As Xero CEO Rod Drury recently said, “Every small business, accountant and bookkeeper now has a supercomputer working for them.”

So how did we get to this undeniably exciting, and perhaps even mildly scary, point in time – and what does it mean for accounting?

While for decades, the promise of thinking machines has remained unfulfilled, essentially providing nothing more than fodder for science fiction authors like Arthur C. Clarke and Isaac Asimov, things have changed more recently. Functional advances in computing power, storage capacity and software capability have provided the quantum leap to make what was theoretically possible in the 1960s practically possible today.

That’s been complemented by the structural change in how data is stored – online, in the cloud, rather than in data centres – and accessed, with programming interfaces (called APIs) which provide the ability to use information in innovative ways.

You already see elements of artificial intelligence (AI), and its close relation, machine learning, in your dailylife today. Siri and Google are good examples of ‘digital personal assistants’, which provide personalised services based on attributes they’ve learned about you.

The possibilities and realities of professional AI

A more intriguing prospect is the application of machine learning and AI into the professional context. Understanding how that will work requires a quick view at how they’re made possible – and that’s a story which starts with the cloud.

After all, the supercomputer to which Drury refers needs information before it can do anything clever. Cloud solutions provide an unprecedented advantage, because all the raw data of millions of users can be anonymised to create the foundation on which AI and machine learning is built. That data is the grist for this ultra-modern mill; machine learning takes place across this data to serve up AI insights and actions which can drive efficiency and performance, and deliver greater convenience, while further eliminating repetitive, manual and tedious tasks.

In simple terms, technology won’t just collect information – it’ll learn from what it stores. Accounting software is getting smarter, automatically performing analysis which previously required human intervention. Consider tasks like bank reconciliation: systems can learn how to completely automate this infuriating job, freeing up your time.

Other industries where AI is being used to fascinating effect include movie-making: the trailer for thriller Morgan was made using the computing power of IBM’s Watson. Banks are looking at using AI chatbots to help customers resolve queries – in fact NAB launched an experimental one back in 2009. Online shopping sites like eBay and Amazon use machine learning to make accurate recommendations of products and services you’d be interested in.

Internal and external data for greater context

It’s not only internal data from which machines learn and provide AI insights. The Hey Xero chatbot, for example, is being designed to integrate financial information with that from Facebook Messenger. It’ll make use of machine learning technology and transactional data processed in Xero to enable businesses to query their latest financial data, including who owes them money, when their next bill is due, or how much money is in their bank account. It will even do smart stuff like connecting to the Xero advisor directory and can recommend a suitable accountant or bookkeeper in their area. Plus it helps discover what new apps are available in the Xero marketplace.

Drury says things like categorising expenditure and sending accounts to be checked could be automated by AI and machine learning programmes which learn the habits of business.

And did we mention Siri earlier? Imagine an intelligent assistant that could answer questions and provide information from your accounting system and the broader business environment. Xero has imagined just that and is working on it. Machine learning technology will also automate many other tasks, such as coding invoice transactions, and providing access to real-time customer and supplier information from public records.

How automation and AI benefits the advisor

With considerable advances in machine learning and AI being made every day, the real question accountants and bookkeepers are likely to wrestle is, “How does this affect me”? An innate tendency to be wary of progress has long characterised the industrialisation of society: change can be frightening, particularly when it impacts your profession.

But the introduction of AI heralds opportunity more than anything else. Machine learning cannot match human insights; rather, it complements brain power. It does the heavy lifting of calculations, the dull stuff of reconciliations and the tedious work of verifying information. While AI does mean computers learning and applying insights, they cannot think like you do and are unlikely to offer the emotional intelligence needed to navigate the complexities of the human world (and, stereotypes and bad jokes about bean counters aside, that does extend to accounting).

As a result, as machine learning and AI have an increasing role in the profession, it will make you more proficient, more productive, capable of taking on and handling more clients, while also delivering more value through insight, rather than through long hours of tallying up figures.

Echoing Arthur C. Clarke, who once said, “Any sufficiently advanced technology is indistinguishable from magic”, Drury contextualises the impact of AI on the accounting industry by noting, “Now we need to make accounting magical. Machine learning is how you create that magic.”

That is surely an exciting prospect for you as an accountant or a bookkeeper. And for your clients, too.

This article was provided by technology journalist Donovan Jackson.