AI in Business: Guide to Transforming Your Company [2020 Update]

You probably read tens of articles on AI in business indicating numerous AI applications or exotic-sounding algorithms like deep learning or support vector machines. But you don’t know what you can do with AI for your own business today. We have a solution:

First, AI is a tool and writing in general about AI in business is like writing about computers in business. It helps to be a lot more specific so we will break down AI applications by industry and business function to give you an overview of what AI can achieve. Read more

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2018 AI predictions: Summary of top AI experts’ predictions

Since the beginning of the year, PwC, CEO of pymetrics, Gil Press  from Forbes published predictions on the direction AI will take. We read them all and couldn’t resist adding our predictions and categorizing the predictions:

Mega-trends that will shape AI in 2018

The news cycle is full of AI, research centers being opened, re-organizations, new research findings and tabloids peddling that robots will kill us all tomorrow. Reading a different type of news everyday, it is easy to lose track of what is really happening. What are the major trends? Read more

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Challenges of implementing an AI solution [2020 update]

Deloitte survey identifies top challenges by corporations applying AI in their businesses

Judging from the numbers above which are from Deloitte’s 2017 State of Cognitive survey, it seems that only a tiny minority (6%) of the corporations are having a smooth ride with AI. We found the survey results realistic and combined them with our experience with companies that reached out to us regarding advice on their AI solutions. We think there are 2 classes of issues

Issues with building own AI solutions

Lack of business alignment

Identifying business cases for AI applications requires managers to have a deep understanding of current AI technologies, their limitations and the current processes of their division. As with any nascent field, lack of AI know-how in management is hindering adoption in most cases. Read more

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AI Limitations in 2020: Data hungry, opaque, brittle systems

Though we preach that AI investments can transform businesses, we are also not naive in our beliefs in AI’s current capabilities. Most modern AI systems suffer from common issues highlighted by respectable publications that we will collect here:

Reliance on large volumes of data

Impacts deep learning algorithms. Sadly, even when data is available, it’s likely to suffer from bias.

Research on one shot learning is an attempt to solve this problem.

Reliance on labeled data

Limits supervised learning algorithms to relatively few problems where labeled data is either available or where the solution is so valuable that companies invest in preparing semi-manually labeled data. Read more

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100+ AI Use Cases & Applications in 2020: In-Depth Guide

AI is changing every industry and business function, which results in increased interest in AI, its subdomains, and related fields such as machine learning and data science:

Google Trends showing increased interest in AI, ML and data science
Source: Google Trends

According to a recent Gartner survey, 37% of organizations are still looking to define their AI strategies. To integrate AI into your own business, you need to identify how AI can serve your business, possible use cases of AI in your business. This article gathers the most common use cases covering marketing, sales, customer services, security, data, technology, and other processes: Read more

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