Like the five blind men describing an elephant, AI means many things to many people and taken individually all of them are not incorrect. Hence a good place to start is by defining both the terms Artificial and Intelligence.
Artificial in the context of AI means anything which is non-biological, i.e. outside the plant and animal kingdom. A short and precise definition of intelligence is the ‘ability to adapt to changing environment.’
In the biological world, the ability of a sunflower to face the Sun as it moves across the sky and a chameleon to change its colours to match its environment are illustrations of natural intelligence. On the contrary, a calculator, a computer game and complex algorithms used by Google and Facebooks to personalize what their users view in their feeds are illustrations of AI as they generate customized response to different situations.
AI For CS
At the base level, AI is labeled narrow or weak AI. In this, the nature of performance expected is defined and the answer is known prior to the question being asked. In business, its best use is in Robotic Process Automation (RPA) embedded in the software, for automating defined business processes. Typical examples of RPA are:
- transferring data from emails to system records like updating customer address from emails to records,
- replacing lost credit cards details with the new one in multiple systems and records,
- identifying failure to charge for services based on analysis of multiple internal usage records and comparing them with billing systems,
- reading legal contracts and extracting specific clauses or information required.
In the Indian Corporate Secretarial World, the use of pre-filling fields in MCA forms is an illustration of RPA. While the extent of pre-fill in the forms available today may be restricted to a handful of fields, the day is not far-off when most of the fields would be prefilled using data from earlier filings of the company or its directors, requiring only a handful of fields to be filled in by users.
At CimplyFive, we have enabled in our automation software, BLISS the feature of prefilling the statutory registers and MCA returns with the data captured at the time of creating an Agenda proposal. An example of it is of using the data given by the director and captured by the company secretary in creating an agenda proposal to fill the Register of Directors and Key Managerial Personnel and DIR-12, required for intimating the appointment of director to the MCA.
At the next level is general or strong AI. Here the objective is to gain cognitive insights from large volume of data analyzed using algorithms. Illustrations of its typical use are to identify users who are likely to be buyers, identify credit card defaults, detect insurance claim frauds, automate personalization of digital ads in search site and mobile phones, and recognition of speech and images.
Practical examples for the use of cognitive insights in the Indian Corporate Secretarial world are not easy to identify, as they need large data pools for analysis. The day is not far-off when we will see regulators like MCA use data of all the companies filings available in its database to predict companies that are likely to- default in filing, file for bankruptcy, defraud on its investors or lenders based on their directors’ and key managerial personnel’s profiles.
At the third level, AI is used for cognitive engagement, i.e. engaging with stakeholders like customers, employees and prospects. Illustrations of this are using chat-bots and intelligent agents for automating interfaces like customer services, technical support services and handling employee queries on compensation and benefits.
Given that cognitive engagement is in its initial stage of development, the most common use of it is seen in free to use sites, which in many ways are experimental, followed by employee engagements sites for organizational insiders. When it comes to dealing with stakeholders external to the organization, it is used in providing customer service or technical service. At the highest level, it can be used to engage prospects and converting them to sales, an area where its use is not visible, as this is a task which even human intelligence is struggling to master.
In the Indian Corporate Secretarial world, use of cognitive engagement can be explored in the area of regulatory information dissemination and interpretation as a part of a larger initiative of promoting ease of doing business in India. Given the voluminous texts in the Companies Act, 2013 and its interlinkage with the SEBI regulations coupled with frequent updates to these regulations, use of chat-bots to help users get the relevant information they need when they state their requirement in words which may be different from that used in the regulations is an apt application for cognitive engagement.
What is today is in the realm of fiction and movies is the highest-level AI, which for the want of a better word we can call God-level AI. Here AI has the capability to not only think, prioritize, act and monitor its own behavior but also continuously evolve in defining the purpose for which it exists.
Moving into the realm of fantasy, some day in the future, we can visualize in the Indian Corporate World, a computer that not only enacts the Company Law and SEBI regulations but also monitors the activities of all the entities regulated by it and evolves on its own by modifying the regulations to meet the purpose that is appropriate at that point of time, be it promoting ease of doing business or preventing frauds, misrepresentation and mis-use based on that which is more important.
To conclude, in the days to come, the world of CS will be significantly influenced by technology and AI will play a significant role in the work-life of a CS; the question is no longer ‘if’, but a question of ‘when’?