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A confession from four decades in finance
I will begin with an admission that may surprise fellow accountants: I can no longer prepare a complete Profit and Loss Statement and Balance Sheet by hand.
Early in my career, the month-end close was a test of patience and stamina. We posted journals, footed ledgers, extracted trial balances and chased differences that stubbornly refused to reconcile. The statements were assembled line by line, and transposed figures may could cost an evening.
Then enterprise resource planning (ERP) systems arrived. Over the years they absorbed the posting, the consolidation and the production of statements, and the manual craft I once practised every month quietly faded from disuse.
Is that a loss to regret, or progress to welcome? My answer is: mostly progress, with one important condition.
Every automation has a price
Every tool that makes life easier takes something in return. Cars and aircraft made travel faster, safer and far more comfortable, and in doing so they reduced how far most of us walk. No sensible traveller proposes walking from Singapore to London to keep their legs strong. The objective is to arrive, and machines achieve it better.
The same pattern appears wherever we look. Calculators made long division by hand uncommon in daily work. Spreadsheets retired the columnar pad and the adding machine. For many drivers, satellite navigation has replaced the paper map. In each case a skill weakened, and in most cases society judged the exchange worthwhile.
This is not decline. It is specialisation: when a machine reliably performs a task, human effort is released for work the machine cannot do.
The objective test
How, then, do we decide whether a fading skill matters? I propose a simple two-part test. A skill may safely fade when the real objective of the work is achieved more efficiently and more accurately without it, and when the people responsible can still tell whether the result is right.
The first part concerns purpose. Accounting was never about adding columns by hand. Its purpose is to give owners, managers, lenders and regulators a true, fair and timely picture of a business so they can make sound decisions. Measured against that purpose, manual statement preparation was only ever a means. If a well-controlled system delivers the same picture faster and with fewer errors, clinging to the old method is nostalgia, not professionalism.
The second part is where many automation stories go wrong, and it deserves closer attention.
What ERP actually changed
Looking back honestly, ERP did not make me a lesser accountant. It changed where my value sat.
| Before ERP | After ERP |
|---|---|
| Days spent posting, footing and reconciling | Transactions posted once, at source |
| Statements assembled by hand at month end | Statements available on demand |
| Errors found late, often by accident | Controls and audit trails built into the system |
| Most effort spent producing numbers | Most effort spent interpreting numbers |
The hours once spent producing numbers moved into understanding them. Instead of asking whether the trial balance agreed, I could ask why margins were narrowing in one region, or whether working capital was being managed well. In my experience, the profession moved up the value chain, and good practitioners moved with it.
That is the promise of well-designed automation. It does not remove the professional; it removes the drudgery standing between the professional and the work that matters.
What must never be lost
Here lies the condition. I stopped building the statements, but I never stopped understanding them.
I can still look at a balance sheet and sense when something does not hold together: an unexplained swing in receivables, a margin that looks too good, a provision that has quietly disappeared. I can also recognise when a system has been configured badly, because I know what the right answer should look like. That knowledge was built during the manual years, and it is what allows me to supervise the system rather than simply trust it.
Aviation offers the clearest illustration. Autopilot now flies much of a typical commercial flight, yet regulators have deliberately resisted total reliance on it. In 2013 the US Federal Aviation Administration encouraged airlines to build more manual flying into training and line operations, citing an observed rise in manual handling errors [1]. It followed in 2017 with further guidance on keeping manual proficiency current [2]. When automation fails or behaves unexpectedly, a person must take over, and that person must still be able to fly.
The psychologist Lisanne Bainbridge described this tension more than forty years ago. Her insight, in my words: the more a system is automated, the more it depends on human operators for the rare and difficult moments, precisely when their hands-on skills have had the fewest chances to stay sharp [3].
This suggests a practical distinction:
| Production skills | Judgment skills |
|---|---|
| Doing the task step by step | Knowing whether the result is right |
| Can safely be handed to machines | Must be kept by people |
| Example: posting journals, compiling statements | Example: spotting a misstatement, challenging an estimate |
| Example: constructing sentences | Example: deciding whether a sentence is true and says what you mean |
Losing production skills is the natural price of progress. Losing judgment skills is how professionals lose command of their own tools.
