Three lessons from chatting about strategy with ChatGPT: when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge
Large language models like ChatGPT are generating excitement about their potential use cases. A pair of business strategists decided to test whether the tool can support ideation, experimentation, evaluation, and storytelling as part of the strategy creation process. In a series of experiments, they...
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
[Place of publication not identified]
MIT Sloan Management Review
2023
|
| Ausgabe: | [First edition]. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/53863MIT64446/?ar |
| Zusammenfassung: | Large language models like ChatGPT are generating excitement about their potential use cases. A pair of business strategists decided to test whether the tool can support ideation, experimentation, evaluation, and storytelling as part of the strategy creation process. In a series of experiments, they posed a realistic question of strategy to ChatGPT, followed by iterative follow-up questions. In this article, they share three lessons that emerged from their experiments with generative AI. |
| Beschreibung: | Reprint #64446 |
| Umfang: | 1 Online-Ressource (5 Seiten) |
Internformat
MARC
| LEADER | 00000cam a22000002 4500 | ||
|---|---|---|---|
| 001 | ZDB-30-ORH-093388594 | ||
| 003 | DE-627-1 | ||
| 005 | 20240228122018.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230626s2023 xx |||||o 00| ||eng c | ||
| 035 | |a (DE-627-1)093388594 | ||
| 035 | |a (DE-599)KEP093388594 | ||
| 035 | |a (ORHE)53863MIT64446 | ||
| 035 | |a (DE-627-1)093388594 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 082 | 0 | |a 006.3/5 |2 23/eng/20230620 | |
| 100 | 1 | |a Stadler, Christian |e VerfasserIn |4 aut | |
| 245 | 1 | 0 | |a Three lessons from chatting about strategy with ChatGPT |b when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge |c Christian Stadler, Martin Reeves |
| 250 | |a [First edition]. | ||
| 264 | 1 | |a [Place of publication not identified] |b MIT Sloan Management Review |c 2023 | |
| 300 | |a 1 Online-Ressource (5 Seiten) | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Reprint #64446 | ||
| 520 | |a Large language models like ChatGPT are generating excitement about their potential use cases. A pair of business strategists decided to test whether the tool can support ideation, experimentation, evaluation, and storytelling as part of the strategy creation process. In a series of experiments, they posed a realistic question of strategy to ChatGPT, followed by iterative follow-up questions. In this article, they share three lessons that emerged from their experiments with generative AI. | ||
| 650 | 0 | |a Natural language processing (Computer science) | |
| 650 | 0 | |a Artificial intelligence |x Computer programs | |
| 650 | 4 | |a Traitement automatique des langues naturelles | |
| 650 | 4 | |a Intelligence artificielle ; Logiciels | |
| 650 | 4 | |a Artificial intelligence ; Computer programs | |
| 650 | 4 | |a Natural language processing (Computer science) | |
| 700 | 1 | |a Reeves, Martin |e VerfasserIn |4 aut | |
| 966 | 4 | 0 | |l DE-91 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/53863MIT64446/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
| 912 | |a ZDB-30-ORH | ||
| 951 | |a BO | ||
| 912 | |a ZDB-30-ORH | ||
| 049 | |a DE-91 | ||
Datensatz im Suchindex
| DE-BY-TUM_katkey | ZDB-30-ORH-093388594 |
|---|---|
| _version_ | 1821494940888203265 |
| adam_text | |
| any_adam_object | |
| author | Stadler, Christian Reeves, Martin |
| author_facet | Stadler, Christian Reeves, Martin |
| author_role | aut aut |
| author_sort | Stadler, Christian |
| author_variant | c s cs m r mr |
| building | Verbundindex |
| bvnumber | localTUM |
| collection | ZDB-30-ORH |
| ctrlnum | (DE-627-1)093388594 (DE-599)KEP093388594 (ORHE)53863MIT64446 |
| dewey-full | 006.3/5 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/5 |
| dewey-search | 006.3/5 |
| dewey-sort | 16.3 15 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | [First edition]. |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02140cam a22004092 4500</leader><controlfield tag="001">ZDB-30-ORH-093388594</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240228122018.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230626s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)093388594</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP093388594</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)53863MIT64446</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)093388594</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3/5</subfield><subfield code="2">23/eng/20230620</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Stadler, Christian</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Three lessons from chatting about strategy with ChatGPT</subfield><subfield code="b">when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge</subfield><subfield code="c">Christian Stadler, Martin Reeves</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">[First edition].