Complete guide to selecting the right tool for AP hyper-automation

With the development of artificial intelligence and machine learning, businesses today are now presented with a new opportunity to do more in less time with the power of AI. From data processing to giving strategic recommendations to sales teams, this is just the beginning of the artificial intelligence era — and its adoption rate isn’t slowing down anytime soon.

In this buyer’s guide, you’ll learn the nine critical elements to consider when selecting the right hyper-automation & intelligence platform for your business. Let’s get started!

Download the AP hyper-automation checklist

(1.) Determine critical needs and ask for proof

Identify why your company needs AI

Before doing anything else, the first thing you want to do is to understand why you need to invest in an AI platform. Do you need it for data entry or approvals? Or, do you need it to track inventory or shipping? This will help you pinpoint what exact functionalities your system should have and simplify the research phase. 

Research & get proof

After identifying your needs, it’s time to consider the options. Do research. Get quotes. Ask for a live demonstration.

Getting a live demonstration is important because you want to make sure that the AI company you're considering has developed technology that works as advertised. AI technology is still new, so you just want to double-check that the sales rep you talk to has proof to back up any advertising claims you find online or elsewhere. 

(2.) Does it revolutionize workflows?

AI technology is rapidly reinventing the workflow for companies across all industries. When an AI system is appropriately deployed and developed, human input and interpretation will no longer be required. The new job for your internal teams will be to review the suggestions from the data AI provides. This allows your teams to get back to doing other tasks that have more impact on your company’s bottom line. 

The goal of AI is to simplify your workflow

A well-trained AI should only ask for human input when its confidence is low. The higher the AI’s confidence, the less a human has to review. The goal, over time, is that less and less human review will be required. Great AI should perform at a higher level than a human is capable of today.

Pro tip:

When investing in an AI platform, confirm that the company behind the AI platform is moving in that direction—where a human will be primarily reviewing the AI’s suggestions. This tip ties into point one. Ask for proof. If you don’t ask for the proof upfront, you may be unpleasantly surprised by the amount of time it takes to manage the system that was supposed to “give you back more time into your day”.

(3.) Is it system-agnostic?

Because this technology is rapidly emerging, you want to confirm that the AI platform you select is adaptable to the other related systems your teams use in the day-to-day. That means that your AI platform needs to be “system-agnostic”. 

What is system-agnostic exactly? 

System-agnostic is defined as the flexibility your platform has to connect to different systems. You never know what systems your customers or employees may use in the future, and you want to ensure that your AI platform can integrate seamlessly with the platform. 

Example:

If your company uses Salesforce, you should be able to easily integrate your AI platform with Salesforce to use their powerful sales analytics capabilities. At the end of the day, you want your new system to make your life easier, not harder. 

(4.) Does it require more headcount to manage?

Which one is more costly: hiring more human talent or investing in a new hyper-automation system? We will let you answer that question.

Like hiring a new assistant, your AI should continuously get smarter so it can function as the new, little genius team member who always remembers what it’s been taught, never gets tired, whose talent you never lose to other opportunities, and who you manage directly.

The opportunity of AI

We do want to address one common concern with this point. Many are worried about job security when it comes to onboarding new technology. Instead of fearing automation, you should look at the opportunities it will give you. Hyper-automation platforms free up your time to do more meaningful work while the system takes those more tedious tasks off your plate. It’s a win-win for everyone involved!

(5.) Is the software reliable in making predictions?

One small slip-up can cost your company time and resources. By selecting an AI system with the lowest error rate on the market, you can breathe a sigh of relief knowing that errors won’t slip under your nose. (Because to be frank, we all know that a “small slip-up” can cost companies millions.)

Errors can cost your company... big time

​You will find many vendors in today's market that offer solutions with error rates higher than 10%. If you run an eCommerce business, for example, you can expect to suffer financial losses if your AI system fails to process orders in a timely manner. This could lead to a long list of frustrated customers and a group of individuals who aren’t interested in doing business with your company anymore. That financial hit will impact your sales in both the present and future. 

Fortunately, there are platforms that offer error rates significantly lower than 10%. By choosing one of them, you will ensure that your business is protected from loss.

*Important to Note: At Vic.ai, our platform has an accuracy rating of 97-99%. We are proud to say that we have one of the highest accuracy ratings in the market!

(6.) Difference between legacy features and new, more efficient features

When selecting the right platform for your needs, don’t just focus on the short-term costs. Consider how each option will perform in the long run. Data is volatile and it’s important to make sure that you are making the best investment possible for your company’s future. This is why we’re here to tell you that a legacy system shouldn’t be part of that future. 

