the boundary you must cross to ensure future success.
by hitendra patil
rise of the aiccountants
imagine there is no artificial intelligence.
i know it is tough to imagine this, but for the next two minutes, just imagine there is no ai.
more: ai systems just for accounting in development | three ways a.i. will take shape in accounting | four ways to prepare for the ai era | seven ways ai could change accounting | who is better at accounting, ai or humans?
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how have you been working as an accounting professional without ai so far?
you were:
- gathering information
- organizing information
- processing information
- applying accounting principles to information
- applying regulatory rules to information
- creating compliant information reports to deliver to clients
and if you provided advisory service, you were also:
- analyzing information
- finding insights from information
- communicating/discussing the findings with your clients – to help them make critical/timely/better/prudent financial and business decisions
now, imagine there is ai
well, you don’t need to imagine ai’s presence today.
but imagine ai becomes ingrained in every part of the technology you will be using.
how will you be working as an accounting professional with ai?
you will:
- not (need to) gather (most of the) information. ai can do that for you.
- not organize information. ai can do that for you.
- not process (most of the) information. ai can do that for you.
- not need to apply accounting principles to the information. ai can do that for you. but you might need to “review” what ai does.
- not need to apply (most of the) regulatory rules to information. ai can do that for you. but you might need to apply more complex/comprehensive regulations relevant to each client’s situation and “review” what ai does.
- not need to create compliant information reports to deliver to clients. ai can do that for you. but you might need to “review” what ai does.
and if you provide advisory service, you will:
- need to know what your clients want to do, their goals, aspirations, risk tolerance, business/financial stage, industry situation and how economy/regulatory changes might affect them, etc.
- not need to analyze (most of the) information. ai can do that for you. but you might need to “review” what ai does.
- not need to find (most of the) insights from information. ai can do that for you. but you might need to “review” what ai does.
- need to communicate/discuss the findings with your clients – to help/guide them to make critical/timely/better/prudent financial and business decisions
while it is not easy to predict the timelines of when will the tasks/functions mentioned above will get into the ai realms, it is reasonable to assume that well defined, mostly data-related tasks and functions are ripe for ai to take over.
so, what’s the most critical difference?
1. foundationally, ai is:
- as good as the data it is trained on
- as good as the user’s competence in using ai
accounting is all about accurate, compliant and timely data.
ai is phenomenally good and infinitely better (compared to humans) at handling data.
therefore, the first word you want to focus on is data.
2. foundationally, what do your clients do?
they want to manage their finances as effectively as possible, so they take your help. but, their “numbers” directly reflect what they do day in and day out (hopefully, they take your advice).
therefore, the second word you want to focus on is decisions.
the two words that will define your work future in the ai world
now you know the two most critical words.
data. and decisions.
the closer your work is to data, the more likely ai will impact your work (more severely as time goes by and ai capabilities evolve).
on the other hand, the closer your work is to the decisions your clients are/should be making, the lesser will be the threat of ai to your work. why? because what humans are thinking/planning/reviewing/contemplating/worrying about is not yet converted to data. ai simply cannot work without data.
how?
using only some large language models (llms) like chatgpt, bard, etc., is not enough. the first and foremost thing you must do is learn how ai is created, how ai learns and how ai works. and after you do that, you will be an aiccountant™, i.e., accountant augmented by (not replaced by) artificial intelligence.