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AMPLYFI’s AI-ness Index Part Two: Sector Frontrunners

By July 20, 2021September 6th, 2023No Comments

AMPLYFI has developed a global index that uses machine learning to quantify the extent to which an organisation is involved in artificial intelligence. It provides a means for a company’s association with AI to be rated on a consistent and objective basis.

In Part One of the AIness Index, we introduced the index and examined a representative sample of companies identified and assessed within the index. Here, we present results for a selection of companies that performed highest within specific subsets of AI, namely autonomous vehicles, speech recognition, and machine learning. 

Download for insights into:

  • The technology behind AMPLYFI’s Index for measuring company involvement in AI.
  • The frontrunners and rankings for companies in fast-moving AI fields of autonomous vehicles, speech recognition and machine learning.
  • Analysis of the rankings and how the industry is predicted to unfold going forward.

About the index

A benchmark for pinpointing cutting edge innovation capabilities, whether as a developer or user of AI, has until now been hard to objectively quantify. To overcome this, AMPLYFI has developed an index that uses supervised machine learning to quantify the extent to which an organisation is involved in or associated with AI (either as a developer or incorporating it into their technology stacks or service offerings). Called the ‘AIness Index’, its purpose is to provide investors and other stakeholders with an unbiased and statistically quantified view of companies and the strength of their associations with AI. With the world currently generating an estimated minimum of 2.5 quintillion bytes of data each day, the extent to which companies harness AI to create value from data is increasingly an indicator to their likely success and competitiveness.

Unlike the vast majority of market indexes that require large teams of researchers to collate and process documents, AMPLYFI’s AIness Index uses machine learning to automatically quantify organisations’ credentials in this space. A suite of AI algorithms including natural language processing (NLP), pattern recognition, topic modelling, and entity identification, spots connections between companies and activity related to AI.

Our machine-driven analysis provides a comprehensive, objective, and unique view of the AI landscape as it stands today and as it unfolds going forward. The second of a two-part series, Part Two of the index explores the rankings for the companies that performed highest within specific subsets of AI.