We’re not a fan of legacy systems...

What do we have against legacy systems? Well, we have a laundry list of reasons, but we will give you just a few. For starters, many legacy systems have terrible performance and predictions compared to a well-trained AI platform. Legacy systems can have a high upfront cost, especially since they generally require a lot of manual work beforehand. On top of that, legacy systems are typically rule-based and rigid. This can be a major issue when trying to scale for growth as the number of rules will need to multiply to account for changes in the business. This leads legacy systems to become more difficult to manage as the volume of data increases. 

Witness the difference with AI

On the contrary, AI platforms are data-driven and hyper-flexible. By using an AI platform, your business can make decisions based on real-time data points rather than strict rules. This allows your company to effortlessly scale and adapt as needed. AI platforms also use historical data to predict future trends and performance, which is why they’re so effective at managing the hyper-volatility of data. 

Content for finance pioneers: The difference between autonomous invoice processing and invoice processing automation

(7.) Continuous learning

Your platform should be able to learn continuously. A good AI system must have the ability to learn, make decisions, and take actions based on those decisions.

Scale your business with continuous learning

A legacy system doesn’t have the ability to continuously learn because like mentioned before, legacy systems are strictly rules-based. You don’t want your system to be rules-based because it requires constant re-iteration as new scenarios or new types of documents appear. 

Having a rules-based system may be fine for now, but it won’t be scalable when your business expands and changes with time. That just isn’t optimal in the long term. You want your system to get smarter over time and learn from human feedback. The goal would be that over time, the machine would learn the tactics that work and well… ones that don’t from your team. 

By selecting an AI platform with strong continuous learning capabilities, you can be confident in your software's ability to adapt and grow alongside your company's needs.

(8.) Be prepared for change management 

A wise company once said, “change management doesn’t end once the new system is deployed.” And, we couldn’t agree with this statement more.  

When you implement new software into your everyday processes, you have to come up with the process, communicate what that process is, train current employees, ensure adoption, and train new people on how to use the software. As you can probably tell, this can be a HUGE undertaking — especially if your business is more technical in nature. That’s why you want to select a platform, like the one we have at Vic.ai, that is prepared for change management. 

Example: 

Here’s a hypothetical example. You’re the CTO of a large eCommerce company and you decide to install an AI platform in your organization. You and your team spend the next six months creating the perfect strategy for your company. Then, you spend another three months communicating it to all employees. Finally, you launch the new process and everything is going well…. or that’s what you planned for. 

The reality is that you have to keep up with the changes that come from your AI system. You have to regularly monitor what your AI is doing and make sure that it’s working correctly. In addition, if there are errors or bugs, you have to report them and have them fixed by the third-party developer. This can take a lot of time, so if you want to automate things,  you need an AI platform that is prepared for change management. (Unfortunately, not all AI platforms are prepared for change management, so be sure to ask the sales reps those hard questions and be educated on the platform you are about to purchase.)

(9.) Intelligence 

Intelligence is everything in the world of AI. You want to make sure your system is smart… real smart. By using technology to leverage existing data sources, you will reduce the manual work of extracting, manipulating, and reconciling actual data from source systems. An intelligent system goes beyond machine learning and autonomy,  allowing you to make smarter and faster decisions with intel from your data sources. 

Example: 

Prism is a great example of a company that uses intelligence effectively. Prism utilizes spend optimization by sending due date reminders, tracking bills, and scheduling payments all through their intelligence technology software. This type of system can apply to business billing/invoice payments as well, making it the best app for bill payment! 

The Bottom Line

AI and machine learning are reshaping the market in ways never seen before. If you don’t begin to consider adopting hyper-automation and intelligence into your business, you may just get left behind. Your competition is already adopting this technology into their everyday processes, why haven’t you? 

In this guide, you’ve been introduced to nine core areas you should explore as you work to select the right AI platform for your business. When you’re ready to start considering your options, focus on an AI platform that’s:

-Proven to meet your needs

-Able to revolutionize your workflow

- System-agnostic

- Autonomous

- Highly accurate

- Not just another legacy platform

- Always learning

- Prepped for change management 

- Intelligent

Are you ready to enter the new era of accounting?‍

There are many options available, but how do you know which accounting tool will actually improve productivity, decision-making, and your employees’ quality of life?

Start now with the AP hyper-automation checklist and find out if you’re on track to give your employees the gift of time.