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230704 ||| eng |
| 050 |
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4 |
|a TA347.A78
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| 100 |
1 |
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|a Joshi, Amit
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| 245 |
0 |
0 |
|a Moving beyond islands of experimentation to AI everywhere
|b the agile teams needed to kick-start artificial intelligence must give way to companywide structures in order to scale the technology across a business
|c Amit Joshi, Ivy Buche, Paredes Sadler
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| 250 |
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|a [First edition]
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| 260 |
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|a [Place of publication not identified]
|b MIT Sloan Management Review
|c 2023
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| 300 |
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|a 10 pages
|b illustrations
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| 653 |
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|a Artificial intelligence / Industrial applications / fast
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| 653 |
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|a Intelligence artificielle / Applications industrielles
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| 653 |
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|a Artificial intelligence / Industrial applications
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| 700 |
1 |
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|a Buche, Ivy
|e author
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| 700 |
1 |
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|a Sadler, Paredes
|e author
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 500 |
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|a Reprint #64425
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| 856 |
4 |
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|u https://learning.oreilly.com/library/view/~/53863MIT64425/?ar
|x Verlag
|3 Volltext
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|a 006.3
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| 520 |
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|a Artificial intelligence typically takes root in an organization in isolated experiments or projects, but formal structures are needed to scale the technology across the organization and deliver on its potential. The authors identify three typical structural phases of AI implementation: islands of experimentation, centers of excellence, and federations of expertise. They identify the strengths and limitations of each and describe how companies have managed transitions to new structures that better enable AI initiatives
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