Today, it is a reality that Artificial Intelligence (AI) – Cognitive Technologies can successfully emulate and supplement the power and processing of the human brain. This is a significant and valuable development for both the private and public sectors which have new and innovative opportunities to leverage and exploit the enormous amount of data pulsing through their organizations, and connected markets, governmental agencies, and individuals. Traditional computer technology has proven that it is not capable to effectively and efficiently extracting, evaluating, repurposing, and monetizing the massive amounts of structured and unstructured data.
AI is now transforming business and government in ways we’ve not seen since the Industrial Revolution; fundamentally reinventing how organization, governmental entities and markets, operate, interact, compete and prosper. When implemented holistically, these AI – cognitive technologies will meaningfully improve productivity and lower operating costs, unlocking more creative knowledge worker type jobs and creating new growth opportunities. In summary, AI is positioned to disrupt our world in a positive manner!
McKinsey Global Institute in 2017 reported that rapid advances in automation and artificial intelligence will have a significant impact on the way we work and workplace productivity. To successfully create value in this emerging market, organizations are experimenting with different strategies, technologies, and opportunities, all of which require large financial and human resource investments.
In this article the terms Artificial Intelligence (AI) and Cognitive Technologies are used interchangeably. Both reference technologies with capability to perform and/or augment tasks, improve decision-making, and create interactions that have traditionally required substantial human intelligence, such as planning, reasoning from partial or uncertain information, and learning. The dawn of the cognitive era creates newer, more creative, and increased opportunities for organizations to generate value from their massive mountains data, in tandem with analytics advances.
Artificial Intelligence (AI), to most people, still sounds more like something from a Star Wars movie, however it is increasingly real, and critical to the success of digital transformation environment. The demystification AI starts with the definition as outlined below.
Artificial intelligence (AI, also machine intelligence, MI) is intelligence generated by machines, versus the natural intelligence (NI) displayed by humans. Further, AI is a collection of advanced technologies that allows machines to sense, comprehend, act and learn. Colloquially, the term artificial intelligence is when a machine mimics cognitive functions that humans associate with other human minds, such as learning and problem solving.
Cognitive Technologies are products of the field of AI that perform tasks that only humans used to be able to do as follows:
- Computer Vision
- Deep Learning
- Intelligent Bots
- Machine Learning
- Natural Language Processing
- Physical Robots
- Robotic Process Automation (RPA)
- Rules-based Systems
- Speech Recognition
Examples: Best-in-Class AI – Cognitive Technologies Use
Examples of successful AI solution use within the private and public-sector community include:
Financial Industry: use automated fraud detection and machine learning to identify human and transactional behavior patterns; use speech recognition to automate customer service telephone communications and interactions.
Healthcare Industry: use systematized speech recognition to transcribe physician patient notes and official documents; use computer vision to automate mammograms and other body condition image analysis; automate reading and comprehending huge amount of medical literature; automate hypothesis generation techniques for diagnosis, and machine learning.
High-Technology Industry: use automated computer vision and machine learning to enhance computer and system products and create new products and services.
Life Sciences Industry: use systematize machine learning systems to predict biological data and compound activity cause-and-effect relationships to identify new advanced or repurposed pharmaceuticals.
Media and Entertainment Industry: use automated data analytics and natural language generation to automate create media and supporting narrative material.
Public Sector: use cognitive technologies to support governmental regulations, rules, and processes for surveillance, compliance and fraud detection.
Retail Industry: use automated machine learning to discover attractive cross-sell and up-sell offers and effective incentive-based promotions.