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AI will transform every dimension of business

AI will transform every dimension of business

  • AI remains experimental and iterative, but still has applications in flexible systems.
  • Train business units to implement AI solutions horizontally and vertically in their enterprises.
  • Employees are the heart of the AI organization.
  • AI development teams must be agile and independent, yet maintain strong connections with the business.
  • AI is only as good as the data that firms use to train it
  • Upskilling employees with AI training across departments will reinforce its relevance.

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612 reads

digital transformation

The digital transformation started decades ago, when companies used software to create “systems of record.” Keeping records digitally extended into “systems of engagement,” expanding into customer relations

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490 reads

AI capabilities fall into three categories:

AI capabilities fall into three categories:

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

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542 reads

DAVID CARMONA

“AI opens up new ways of interacting that can make our applications more engaging or accessible to more users.”

DAVID CARMONA

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438 reads

Create inventories

Create inventories

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.

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378 reads

participate in the AI revolution.

  • 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.

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309 reads

The MLOps Loop demonstrates this integration and dissemination p

The MLOps Loop demonstrates this integration and dissemination p

  • 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.

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289 reads

DAVID CARNONA

“No matter what scenario you are targeting, chances are that without relevant data, you won’t be successful in delivering an AI solution.”

DAVID CARNONA

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322 reads

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