Bridging the chasm between domain and data expertise is key for AI success

In this blog, learn why bridging the divide between industrial domain and data expertise is critical for AI success. Read the blog at
2 min
Bridging the chasm between domain and data expertise is key for AI success

As the number of AI deployments grow across industrial firms, the lack of collaboration between the domain experts and data scientists team is emerging as a key reason for the high failure rate of AI projects. 

The organizations which are able to bridge this gap are better placed to leverage the potential of AI to enhance the production and operational efficiencies of their organization. 

The success of Fortune 500 food manufacturer is a case in point. The organization used Canvass AI's no-code platform to cut energy costs by $330,000 and reduce carbon emissions by as much as 9 million pounds. A critical factor behind the firm's success is that it addressed the people issue head-on by including members from both its operations and digital teams in the AI team. 

A recent webinar, 'Industry 4.0: Where the battle between domain and data expertise is won' traces the firm's AI journey. Moderated by Renee Bassett, Chief Editor,, the webinar is presented by our experts, Marc Gallant, VP Partnerships, Canvass and Forogh Askari, AI Industry Lead, Canvass. 

The food manufacturer is leading digital transformation by using AI to bring together domain expertise and data. A key reason behind the project's success is that Canvass AI's platform empowered the industrial engineers to prepare data for AI, build and train AI models, and deploy them in their day-to-day operations.

The Canvass solution puts AI capabilities in the hands of industrial engineers and eliminates the need to employ data scientists or hire consultants. By giving industrial engineers the power of AI, Canvass AI helps them solve real challenges, stay competitive and grow.

Watch the on-demand webinar here to learn how a no-code AI platform can play a crucial role in bringing together the domain and data experts.

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