Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...
Full BioNand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...
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Enterprise Artificial Intelligence Could Make Gridsum Holding The Swing Trade Of 2018
- I contend that enterprise artificial intelligence (AI) will be the top investment theme of 2018.
- GSUM believes it is currently the technology market leader in the China enterprise-focused AI space with a global best-of-breed enterprise-AI engine.
- There is a scarcity of legitimate AI companies that are publicly traded. This can lead to scarcity in stock price premiums as in the case of Veritone and Alteryx.
- GSUM would have a share price of $38-70 if it traded at the price to sales multiple of Veritone or Alteryx. It closed yesterday at $12.28.
- This all could make GSUM the swing trade of 2018.
Broadly speaking, consumer AI often leverages the ubiquitous consumer Internet ecosystems across e-commerce, social, mobile, entertainment and others and focuses to quickly solve or facilitate relatively simple (from a mathematical standpoint) but often time-consuming, "painful" or distracting consumer challenges. Consumer AI is incredibly broad in scope, having the potential to revolutionize and facilitate the way people live and, within the next 10 years, will likely touch the lives of most of the people on the planet.
Enterprise AI is different in focus, structure, development, management, application and goals. It requires a very different and focused "organizational DNA" which is particularly rare in China (and elsewhere in Asia). It is focused on creating immediate and quantifiable value for companies with an immediate KPI impact and evolving and increasing that value-add over time.
Enterprise AI hence requires deep domain expertise and knowledge of the target industry and its ecosystem. This allows Gridsum to understand the challenges and opportunities where AI technologies can be effectively applied to delivering immediate and quantifiable value to an enterprise customer whether it is improving efficiency, reducing cost, or allocating marketing budget for optimized ROI. These are often industry-specific drivers and dynamics, typically requiring more focus and depth in a narrower area than consumer AI. To accomplish this, enterprise AI tends to heavily leverage supervised learning techniques to infuse human expertise into the resulting intelligent solutions.
According to the survey, 73% of respondents agreed or strongly agreed that their AI deployments have already transformed the way they do business, and 90% of c-level executives reported measurable benefits from AI within their organisation.
AI deployments are no longer imminent but are becoming pervasive, as 86% of organizations surveyed have middle- or late-stage AI deployments and view AI as a major facilitator of future business operations.
80% who said they've seen at least some measurable benefits from AI agreed or strongly agreed that their organization had a defined strategy for deployment, while 53% of all respondents said that their industry has already experienced disruption due to artificial intelligence technologies.
As you can see from the chart below, revenues from enterprise AI applications market worldwide are forecasted to go from $360 million in 2016 to $31 billion in 2025.
