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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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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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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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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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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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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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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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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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316 reads

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