AI strategy and quality thought leadership – why it’s crucial for modern accountants

Highlights from the Conversation

What is AI decision making and how do you go about it?

If there are all these new accounting apps coming out every other day, it’s normal to think, shouldn’t it be harder to build? And a part of its yes and a part of its no. I usually say to people that there’s AI, and then there’s AI. Our AI we use at Access is safe. When it comes to tech changes in the accounting world, we actually have a new tech change every 10 years, roughly. So, we went from paper to Quicken and Lotus Notes in the late 80s. By the end of the 90s, we were going to desktop suites. In the 2000s, we were going to the cloud. And now, AI is here. The biggest difference between AI and all those other ones that we’ve all adapted to in the past is, accountants who have used AI see the benefit immediately. It’s so obvious that this is going to have use cases for us and we don’t necessarily know exactly what they are. Accountants are looking at AI and are recognising that this will make their life easier.

I can tell you that because there’s so much obviousness about where AI is going to be able to help, I think we’ve just seen this rush of new apps coming into the marketplace and that’s going to cause a problem. I’ll explain the problem really clearly. The problem is that firms and accountants and small businesses are having to run their practice or run their small business, using maybe 10 apps every day. So, if you’re in and out of workflows and your reliance on usually one central app to open data up and to allow data to flow, we call that APIs. So, these are APIs that are connected to other integrations or platforms which means all of your data, all of your firm data, is sitting in different apps and different databases and different silos all over the place.

AI works so well because it’s trained on so much information. You need a lot of data for these things to work and the more specific data you can put into it and the more proprietary data you can put into it, the better it gets. That’s where this stuff’s really going to start elevating firms. I think that firms that need to make decisions about software purchasing and workflows, I think that we need to have a different conversation about where our AI is right now, rather than “here’s a new shiny toy, I’m going to rush to use it.” I also think that we need to start thinking about what AI strategy looks like for firms, because if tech changes every 10 years, I’ve just proven that it has, then it’s reasonable that a board of an accounting firm or a managing partnership committee should be talking about the tech changes and the platforms that they use in a 10-year cycle.

We’ve got a working prototype now where a firm running Handisoft desktop can push tax return data into ChangeGPS. Desktop data moving into a cloud-based product that is enabled by artificial intelligence. This will mean that no firm is going to be left behind with AI. The reality is, there’s thousands of firms in Australia who can’t, don’t want to deal with the disruption. They want to move to the cloud if it’s the right product for them, but at the same time they want some of the benefits available, and AI represents that opportunity for them.

How is the Access Group upskilling in AI to create an evolving product useful for the accounting industry?

I think it’s just a positive message. The subject matter expert isn’t made less important because of AI. You still need to know what to ask and you still need to know what the wrong answer is. The way we can do it is we’ve got access to this Evo platform. So, everyone at Change GPS is going to get Evo and, and not just ChangeGPS, all the Handisoft firms will be getting it on their desktop.

At Access, we’re able to get the required learning and information. and then we’re able to come up with discrete use cases for accountants. The easy ones that we thought we’d come up with were the vectorisation of the ATO website and fair work, and on our roadmap is private binding rulings as well. We need to get lots of firms on this, because the more information we feed AI the better the service will be for everyone. The more AIs used, the smarter it gets. But the security layers that we’ve got on Evo are so advanced that every firm and every user has their own security, and at our level we have our own security, so we can train it. We’ve got people in our AI system always, that are using it and asking questions and prompting it and saying, no, that’s wrong. It’s about the exercise of consistently using it and training it for the AI to get smarter.

Firms sit on gigabytes, terabytes of really, really critical data. How do we get all that data in one place to update AI engines, so anything you want to do is made easier rather than connecting it piecemeal from all these silos? Can we have it in one place so that we can query it? How does a firm get this information now?  It’s often expensive subscriptions, or it’s a lot of time spent searching a largely tough to search database on the ATO website. Now, you can search it through Copilot, so anyone in your team can ask a question about firm policies, engagement letter requirements., whatever you can think of. You can basically create your own help desk inside your firm. Once it can work out the context of the question that it’s being asked, it’s pretty exciting.

What is an AI strategy and why should it be implemented?

Whenever a business is adapting to something new, or whenever responding to risks and opportunities in any business, leaders must think, “what’s my strategy going to be around this?” We’ve got so many early adopters that are jumping on AI and are using the tool and are coming up with answers, and that’s fantastic. I think we all need to take the same approach that we make with other big decisions and big investments we need to make in business.

We thoroughly research. We have a look at what’s on the market, we talk to all the big players and find out what their plays are, and we think about the type of firm that we want to be. From here, we try to understand if there is a capability out there in these products that we didn’t know was needed, and would it solve a problem? The strategy that I think accountants might want to adapt is to go to all the big players and go out to the critical vendors that you’ve got in your mix and ask, “what do you have that’s coming down the pipeline that I need to be aware of?”  From here, the decision criteria can become how they’re going to respond to this and question whether they want this to be part of their firm’s future.

I would strongly encourage accountants to have AI as part of their future, just like I’d heavily encourage everyone to have cloud as part of their future, if they’re not there already. Accountants should ask themselves, “how are we going to support this? Are we going to build this ourselves? Are we going to go to the market and have a look at what’s cutting edge?” Almost every time in the past, firms have decided to build. Over the last five years, I think there’s been a lot of investment in big accounting firms and their own internal IT teams and they’re building out amazing products and amazing analysis themselves; however, other companies like Access can now provide just what they need.