Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of the Economic Times – ET Edge Insights, its management, or its members

27nov

Understand how you can scale the AI ladder and accelerate your enterprise’s current ML adoption.

Machine Learning (ML) is one of the most powerful technologies in a modern enterprise. The hype cycle for terms like Machine Learning or Artificial Intelligence (AI) continue to climb and grandiose outcomes are promised for the future under the garb of these terms.

According to IDC, spending on AI and ML will grow from $12 billion in 2017 to $ 57.6 billion by 2021. Of course, a host of forces would be driving the ML market as it powers the algorithm or program to run efficiently and accurately, which in turn, helps in making better decisions. As enterprises start valuing data and unlock its true potential, the time would be ripe to join the machine learning club and scale the AI ladder.

Some of the leading tech leaders are realizing the value of ML and AI and deploying these technologies into their future-generation products in order to improve customer experience and channels’ efficiency.

As per a study by Deloitte, 60% of organisations are at various stages of machine learning adoption, and about 45% believe that the technology has triggered extensive data analysis and insights. Organisations are therefore turning their data science initiatives from simply being research endeavours to serving as an integral part of the business processes.

This Economic Times webinar on ‘Accelerate Your Enterprise’s Machine Learning Adoption’ will help you understand how you can scale the AI ladder and accelerate your enterprise’s current ML adoption by laying down an effective information architecture platform.

Key Takeaways

  • Grey areas in ML adoption
  • Uncover true data potential with ML & AI
  • How to leverage ML/AI for scalable business, higher profit

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of the Economic Times – ET Edge Insights, its management, or its members

Leave a Comment

Your email address will not be published.