AI in aid of knowledge economy

The advent of Artificial Intelligence (AI) has boosted the cause of business in many ways. It has speeded up the process of strategy formulation that derived new strength from a rapid analysis of comprehensive and relevant data relating to the past and the present.

It has also enabled businesses to deal with the new level of competitiveness that exists in today’s world, on the basis of an in-depth study of other players in the field as well as of the intricacies of the business environment.

Finally, AI is setting new benchmarks in human resource management in the matter of reconstituting teams to focus on creating new products and services and ensuring timelines of delivery.

In the Age of Information brought in by Information Technology, knowledge-based decision-making became the first priority of all business enterprises and towards that objective, arrangements were made to collate and analyse a given set of parameters for defining the future vision of the business entity to be achieved within a timeframe.

The scope of Business Intelligence has been infinitely enlarged by AI which is a tool for quickly examining an unprecedented amount of raw data and collated facts, analysing all risk factors and opportunities and producing a set of reliable-looking predictions. The AI-assisted analytics covers a volume of data that was humanly impossible to handle in one go. This has pushed decision-making to a level of near perfection in a competitive environment.

Analysis of vast datasets through the application of AI can unearth patterns and trends that throw light on the modus operandi of a rival that was not visible to the human eye and which could be put to good use in a competitive setting. Even while leveraging historical data, AI can read areas of success of a competitor and determine the scope for improvement there far more accurately thus creating a competitive advantage. The more comprehensive the data, the better the outcome of the AI application.

It is possible to roll out new GenAI-based products and services to bring more value to investors and customers. AI-aided skills are extensively used now for profile writing, creating engaging headlines and understanding natural language for putting across the work being done by the business enterprise.

As already mentioned, AI is proving indispensable for predictive analytics. Simulating market conditions and their probable outcomes accrued through advance scenario planning and risk assessment, is becoming a trendsetter.

There are limited programmes for GenAI skills in the university curricula. Even at the leadership level specific GenAI programmes have to be devised to enhance the trickle-down effect in creating motivation and ambition across the hierarchies. These are also needed for strategy formulation and possible policy amendments that could be required for better implementation. Today, an understanding of Learning & Development (L&D) and Large Language Models (LLMs) and their importance in business is needed at the leadership level itself.

The main point of understanding and acceptance by the leadership is that AI’s first impact on business was to enable the enterprise to reduce cost and increase the efficiency of its operations so that there was better ROI resulting from the value-add created by AI.

Decision-making is one of the most important areas depending a great deal on AI because the latter can scrutinise large databases on customer preferences, text images and videos that are made for knowledge-based decisions- considered so important for standing against the competition. Supply chain management, security enhancement and customer experience data are among the basic advantages that AI-aided programs could provide.

Above all, India is quite aware of the promises and perils of AI and that is why it has asked tech firms to seek government approval before releasing under trial or unreliable AI tools and to caution the customers that the programme may not be able to answer every query of the user.

AI tools should be used with the basic understanding that they are governed by the input-output principle and that any predictive analytics provided by them rested on the detection of patterns and keywords in an unusually large database. Best results therefore are achieved when human intelligence works in conjunction with data-driven insights.

(The writer is former Director of the Intelligence Bureau. Views are personal)