The AI Organization

• Perception – Vision, Audio, Speech and Natural Language.
• Cognition -Regression, Classification, Recommendation, Planning, Optimization and Pattern Recognition.
• Learning – Supervised, Unsupervised and Reinforcement Learning.

Create inventories and categorize processes under a framework that includes the following zones:

• Incubation – Evaluating opportunities to expand business using technology. This is long term and therefore more agile.
• Transformation – Choosing opportunities to develop and scale that will push the organization beyond “business as usual” practices.
• Performance – Generating revenues that rely on ROI and investment priorities.
• Productivity – Optimizing effectiveness while reducing inefficiencies.

• Democratization of knowledge – Currently, data are disseminated in complex ways across organizations, and are inaccessible to most employees. They need knowledge that is structured (graphs), semantic (clearly defined attributes) and consolidated.
• Democratization of AI consumption – Build AI into existing programs, such as Excel, to augment employee workflow.

Democratization of AI creation – Using “transfer learning,” a nontechnical user can customize a model that a data scientist trains.

• Definition – Business stakeholders working closely with developers to determine business needs, experiment with models and acquire data.
• Development – Implementing the process (preparing data, modeling and training). Solutions are incrementally integrated and monitored.
• Operations – Managing the system in production and operations is part of the continuous deployment in its various iterations, and provides feedback via telemetry.