21 Aug
2018

Five Pillars of a Successful AI-based Transformation

The innovations resulting from the arrival of artificial intelligence (AI) are within reach for many companies. When it comes to using AI and IIoT, consider the five pillars to make a successful AI-based transition and adopt leaner and more agile work practices.

Artificial Intelligence
Industry 4.0
Lean Manufacturing
IIoT
Les cinq piliers d'une transformation réussie basée sur l'IA

The innovations resulting from the arrival of artificial intelligence (AI) are within reach for many companies. When it comes to using AI and the Industrial Internet of Things (IIoT,) Senior Vice President, Global Solutions & Innovation at Hitachi Consulting Philip Townsend says these things need to “work together securely at commercial or industrial scale to create business value.” In a report he wrote with Vice President Organization Effectiveness at Hitachi Consulting Susan Anderson and Hitachi Fellow Dr. Kazuo Yano, they discuss the “Five pillars of a successful AI-based transformation,” and more with a view to helping your manufacturing plant more lean and agile with AI and IIoT.

Here are the five pillars of a successful AI-based transformation according to Townsend, Anderson, and Yano.  

 

  1. Demonstrate effective digital leadership: Leaders wanting to create new value streams from AI need to be collaborative with  groups like R&D and IT, but also recognize that the digital vision ultimately cascades from the  top down through the rest of the organization.
     
  2. Enhance customer engagement: In practical terms, this means putting the customer at the center of the AI vision and building the capabilities required to move ever closer to customers, end-users, suppliers  and investors.
     
  3. Improve the operational environment. This pillar is foundational because AI and other digital capabilities enable organizations  to act faster, smarter and more cohesively, with unprecedented levels of clarity and precision.
     
  4. Evolve the core architecture: An essential component of digital transformation using AI is evolving the  core architecture. Streamlined, secure and robust IT drives the digital enterprise, creating a more  responsive digital core that provides intuitive access to business data and apps that enable greater efficiency and effectiveness.  

    Source + read the complete report.

 

Want to learn more?
Download the ebook
Related blog articles

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
28
Juin 2023

Investing in Industry 4.0: It’s now more important than ever for food & beverage manufacturers of all sizes

English
20
Fév 2018

Worximity fera partie de la super grappe Scale AI

French
20
Fév 2018

Worximity will be part of the Supercluster Scale AI

English

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
28
Juin 2023

Investir dans l'industrie 4.0 : c'est désormais plus important que jamais pour les manufacturiers d’agroalimentaire et boissons de toutes tailles

La clé est d'adopter l'innovation pour naviguer dans des conditions en constante évolution et rester à l'écoute des demandes des consommateurs, tout en maximisant la rentabilité.

French
28
Juin 2023

Investing in Industry 4.0: It’s now more important than ever for food & beverage manufacturers of all sizes

Faced with challenges that include labor and raw material shortages, tightened regulations ,and skyrocketing costs, companies like you are struggling to produce and price products to meet the demands of increasingly cost-conscious consumers and anxious stakeholders alike.

English
27
Juin 2023

Au-delà des chiffres : maximiser le retour sur investissement dans le secteur manufacturier grâce à l'analyse de données

L'intelligence des données provient de chiffres bruts. Ces informations doivent être analysées et traduites en actions ayant un impact sur l'entreprise. Mais avec des données qui s'accumulent plus vite qu'elles ne peuvent être transformées en analyses de données manufacturières, les entreprises ratent des opportunités.

French