You’ve no doubt heard it – COVID-19 has accelerated the adoption of cloud technologies and work from home by at least five years. But what does that actually mean? In short, conversations that IT professionals thought they would be having in 2025 or beyond are happening today. A year ago, advanced cloud computing was for technology-savvy organizations. But COVID-19 and sudden shelter-in-place orders meant that the benefits of being able to access your tech stack anywhere became very clear, very quickly.
So what does this acceleration mean for top technology trends and the accounting industry? Below I’ve broken down how three top technology trends will impact the accounting industry in the next 2-3 years.
Big data analytics will increasingly impact how we make decisions.
Big data – the large volumes of data that inundate a business on a day-to-day basis – is already among us. However, using big data in conjunction with powerful analytics tools and platforms is still a relatively new concept. Consider how most organizations access and utilize analytics today. A single piece or subset of data from a few applications in your tech stack is analyzed through a mostly manual method, with humans driving the metrics.
Analytics tools of tomorrow will see big data integrating with AI- and RPA-supported analytics tools. These tools will not only track human-determined metrics, but through sophisticated computational analysis reveal patterns, trends, and associations that humans may not have found. Warehouses consolidating data from multiple applications across your tech stack will become common as big data and analytics integrate. A few organizations have already built tools that utilize advanced computational models to provide actionable intelligence.
And how will your organization pull big data into these data warehouses? Through APIs and RPA. Which leads me to:
RPA will be applied to more and more mundane, repetitive tasks.
Like big data, RPA – robotic process automation – is not new to the accounting space. Over the next 2-3 years, expect to see adoption accelerate as accountants and IT professionals become more comfortable utilizing RPA as part of their business process. RPA will perform those mundane, repetitive tasks that take up so much of our time. RPA will support humans as they perform more useful, productive, and valuable work, whether in consulting, analysis, or review.
For example, consider the organization with two disparate systems and a need for data from system B to be entered and/or updated with information from system A. These systems do not support an API to transfer the information. The firm has two options: having inaccurate information in one system or having someone manually update system B. With RPA, this process could be done overnight to avoid manual intervention, and all your staff will need to do is review the results.
AI will automate time-intensive and tedious decision-making.
As with big data and RPA, AI is not unknown (there’s a theme here). However, AI has been slow at proving itself more than a gimmick or talking point and has had even slower adoption rates. However, AI is reaching the adoption (and usefulness) tipping point. In the near term, I expect that AI will increasingly be integrated into systems, quite possibly in a way that users may not realize AI is behind the technology, helping them make decisions.
For example, we are looking at how to bring AI into workflow, specifically into scheduling and how to automate staff scheduling for our clients. Rather than the administrator poring over spreadsheets and manual reports to determine the correct staff combination to provide the knowledge and experience necessary for an engagement, AI will review all pertinent data and make suggestions at the click of a button. The user – an administrator in this example – may or may not know that AI is providing these suggestions. They may or may not care. But what they will care about is that their job is becoming easier, and one of their tedious and time-intensive tasks is being simplified.
Over the next few years, expect to see several technologies begin to work together behind the scenes to facilitate human decision-making. As with the administrator using AI to assign staff to engagements, users may not know that these technologies are making their work more efficient – and that’s the point.
It’s not the users’ responsibility to make it work – it’s the technologists. We are the people working to combine all of these technology tools so that users and all stakeholders, both internal and external, have access to that data to make more intelligent decisions. Some technologies are already working together, and as for the rest – we’re working on it.