The same lesson, now for AI
Generative AI is doing to writing and analysis what ERP did to bookkeeping. It drafts reports, summarises documents and produces fluent sentences, drawing on patterns learned from vast amounts of text. Much of what it writes reads well, and there is little virtue in rewriting a good sentence merely to prove we could.
The risk lies elsewhere. A 2025 study by researchers from Microsoft Research and Carnegie Mellon University surveyed 319 knowledge workers who use generative AI at least weekly. Participants who placed more confidence in the AI reported applying less critical thinking to its output, while those more confident in their own expertise reported more scrutiny [4]. Because the study relied on self-reported survey data, it shows an association rather than proof of cause. Its broader observation is still telling: critical thinking is shifting from producing content towards verifying it, integrating it and stewarding the task.
Regulators are reaching a similar conclusion. The European Union’s AI Act requires that people assigned to oversee high-risk AI systems be enabled to remain aware of automation bias, the tendency to over-rely on a system’s output [5]. In governance terms, human oversight is only meaningful when the human still has the competence to disagree with the machine.
That mirrors my ERP experience exactly. Production moves to the machine; judgment becomes more valuable, not less. Professionals who keep their domain knowledge current become better supervisors of AI. Those who let it lapse risk accepting confident answers they can no longer check.
Arriving with clear eyes
I do not miss building a balance sheet by hand, any more than a traveller misses walking across continents. The machine carried the load, and I arrived at better work sooner.
But the traveller must still know the destination, and the accountant must still know when the numbers are wrong. Let automation take over our labour, but never our judgment.
A question to carry into your week: list the skills in your role in two columns, those that produce and those that judge. Release the first column to the machines with a clear conscience. Guard the second as the core of your professional worth, and keep exercising it.
AI-assistance note. This article was drafted with the assistance of an AI writing tool. The ideas, professional experience, editorial decisions and final content were reviewed, edited and approved by the author, who takes full responsibility for the published text.
Disclaimer. The views expressed are the author’s personal opinions, drawn from his own professional experience, and do not represent the views of any current or former employer, client, academic institution or the World Certified Institute. This article is provided for general information and discussion only and does not constitute accounting, legal, regulatory, financial or other professional advice. References to research, regulations and organisations are for illustration only and do not imply their endorsement. While reasonable care has been taken to ensure accuracy as at October 2026, research and regulations change, and no warranty is given as to completeness or currency. Readers should obtain qualified professional advice before acting on any matter discussed. All trademarks remain the property of their respective owners.
References
Federal Aviation Administration (2013). SAFO 13002: Manual Flight Operations. 4 January 2013.
Federal Aviation Administration (2017). SAFO 17007: Manual Flight Operations Proficiency.
Bainbridge, L. (1983). Ironies of automation. Automatica, 19(6), 775–779.
Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R. and Wilson, N. (2025). The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers. Proceedings of CHI ’25.
European Union (2024). Regulation (EU) 2024/1689 (Artificial Intelligence Act), Article 14: Human oversight.
This article was written by Dr John Ho, a professor of management research at the World Certification Institute (WCI). He has more than 4 decades of experience in technology and business management and has authored 28 books. Prof Ho holds a doctorate degree in Business Administration from Fairfax University (USA), and an MBA from Brunel University (UK). He is a Fellow of the Association of Chartered Certified Accountants (ACCA) as well as the Chartered Institute of Management Accountants (CIMA, UK). He is also a World Certified Master Professional (WCMP) and a Fellow at the World Certification Institute (FWCI).
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World Certification Institute (WCI) is a global certifying and accrediting body that grants credential awards to individuals as well as accredits courses of organizations.
During the late 90s, several business leaders and eminent professors in the developed economies gathered to discuss the impact of globalization on occupational competence. The ad-hoc group met in Vienna and discussed the need to establish a global organization to accredit the skills and experiences of the workforce, so that they can be globally recognized as being competent in a specified field. A Task Group was formed in October 1999 and comprised eminent professors from the United States, United Kingdom, Germany, France, Canada, Australia, Spain, Netherlands, Sweden, and Singapore.
World Certification Institute (WCI) was officially established at the start of the new millennium and was first registered in the United States in 2003. Today, its professional activities are coordinated through Authorized and Accredited Centers in America, Europe, Asia, Oceania and Africa.
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