How Enterprises Are Bridging The Gap Between Consumer &#038; Business AI
The Business AI sector is very different from the consumer one. In the last five years, AI has finally been proliferating the enterprise world, which is very different to work with than your classic B2C scenario. B2C is much more reactive — you build something and you throw it at a million users and see what happens. And if it doesn’t work, you can pull it back. With B2B, you cannot do it because you have a limited number of customers and each one of them is paying you. That’s why AI vendors need to do the research in advance and make something enterprise clients want. Instead of having a large number of users out there that all contribute a little bit of data to you, business AI vendors may have very few users that contribute a lot of very valuable, very private data. For AI companies, wherever there is an area of human activity that generates activity data, there is a ripe opportunity be it B2B or B2B, such as collecting data for shipping containers, data from a wind farm, recording emails from a salesperson, recording location metrics of drivers, etc. Lesson From B2C: The Bundling Of Business AI Services There are cycles of bundling and unbundling playing out here already in the latest wave of machine learning applications. The use cases are getting increasingly precise and tailored to the end-user. As a consequence, we have systems which are now richer and deliver more promises to the user and then help them do their job and more and more ways. We see this happening in B2C where the bundling of services is happening as companies figure out the right workflow. B2C companies are designing their products to be simpler. The UX is designed such that there’s a level of intent that you can observe from the user. Take Uber as an example of bundling of services. Started as a cab aggregator, the platform has extended to other businesses like food delivery, freight and other things from the same app. Once the company finds an optimal user interface that allows for suggesting best next action, then it just makes sense to bundle in more and more functionality and take over more and more of the attention span of the users. Similar to B2C, the next wave of business AI software makes workers lives easier through increasing orchestration of the knowledge worker labour force. Instead of you pulling data and looking for it in a bunch of excel reports, salesforce reports or websites, it’s actually being pushed in prepackaged personalised actionable insights. Here, everything workers need to know to complete an action is right there, pushed through one single channel through which workers are most likely to engage.
The Business AI sector is very different from the consumer one. In the last five years, AI has finally been proliferating the enterprise world, which is very different to work with than your classic B2C scenario. B2C is much more reactive — you build something and you throw it at a million users and see […]
Similar to B2C, the next wave of Business AI software makes workers lives easier through increasing orchestration of the knowledge worker labour force.
["enterprise ai"]
["machine learning", "programming_languages:R", "AI", "ViT", "enterprise ai", "R"]
["AI", "machine learning", "R", "ViT", "programming_languages:R"]
Vishal Chawla is a senior tech journalist at Analytics India Magazine and writes about AI, data analytics, cybersecurity, cloud computing, and blockchain. Vishal also hosts AIM's video podcast called Simulated Reality- featuring tech leaders, AI experts, and innovative startups of India.