMF website [https://www.imf.org/external/datamapper/datasets/AIPI] and the ECI on</u> trade and research for 2021-22 are obtained from the OEC website [https://oec.world/en/rankings/eci/hs6/hs96?tab=ranking]. Notes: The first principal component (PCA) of ECI trade and ECI research, with an eigenvalue exceeding 50 percent, is used to capture the multidimensional aspects of national economic complexity. Population size for 2023, used for the weighted analysis, is sourced from the “wbopendata” module in Stata (Azevedo, 2020), with data for Taiwan Province of China obtained from the Statista website. All countries with an observed AIPI score exceeding 0.7 (the weighted average and median score for HICs) are highlighted in the grey quadrant. Among these, only countries with AIPI scores surpassing their predicted values (above the linear fit line) are marked in yellow and identified as global overperformers.

Both charts highlight the top performers in AI preparedness, concentrated in the northeast quadrants. Consistent with previous BMA findings and the critical role of initial conditions in AI readiness, these top performers are exclusively HICs. To identify global overperformers within this

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