</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[Place of publication not identified]</subfield><subfield code="b">MIT Sloan Management Review</subfield><subfield code="c">2023</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (5 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Reprint #64446</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Large language models like ChatGPT are generating excitement about their potential use cases. A pair of business strategists decided to test whether the tool can support ideation, experimentation, evaluation, and storytelling as part of the strategy creation process. In a series of experiments, they posed a realistic question of strategy to ChatGPT, followed by iterative follow-up questions. In this article, they share three lessons that emerged from their experiments with generative AI.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Natural language processing (Computer science)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Artificial intelligence</subfield><subfield code="x">Computer programs</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Traitement automatique des langues naturelles</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Intelligence artificielle ; Logiciels</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence ; Computer programs</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Natural language processing (Computer science)</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Reeves, Martin</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-91</subfield><subfield code="p">ZDB-30-ORH</subfield><subfield code="q">TUM_PDA_ORH</subfield><subfield code="u">https://learning.oreilly.com/library/view/-/53863MIT64446/?ar</subfield><subfield code="m">X:ORHE</subfield><subfield code="x">Aggregator</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
| id | ZDB-30-ORH-093388594 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-17T11:22:22Z |
| institution | BVB |
| language | English |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (5 Seiten) |
| psigel | ZDB-30-ORH TUM_PDA_ORH ZDB-30-ORH |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | MIT Sloan Management Review |
| record_format | marc |
| spelling | Stadler, Christian VerfasserIn aut Three lessons from chatting about strategy with ChatGPT when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge Christian Stadler, Martin Reeves [First edition]. [Place of publication not identified] MIT Sloan Management Review 2023 1 Online-Ressource (5 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Reprint #64446 Large language models like ChatGPT are generating excitement about their potential use cases. A pair of business strategists decided to test whether the tool can support ideation, experimentation, evaluation, and storytelling as part of the strategy creation process. In a series of experiments, they posed a realistic question of strategy to ChatGPT, followed by iterative follow-up questions. In this article, they share three lessons that emerged from their experiments with generative AI. Natural language processing (Computer science) Artificial intelligence Computer programs Traitement automatique des langues naturelles Intelligence artificielle ; Logiciels Artificial intelligence ; Computer programs Reeves, Martin VerfasserIn aut |
| spellingShingle | Stadler, Christian Reeves, Martin Three lessons from chatting about strategy with ChatGPT when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge Natural language processing (Computer science) Artificial intelligence Computer programs Traitement automatique des langues naturelles Intelligence artificielle ; Logiciels Artificial intelligence ; Computer programs |
| title | Three lessons from chatting about strategy with ChatGPT when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge |
| title_auth | Three lessons from chatting about strategy with ChatGPT when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge |
| title_exact_search | Three lessons from chatting about strategy with ChatGPT when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge |
| title_full | Three lessons from chatting about strategy with ChatGPT when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge Christian Stadler, Martin Reeves |
| title_fullStr | Three lessons from chatting about strategy with ChatGPT when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge Christian Stadler, Martin Reeves |
| title_full_unstemmed | Three lessons from chatting about strategy with ChatGPT when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge Christian Stadler, Martin Reeves |
| title_short | Three lessons from chatting about strategy with ChatGPT |
| title_sort | three lessons from chatting about strategy with chatgpt when generative ai s capacity for strategy creation is put to the test it reveals where its strengths lie and where humans still have the edge |
| title_sub | when generative AI's capacity for strategy creation is put to the test, it reveals where its strengths lie, and where humans still have the edge |
| topic | Natural language processing (Computer science) Artificial intelligence Computer programs Traitement automatique des langues naturelles Intelligence artificielle ; Logiciels Artificial intelligence ; Computer programs |
| topic_facet | Natural language processing (Computer science) Artificial intelligence Computer programs Traitement automatique des langues naturelles Intelligence artificielle ; Logiciels Artificial intelligence ; Computer programs |
| work_keys_str_mv | AT stadlerchristian threelessonsfromchattingaboutstrategywithchatgptwhengenerativeaiscapacityforstrategycreationisputtothetestitrevealswhereitsstrengthslieandwherehumansstillhavetheedge AT reevesmartin threelessonsfromchattingaboutstrategywithchatgptwhengenerativeaiscapacityforstrategycreationisputtothetestitrevealswhereitsstrengthslieandwherehumansstillhavetheedge |