We find AI ties for 40 of 81 Turing Award laureates

How much of computing's recognized talent has a connection to AI? We estimate that 40 of the 81 Turing Award laureates (49%) have a recorded link to AI through the people we track. For awards dated 2000 onward, the share is 61% (25 of 41 laureates).

We matched published fellow and award rosters to our research profiles. This gives each honor a denominator: all entries on the collected list. A match measures a connection to AI across a person's career. It includes past work and deceased researchers. The award itself can recognize work in another field. Our choice of people and the evidence needed for a match affect each share.

Key findings

• 49% of Turing Award laureates have a profile here. The share for awards since 2000 is 61%, with 25 matches among 41 laureates.
• The ACM Fellow class share rose from 17% to 37%. We match 60 of 355 fellows elected in 1994–1999, and 127 of 346 in 2020–2024.
• AAAI Fellows have 99% coverage. We match 373 of 378 entries. AAAI is an AI society, so its fellow list has a direct link to this site's subject.
• 24% of matched fellows with a recorded current workplace have a company role. This is 171 of 703 people; 86 also have a university role.

Computing honors show different degrees of overlap

Across the full collected rosters, we match 442 of 1,640 ACM Fellows (27%) and 171 of 812 IEEE Fellows evaluated by the Computer Society (21%). The IEEE comparison covers the classes from 2015 to 2026. It covers one society's evaluated classes within IEEE.

Horizontal bars show matched profile shares for 12 honor lists. AAAI Fellow: 99% (373/378). ACM Fellow: 27% (442/1,640). Turing Award: 49% (40/81). IEEE CS Fellow: 21% (171/812).

Source: AAAI Fellow; ACM rosters via Wikipedia, including Turing Award and ACM Fellow; IEEE Computer Society class releases. Matches as of 24 October 2026. Full roster links are in the data table.

Data table

Honor list	Years	Matched entries	All list entries	Share	Sources
AAAI Fellow	1990–2026	373	378	99%	AAAI Fellow
ACM Prize in Computing	2007–2025	14	20	70%	Prize in Computing
ACM A.M. Turing Award	1966–2025	40	81	49%	Turing Award
ACM Paris Kanellakis Theory and Practice Award	1996–2025	24	69	35%	Paris Kanellakis Theory and Practice Award
ACM Grace Murray Hopper Award	1971–2025	19	56	34%	Grace Murray Hopper Award
ACM Fellow	1994–2025	442	1,640	27%	ACM Fellow
IEEE Fellow (IEEE Computer Society evaluated)	2015–2026	171	812	21%	IEEE CS Fellow source 1, IEEE CS Fellow source 2, IEEE CS Fellow source 3, IEEE CS Fellow source 4, IEEE CS Fellow source 5, IEEE CS Fellow source 6, IEEE CS Fellow source 7, IEEE CS Fellow source 8, IEEE CS Fellow source 9, IEEE CS Fellow source 10, IEEE CS Fellow source 11 and IEEE CS Fellow source 12
ACM Doctoral Dissertation Award	1978–2025	21	129	16%	Doctoral Dissertation Award
ACM Eugene L. Lawler Award	1999–2024	2	16	13%	Eugene L. Lawler Award
ACM Software System Award	1983–2024	14	179	8%	Software System Award
ACM-IEEE CS Eckert-Mauchly Award	1979–2026	3	48	6%	Eckert-Mauchly Award
ACM-IEEE CS Ken Kennedy Award	2009–2023	0	15	0%	Ken Kennedy Award

These lists recognize different kinds of work. Their date ranges also differ. The dissertation list includes winners and honorable mentions; team award lists can have several entries for one award year. Each bar counts recipient entries. ACM awards without a collected Wikipedia recipient list are outside this comparison. The source links in the data table show the scope of each list.

AI connections by ACM Fellow election period

The matched share rose from 17% in 1994–1999 to 37% in 2020–2024, a change of 20 percentage points. We sum the matched people and the full class sizes within each period, so each elected fellow has the same weight.

The share is 17% (60 of 355) in 1994–1999 and 37% (127 of 346) in 2020–2024.

Source: ACM Fellow, matched to research profiles as of 24 October 2026. Period shares use summed class sizes.

Data table

Election years	Matched researchers	All fellows elected	Share
1994–1999	60	355	17%
2000–2004	26	164	16%
2005–2009	52	205	25%
2010–2014	62	236	26%
2015–2019	89	263	34%
2020–2024	127	346	37%

The latest period, 2025, has 26 matches among 71 fellows (37%). We show it separately because it contains fewer election years than the full periods above.

These cohorts describe when fellows were elected. Their profiles describe their careers through 24 October 2026. AI work can come before or after election, and the coverage of earlier careers can differ from the coverage of recent careers. The comparison gives a historical view of today's profile overlap.

Where the matched fellows work

We count 800 distinct people across the matched AAAI, ACM and IEEE CS fellow lists. After excluding recorded deaths, 703 have a current workplace in our career records. Of these, 171 (24%) have a company role and 593 (84%) have a university role. The groups overlap: 86 people have both.

The chart shows 13 workplaces, including all ties at the cutoff. Google leads with 40 fellows.

Source: Collected fellowship lists as of 24 October 2026; People of Superintelligence career records as of 24 October 2026. Recorded deaths are excluded.

Data table

Organization	Matched fellows
Google	40
Carnegie Mellon University	27
Massachusetts Institute of Technology	27
Stanford University	24
Cornell University	18
University of Southern California	18
Microsoft	17
University of California, Berkeley	15
University of Illinois Urbana-Champaign	15
University of Washington	15
Harvard University	13
Columbia University	12
University of Michigan	12

A person counts once at each parent organization, including concurrent roles. These are affiliations recorded as current as of 24 October 2026. They can include visiting and emeritus roles. The chart describes the matched fellows with known workplaces; it gives no workplace estimate for the unmatched members of the source lists.

Source note: AAAI and IEEE Computer Society rosters come from their published pages. ACM rosters come from the Wikipedia recipient lists saved with the collection. We use the checked matches in the collection and leave uncertain matches out. A person without a match can still have AI work. Our earlier posts examine honors named in biographies and the universities linked to prize winners.