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3 Things You Need to Know About Adding Artificial Intelligence to Your Technology Stack

It’s 2020, and after possibly months or years of stalled digital transformation conversations

and further delays due to COVID-19, your manager or one of your firm’s executives has

finally given you the green light to start pursuing artificial intelligence (AI) and machine

learning (ML) accounting solutions.

It’s great news that will allow your business to remain competitive, but where do you start?

Here are three tips to consider when looking to evaluate what AI can bring to your

outsourced accounting practice.

Is it Really AI?

Let’s clarify what AI is. It’s machine technology that’s able to solve for certain tasks typically

performed by humans, which tend to be related to classification and prediction. On an

average day, you probably interact with AI technologies like voice-activated assistants Alexa

and Siri; email spam filters that can separate the junk from regular email; and Lyft and Uber,

which use AI to figure out when your ride will arrive.

But most importantly, AI learns from experience and can get smarter on its own.

You will no doubt find tons of solution providers claiming that their technology can

automate various aspects of accounting processes. In reality, many of these technologies

aren’t AI but rather Optical Character Recognition (OCR), which is software that recognizes

text from a document, like an invoice. Both OCR and AI are used to automate tasks, but OCR can only function based on rules that humans have programmed it with. With AI, however, the technology can think for itself through continuous exposure to data.

If you take time to look under the hood, the most valuable question you need to ask is,

“Does your AI learn on its own?” If the answer is “No,” then it’s not AI, and the system will

never be able to do more than what you have to dedicate time and effort programming it to


The Proof is in the Data

AI is only as smart as the data it’s been exposed to. The quality of the data is responsible

for making the technology as accurate as possible, so this is no small concern. It’s the

same as eating a meal - if you “fuel” AI with a lot of clean data, like eating your fruits and

vegetables, it will get smarter. If you feed it data that’s not clean, it’s the same as eating fast

food - you get out of the AI what you put in. For AI that tackles invoice processing, it’s

important to understand things like:

  • How many financial documents and transactions has the AI trained on? (If it’s in the hundreds of millions, or has been trained for years, that’s a good sign)

  • Have actual auditors audited the data?

  • Does the data meet strict privacy and regulation laws?

  • Is the data set clean?

All these elements contribute to the intelligence of the AI.

Plays Nice with Others

True AI is similar to other technologies, like the cloud, in that it is agnostic and can be used

with multiple other platforms. As you start evaluating AI accounting vendors, you’ll want to

look for a solution that allows you to switch easily between systems and not have to overly

rely on a single platform.

Like a member of your accounts payable team, AI should be able to work with any

technology. Your accounting firm should have some level of ownership of the AI since it

would be developed from your client invoice data and the associated interactions. The AI

shouldn’t be “trapped” or “locked” into a system you don’t have full control over. That would be like hiring a new staff accountant and only giving them access to one of the eight

platforms they need to do their job.

For additional AI technology considerations, check out the eBook How to Select the



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