You, the enterprise and AI - Part 1: The introduction
Oladimeji Kazeem
Certified AI Transformation Leader (CAITL) | Senior Data Architect | AI Scientist | Data Scientist | ML Engineer
The world has experienced major breakthroughs, but the best is yet to come. The beautiful ones are not born yet. This explains why we find ourselves, our organizations, our nations, and humans passing through various developmental phases. Technological revolutions started way back in 1784 when water and steam were used to power production activities. This was marked the 1st industrial revolution. The quest for more efficiency brought about need to apply division of labour and the need to and improve production of goods and services by the used of electricity which characterised the second revolution in 1870. In 1969, further achievements were made by the application of electronics and information technology to automate production processes. The world is now trying to sustain the fourth industrial revolution (4IR or 4.0) which was initiated at the onset ?of 21st century. Human autonomy is now the order of the day, from mechanization and mass production to fully automated systems. This has paved ways for the development and applications of disruptive technologies such as cloud computing systems, robotics, machine learning, internet of things (IoT), virtual reality and artificial intelligence.
Furthermore, whatever reason(s) must have been adduced to the various industrial revolution changes it should be noted that the world is and will continue to evolve given that nothing can be held constant forever. Industrial revolution,?irrespective of its dimension(s), comes at a cost to everyone, our organizations, and the entire society. This cost can be dimensioned based the apparent or perceived negative effects, which include but not limited to obnoxious living conditions, poor nutrition, stressful lifestyle without satisfaction, unpleasant workplaces, child labour, discrimination against women and all sorts of environmental harm including global warming.
The dimensions that characterised the 4th industrial revolution seem to be the most challenging as they tend imitate humans. This phase in the evolution of the world, produces data irrespective of whether usable(structured data) or directly unusable(semi-structured?or unstructured data). ?The data could be studied for insightful information that could assist in decision making and associated use cases. The process involved in uncovering these insights is simply known as data analysis. In some cases, the data involved is multidimensional in nature, as such would require a more advanced multidisciplinary approach called data science. The latter approach combines principles and practices from the fields of mathematics, statistics, artificial intelligence and computer engineering to analyse large amount of data. Data science is has different variants which include decision science as the maybe in some organisations.
Artificial intelligence is an aspect of science that studies the theory and development of computer systems towards executing task that involves human intelligence which includes image recognition, speech recognition, translation between languages as well as decision making.?
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How does Artificial intelligence(AI) works?
The mode of operation of an AI is heavily dependent on data availability.?It ingest a large amount of labelled data within the sphere of interest, analyses the data for correlations and related patterns. These patterns, used to understanding the perceived operations of the system that generated the data is also required for predicting the future states. It takes some effort to ensure that the AI system is properly trained. A robot is an AI product or tool which emanate from artificial intelligence?activities. A chatbot is a robot which learn to produce results similar to human behaviour based on the nature of data that must have been used to train it. If fed with images, it learns to identify and describe images among several collections. If fed with text, it can engage in exchanges just as a human being would do.
There are numerous applications of AI depending on the areas of focus, however some dimensions of application are as enumerated as follows:
Finance: AI tools provide more accurate assessment than traditional tools of methods for credit score scan, they are also applied in the detection and prevention of fraudulent transactions on customers’ accounts. All other finance tasks such as credit decisions, risk management, financial advisory services, trading, and related tasks which were being handled manually are being automated using AI.
Manufacturing: ?Operation involved in the production of goods now run faster and more efficiently. Several products are packaged and delivered by robots at high precisions. Breakdown prevalence is reduced where AI is applied for preventive maintenance of manufacturing hardware. Machine learning models are now being used for product designs to surpass customers’ expectations. Other applications include raw material forecasting, inventory management, and hedge analytics.
Retail: While shopping online the system can study the buying patterns of customers along with the items purchased. Robots use the associated data to suggest to possible items to purchased based on several factors. Store managers can now predict the possible items to restock given that various items are out of stock and unavailability of enough resources for restock.
Healthcare: Some applications include possible errors in the diagnosing a patient for an ailment has been reduced by the used of Natural Language Processing (NLP), it now much more convenient for doctors to narrow down all relevant detail from to a patient. Doctors can now focus on more urgent and dire cases because of the application of AI to the flow of primary healthcare. Robots have now been involved in surgical operations, on patients.
Education & Scientific Research: The current pervasiveness of personalized learning couple with smart content creation has made educational activities and research to be more interesting than ever. Skill gaps closure and customised data – based feedback has now made teaching or tutoring to more student – oriented than it used to be. Research and grading are being conducted with great attention to plagiarism and little reasons to flip through lot of physical books.
Pharmaceutical: Identification and diagnosis of new diseases are being responded to using AI, by pharmaceutical organizations. Other areas of application of AI in pharmaceutical activities are clinical trials, predictive analytics, drug development and digital therapeutics.
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Hospitality: Predictive analytics and dynamic pricing is used in the appropriate determination of the price of hotel rooms through the online channels. This explains why these prices are never same all the time. Hotel reviews are also made actionable as well as improved booking processes, thanks to AI.
Who should consider AI?
The proliferation of AI tools and practices were introduced by need for improvement, as such both individual and enterprise require one form of improvement or the other. A school of thought believes that AI has come to take away those tasks being carried out human and the attendant possibility of joblessness. Another posit that it is an opportunity for human being to do those things that add value to the enterprise while the mundane tasks should be left for AI.
The hard truth is that investors want to constantly increase their returns on investment, as such would embark on any initiative such as AI that would allow them to realise their goals. They do this by ways of process automation even if it implies downsizing or rightsizing the labour force. To be relevant or maintain your relevance in the 21st century and beyond, as professional, or skilled labour you now have an opportunity to upskill.
?This is the first part of our series: You, the enterprise and AI. The upcoming series have been planned as follows:
You, the enterprise, and AI – Part 2: How is AI related to Data Science?
You, the enterprise, and AI – Part 3: What is it for you and the enterprise?
You, the enterprise, and AI – Part 4: The dark side of AI?
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Photo by Andrea De Santis and Possessed Photography on Unsplash
?Further Reading
Founder & CEO at DFA | Co-Founder & Member Board of Directors | Exit Co-Founder | Successful Exit Strategist | Entrepreneur & Investor
1 年Thank you Oladimeji Kazeem.