Artificial intelligence (AI) and machine learning (ML) are the two essential technologies that have experienced rapid growth in the past few years. Not just limited to automation of activities, but it is also capable of empowering businesses to innovate, improve and grow. AI has the potential to transform businesses by allowing them to make better decisions.
[box type=”info” align=”” class=”” width=””]Building an AI ML strategy is a great way for businesses to embrace AI and ML and take advantage of their benefits. Innovation is another important aspect of having an AI and ML strategy. [/box]
Having an AI and ML strategy will help you innovate, which will in turn provide you with a competitive advantage.
How businesses boost operations by using AI-ML solutions
By leveraging the features of AI, businesses can greatly improve different operations that they conduct as part of their business process.
Highly personalized marketing: Media conglomerates use AI capabilities for personalized recommendations on their platform. The AI is able to play the exact clip from the recommended content to maximise the consumer’s time spent on the platform. This means that while the same video may be recommended to a group of viewers, the clips shown would be based on each individual’s viewing habits.
Social media interactions and engagements: With AI-ML capabilities, chatbots can help flag instances when a particular brand is mentioned on social media via notifications. This allows businesses to interact and increase meaningful engagement, pushing personalized promotions, loyalty programs, and new customer acquisition.
Drawing actionable insights: AI-ML capabilities help retail businesses to gain meaningful insights by analyzing online reviews. Instead of simply using a weighted average of 5-star and 1-star reviews, with AI-ML capabilities, businesses can determine the sentiment within the reviews, factors that push toward favor for the product or against and identify patterns that can help improve their products.
Predictive capabilities: For example, a leading healthcare institute developed a predictive dashboard on cloud to help improve COVID19 public forecasts in the US. The dashboard gave first responders and healthcare organizations the best possible information to prepare for what lay ahead. The solution was then scaled to several other countries.
Concerns, risks, and ethical conundrums around using an AI/ML strategy
Data privacy and anonymity: Unlike traditional programs, AI/ML cannot use dummy data and instead requires valid data for the algorithm to work. Countering attacks on data and privacy with solutions such as differential privacy are then helpful to protect data.
Protection and security: Much of the security practices used in traditional systems can help in securing an AI/ML model. Practices such as data governance, access control and other basic security principles can help in ensuring a secure and safe AI/ML model, capable of warding off foreign manipulations.
Some real-world use cases and implementation
- A leading media organization required its subtitle texts to be translated from Arabic to English. With help of Auto ML, Niveus Solutions ran the Arabic texts through the translation program to identify a base level of accuracy. A language expert verified and addressed issues regarding interpretations, grammar, and the like. A glossary for Arabic words and their equivalent interpretation in English was used by the auto ML program to translate. A custom ML program then provided an accuracy of 95% and more.
- A home furnishing organization used the recommendation AI program and increased the number of relevant recommendations displayed on their website by 400%, creating a tangible improvement in conversion rates and average order value. Customers were able to find their preferred choices, complimentary products and more, based on recommendations and personal tastes, with as few clicks as possible.