Artificial Intelligence (AI): Where do we start in 2021

In 1955, Stanford Professor John McCarthy coined the term Artificial Intelligence, while there is no universally accepted definition for AI, he called it “Programs with common sense”.

In 1959, he also invented the programming language for AI known as the LISP acronym for list processing, designed specifically for manipulating data strings. There has been a great development in these six decades with AI initiatives on all forms of data available, whether it is natural language processing, speech recognition, and computer vision.

How Artificial Intelligence could change our lives?

It won’t be less of a prophecy to say that Artificial Intelligence will soon change our daily lives. Some of us have already adopted a digital culture or going through a digital transformation which is here before time, because of an ongoing pandemic. The organizations are capturing maximum value from this technological wave setting us up for the changed era post-pandemic.

Can Artificial Intelligence Transform Business(es)?

The availability of AI in augmenting human capabilities to read data, recognize patterns, anticipating events, increasing situational awareness for informed decisions has forced businesses, small organizations, and large enterprises to adopt AI.

The best-fit solutions today not only solve business problems but also transforms culture, thriving to provide all good reasons to organizations to collaborate, whether it is growth, savings, or lower risks. 

There are various solutions based upon NLP and computer vision that helps our customers enhance current products, optimize operations, and make better decisions.

Smart deployments over cloud make it accessible from anywhere without even spending upon space, infrastructure and are available over low bandwidth. 

The solutions available today are transforming organizations & Industries at an equal pace, the ongoing wave of innovation has enabled new processes capturing value for various enterprises and becoming a source of revenue or savings for another. 

We are at a junction in the AI journey for the first time where computation power is leading us to various possibilities in terms of different types of AI learning.

Supervised learning has made it possible to validate the input as well as the output data for the machines. Making a model learn on both improves the accuracy enabling a better result.

Artificial Intelligence in Security & Surveillance

There are primarily three top reasons driving organizations on the journey of adopting AI

  • Enhancing current products
  • Optimizing operations
  • Taking informed decisions

The solution based on these three buying logics is very few.

Integrating seamlessly with legacy recorders, and ONVIF compliant cameras enable you to fetch RTSP streams to run various scenarios like Face Recognition, Object Detection e.g., Weapon, Helmet, Mask, Backpack and Sunglasses, Automatic Number Plate Recognition, Speed, and many more such scenarios are available off the shelf.

You can set various KPIs based on these detections to run specific SOP collaborating with all the actors from various agencies in real-time. AI also helps in correlating various alarm inputs for accurate situational awareness enabling you to make an informed decision, saving on time and resources. 

Such optimized operations set the organizations for growth and lower risks at the same time. This is not just a performance matrix but a cultural change in doing things, pushing us for a complete digital transformation.

Artificial Intelligence and Data Analytics 

Ocean of data available for unsupervised learning for AI yields patterns and can give a predictive analysis for proactive action. Correlating previous outputs, finding patterns can help organizations with Risk Modelling based upon regulatory compliance, workforce, physical security, and organizational reputation.

Correlating distant data sets, reading values, running numerous algorithms is all possible today, giving results and improvements all at the same time. This also increases efficiency, effectiveness, making employees more productive as they discover new insights. 

These new use cases can significantly change the way an organization operates by creating new business models, reducing headcounts, or lowering costs. It will not be out of context to quote that it ultimately enhances customer relationships and create new products and services. 

Adoption of Artificial Intelligence across Industries 

There has been tremendous growth in the adoption of Artificial Intelligence in understanding customer behavior in BFSI, Retail, and Transportation. 

For example, A Smart Bank, today wants to know its customer service metrics. It would simply analyze:

  • Face for recognition
  • Customer expression
  • Speech to analyze discomfort or anger                                    
  • Gestures for any duress conditions                                                            

In the Retail Sector, it can be instrumental in defining promotion, peak times, and overall customer experience.

Smart City projects can leverage AI on traffic data to give trends, recommend routes, avoid accidents, and can also help to decrease carbon footprint.

Artificial Intelligence
AI Use Case
Why should you invest in Artificial Intelligence? The way forward…….

AI is quite compelling for organizations to invest for exponential improvement in processes. The transformative benefits of AI can be overwhelming, which usually push you to think about the journey of digital transformation and leave you clueless about where to start. 

The way to go for this in my opinion would be smaller, incremental changes to the operating model step by step. It will be a mistake if we look at AI as an independent technology, as it is so intertwined with other technologies to grow to its full potential, like cloud computing.

The convergence of technology can build resilience, its adoption can make you agile to overcome complexity, uncertainties, and the risk of running behind to establish a new normal