By Randy Johnston, K2 Enterprises
When our K2 team offers a CPE course related to accounting technology, our rule is that we should have content that can be applied the next day you return to your office. While creating our team’s content to teach emerging technology this year, we applied this rule and learned some things about emerging technologies.
One key learning point is that emerging technologies can and will be applied in the practice of accounting, whether you are in public practice or industry. It is also clear that emerging technology will contribute to the profits of the firm. Something that was not fun to learn — there are many snake oil sales efforts around emerging technology.
Let’s discuss observations and opportunities:
The latest marketing buzz word is artificial intelligence. We’ve seen this before — for example, cloud computing or “ease of use.” You know the pitch: If you’re not in the cloud, you’re missing out; or, if you embrace this technology, it will make your life easier. While there are applications that work better in or with cloud technologies, vendors used the word “cloud” with their products, even when they were not.
“Artificial” artificial intelligence is suffering from the same issues. AI uses one or more of the dozens of algorithms to process data to produce insights and results that may not otherwise be obvious. Some artificial intelligence applications can apply machine learning. This is where the computer programs can learn without the programming of rules. Machine learning can leverage special hardware and computing power with Google’s TensorFlow, Microsoft’s FPGA (Field Programmable Gate Arrays), Amazon’s AWS Machine Learning, or NVIDIA CUDA.
As a consumer of artificial intelligence products, it is hard for you to tell the difference between a rules-based product or one that has true artificial intelligence. While you may only care that a particular business objective is accomplished, rules-based products typically take more maintenance, are not as flexible, and will have severe limitations when the transactions are less consistent. While AI capabilities are progressing rapidly right now, sales hype is progressing even faster.
Blockchain is just a database. K2 associate Brian Tankersley more fully developed this idea in an article he created earlier this year. While the concept and application of blockchain techniques are important, you don’t need to have FOMO (Fear of Missing Out). Applications are being developed in a wide variety of industries, as well as for public practice. But most of you won’t develop the technology, you’ll just need to use it. Blockchain ledgers provide relatively secure transactions (proponents say “completely secure,” but that may not be so) that can be verified and audited. Much like we use a credit card without thinking much about how the money flows, blockchains will evolve to be an automated black box for processing transactions. We’ll feed a transaction on one side of the box, and a secure, completed transaction will come out the other side.
We have complete blockchain and cryptocurrency sessions ready to explain these concepts in ways that should clarify how blockchains work, why they work, and the opportunities to apply blockchain.
Many industry businesses and CPA firms are hiring data scientists. While data science is important, it is not “the” silver bullet but simply a fresh way to analyze data. Why has this happened? Because we have data available from more sources than ever. Again, colleague Brian Tankersley coined the phrase “digital exhaust” to describe this output, like the way he defined “digital plumbing” to describe the connections between cloud applications. We’ll get even more data with the expansion of the Internet of Things and 5G cellular technology.
But how do you make sense of all this data? Do you wind up with actionable information or do you simply have big, bad data?
We know there are four types of data analytics: descriptive (what’s happening in my business), diagnostic (why is it happening), predictive (what’s likely to happen) and prescriptive (what do I need to do).
But building predictive and prescriptive analytic models is not sufficient in a world where our users’ personal experiences have dramatically changed their expectations. Users want highly personalized, highly relevant recommendations, and one of our roles in using the emerging technology of big data correctly is to ask the right questions.
Conclusion: In our K2 emerging technology courses offered through your State Society, we saw that we had to give a practical accounting solution for each emerging technology including blockchain, artificial intelligence and Big Data.
Don’t be fooled by the sales pitches. While the opportunity is great, the opportunity to be fooled has never been greater.
Are you asking the right questions?
Randy Johnston is a shareholder in K2 Enterprises, LLC, a leading provider of CPE to state CPA societies. He also owns Network Management Group, Inc., a managed services provider that provides support 24×7 from Boston to Honolulu. Concepts for this article were extracted from the Technology Update session produced as part of the K2 Technology Conferences in 2018 and from his own experience working with technology at various firms in the U.S.