Artificial Intelligence for Business: A Roadmap for Getting Started with AI

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John Wiley & Sons, Apr 21, 2020 - Business & Economics - 240 pages

Artificial Intelligence for Business: A Roadmap for Getting Started with AI will provide the reader with an easy to understand roadmap for how to take an organization through the adoption of AI technology. It will first help with the identification of which business problems and opportunities are right for AI and how to prioritize them to maximize the likelihood of success. Specific methodologies are introduced to help with finding critical training data within an organization and how to fill data gaps if they exist. With data in hand, a scoped prototype can be built to limit risk and provide tangible value to the organization as a whole to justify further investment. Finally, a production level AI system can be developed with best practices to ensure quality with not only the application code, but also the AI models. Finally, with this particular AI adoption journey at an end, the authors will show that there is additional value to be gained by iterating on this AI adoption lifecycle and improving other parts of the organization.

 

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Contents

Ideation
13
Becoming an InnovationFocused Organization
23
Information Flows
29
Ranking Categorizing and Classifying
35
AI Limitations
41
Defining the Project
47
4
71
5
97
Steven Flores
187
APPENDIX B Roadmap Action Checklists
191
Data Curation and Governance
192
Production
193
Pitfalls to Avoid
195
Defining the Project
196
Data Curation and Governance
199
Prototyping
203

6
117
Thriving with an AI Lifecycle
139
10
144
Conclusion
163
23
169
25
179
Rahul Akolkar
183
Production
204
Thriving with an AI Lifecycle
206
Index
209
27
211
34
220
Copyright

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About the author (2020)

JEFFREY L. COVEYDUC is Vice President and Master Inventor at IBM. His diverse background consists of positions that encompass the creation of innovative, technologically advanced global AI solutions and client adoption.

JASON L. ANDERSON is a Partner and CTO with the data consultancy, Comp Three, where he established a new AI line of business. He is also a former IBM Cognitive Architect and Master Inventor. He received both BS and MS degrees in Computer Science from California Polytechnic State University, SLO.

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