Is AI the Future for Spreadsheets?
Until just a few years ago, there was no real alternative to Excel. If you wanted to do any type of data analysis, keep financial records, manage your corporate finances and perform risk analysis, Excel was the only tool at your disposal. But, as those of us working with them to make decisions based on numbers will tell you, traditional spreadsheets leave a lot to be desired. Yet, virtually everybody still uses spreadsheets that are vulnerable to data leakage, undetected errors and often bad business decisions.
Data remains at risk. Especially when companies share financial projections, records and other important financial documents (usually in spreadsheets) as attachments across email. Mistakes happen. Type in the wrong email address, or accidentally CC the wrong person and you could cause a whole world of problems. Plus, of course, sensitive data can get into the wrong hands on purpose, be it through a disgruntled employee, service provider or cybercriminal.
What’s more, studies show that up to 90 percent of spreadsheets contain errors. From copy and paste blunders and hidden cells to miscalculations and version control, it is almost worth assuming that you’ve encountered or created an Excel error at some point.
So, in today’s age of artificial intelligence (AI) and machine learning it stands to reason that this type of tech could be the natural progression for spreadsheets. Many of the big players in the software industry think so. Microsoft has made a significant investment in OpenAI, ChatGPT’s parent company and has announced that it would be adding AI features to Excel and other applications. Google Sheets boasts AI capabilities with auto-suggest for formulas and one-click visual representations of data. But, is AI the magic wand spreadsheet users need, and will it influence productivity?
In theory, intelligence-based features promise huge gains in terms of streamlining operations. With financial analysis for instance, AI may help with layout structure and assumptions, suggesting what the next items to model are and how you should model them. But this is actually no better than an ecommerce site suggesting which books you should buy based on what others are similar to ones you have previously bought.
Yet imagine if, for example, you could just tell the spreadsheet that you have a start-up in the energy sector, and have the financial model laid out for you through AI. Unfortunately, this just isn’t possible, even if the AI could read minds! Even a top consultant cannot come up with a completely perfect model without conversations requiring consciousness.
As any professional dealing with spreadsheet-based analysis daily will tell you, modelling, analysing and presenting a business case is an art as much as a science. An extensively trained machine learning algorithm powering a spreadsheet will still need more information for a proper financial model layout: the size of the company, what type of products or services it offers, and so on. This poses another question, which is: how is the AI trained? What data do we feed into it? All the spreadsheets in the world? Only the ones in your company? The list is endless.
Automation vs AI
There is another way to improve standard spreadsheets. Automation – without the need of AI – can suggest the most common options a trained professional would consider. This still requires an interaction with a chatbot asking contextual questions based on the previous answers. Yet, it removes error probability as it delegates to a machine the task of writing formulae in a spreadsheet based on the answers a human provides.
On the plus side, AI may detect anomalies and warn of potential errors. If problems can be solved with imperative algorithms, they are better and faster than AI. AI is suitable for problems that machines cannot be instructed to solve deterministically. For most businesses, AI can help with workflow, suggesting who should have what permission levels based on past actions.
Finally, could the use of AI in spreadsheets help businesses make better decisions? Certainly. But only when we are able to train it to human-level understanding, ethics, business sense and awareness, or when they’ll train themselves – at that point we may no longer find spreadsheets interesting enough!
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