Brace yourself for AI and blockchain

At first glance, the threats seem clear: One type of software will learn how to perform all manner of business functions, particularly in finance and accounting, while another will continuously validate any set of data or information.

Between them, artificial intelligence and blockchain seem poised to disrupt — or even destroy — many of the core businesses of the accounting profession, automating or rendering irrelevant important traditional services like the audit. But while there can be little doubt that they will eliminate the need for human beings to perform many of the individual functions traditionally associated with accountants, both in public practice and in industry, they will certainly not eliminate the profession’s overall role, or its importance.

In fact, both AI and blockchain have the potential to help accountants actually boost their revenue, their relevance and their value — provided they’re willing to develop the necessary skills, and change their mindsets.

Understanding why each of these two emerging technologies is less of a threat and more of an opportunity than they might seem requires a separate, deeper dive into each, as they’re going to have different impacts on the profession, over different time horizons.

Artificial intelligence

It’s only partially accurate to describe AI as an emerging technology; it has already emerged in some forms and some applications. It’s at the core of IBM’s Watson, for instance, which Big Four firm KPMG is applying to its professional services offerings, with a focus on auditing. H&R Block is adding Watson’s artificial intelligence to its tax prep process, while the Maryland Association of CPAs is working with IBM to train accountants in technology skills like AI and cognitive computing.

All this begs the question: What, exactly, is AI? Pop culture gives us HAL from “2001” as one example, Skynet from the “Terminator” movies as another, and Scarlett Johansson’s disembodied voice in “Her” as another, friendlier one, but those are fictional characters, not models for AI. “A computer that thinks like a human being” comes close to the overall goal of the field, but that’s an idea that’s both nebulous and fairly far off (to say nothing of not necessarily worth pursuing, given the quality of most human thinking).

A more useful definition, and certainly one more in keeping with the current state of the field, is that AI is software that can draw conclusions from large quantities of data, and adjust its activities based on those conclusions — that can, in effect, learn. Leon Katsnelson, director and chief technology officer for strategic partnerships for data science at IBM, cites the example of an elevator company having AI go through reams of data from all of the sensors on its individual cars, identifying from that data the characteristics of an elevator car that is about to have problems. The AI can then keep an eye on all the company’s elevators going forward, and dispatch maintenance crews as soon as they exhibit any of the pre-problem characteristics.

Essentially, AI is about software that can learn and adapt, which is why one subset of it is called machine learning. “Machine learning is like a rocket engine and data is the rocket fuel,” Katsnelson explained. “In traditional programming, we’re teaching the machine how we do the job — we’re telling it, ‘Repeat what I do.’ AI is about teaching the machine to learn how we learn — to learn from data.”

That means that it can learn without human input, and that it can act without human direction. It can also analyze far, far greater amounts of data than a human being ever could — and make useful decisions and recommendations based on that data. Given all that, it’s not hard to see why it’s considered the next big thing. IBM, Google and the government of China have all made significant investments in it, according to Katsnelson, who also quoted a famous tweet from Wired founder Kevin Kelly: “The business plans of the next 10,000 startups are easy to forecast: Take X and add AI.”

Some of those startups will no doubt be in the accounting space, attempting to realize the potential in software that knows the entire Tax Code by heart and can see trends across literally millions of tax returns, or that can learn how to characterize and treat new financial transactions based on how millions of similar transactions have been characterized and treated before.

“What can AI do?” Katsnelson asked. “Just about anything. Where can you apply it? Just about anywhere.”

“Most people think audit is the first field in accounting that will benefit from AI,” he continued. “It allows auditors to dig deeper into the data by processing much larger volumes of data. Machines are much better than auditors at processing huge amounts of data.” AI can also process, analyze and incorporate all sorts of structured and unstructured data and information that auditors can’t — and it will be able to consider all the available data, without the need for sampling. “With AI and machines, you won’t need to sample — the machine can check all the transactions, which human auditors couldn’t,” Katsnelson explained. “That’s where the power of the machine is.”

Nonetheless, Katsnelson still sees a critical role for accountants. “I don’t believe for a second that the auditors will be replaced by machines — the human touch, and human thinking, are critical,” he said. “Human judgment is still paramount.” To operate at its best, though, that judgment will need to be paired with data science skills, and accountants will want to make sure that they’re ready and able to leverage the opportunities that artificial intelligence, cognitive computing and machine learning offer.

Erik Asgeirsson, the president and CEO of CPA.com, the technology subsidiary of the American Institute of CPAs, is bullish on the implications of artificial intelligence for those who are ready to leverage it. “Auditors are going to become better with AI. They’re going to provide more value,” he said. “The firms that are leveraging technologies like AI are going to win in the end.”

Blockchain

The idea of machines that think goes back at least a century, so it’s no surprise that AI is fairly well advanced. Blockchain, on the other hand, is still in its relative infancy, with few applications. It’s not likely to have more than a theoretical impact on the profession for at least a year or two, but its eventual impact will be significant, which is why Ron Quaranta, the chairman of the nonprofit industry group the Wall Street Blockchain Alliance, says it’s important to make 2018 “the year of education” about the young technology.

That can start with a clear definition of what blockchain is: a technology that creates a database that’s distributed across the Internet but can only be accessed by users with heavily encrypted, highly secure keys. Those users can post individual transactions, or “blocks,” to the database, and when those transactions are accepted, they become part of the “chain” — and are both completely unchangeable, and irrevocably associated with their creator. A later block in the chain may record a change to the status of the assets or the information in the original block, but that original block remains permanently in the chain.

Before exploring what the means for information — essentially, that the structure in which the information is kept automatically audits and validates the information — it’s worth defining what blockchain is not:

It is not bitcoin. Though it is often associated with the famous crypto-asset, blockchain is an entirely separate technology, with applications that go far beyond alternative digital currencies.

It is not a single database. There are already multiple blockchains, and if it lives up to its promise as a self-validating, self-auditing form of database, there will be many, many, many more in the future. There will be public blockchains (for real estate records, for instance, or the provenance of different types of collectibles), but the vast majority are expected to be private, maintained by individuals or companies for their own purposes. Your bank account might be a blockchain, and you might have an individual blockchain for your interactions with the IRS; a company might keep its books in one blockchain, interact with suppliers through another, and manage its sales tax obligations in another (and that one might be accessible to various levels of state or local tax authorities).

Once you have a clearer picture of what blockchain is, multiple implications for the accounting profession begin to present themselves — and it’s only fair to note that many of the first ones are negative.

For instance, by creating pools of instantly verifiable data, it can transform assurance functions. “We may not need audits if we can access automatically validated information,” explained Jon Baron, the managing director of the professional segment for Thomson Reuters’ Tax & Accounting business. “The Big Four firms are hiring fewer accounting grads — we won’t need these armies of auditors.”

There may be fewer auditors, but that doesn’t necessarily mean fewer audits.

“Blockchain does not mean that the audit will go away,” said CPA.com’s Asgeirsson. “There are going to be huge opportunities in private blockchains for audits. There are going to be assurance needs. Over the next couple of years, you’re going to see some really interesting assurance opportunities arising around blockchain.”

It will be a different kind of audit — the auditors won’t be sampling and waiting by fax machines; instead, they’ll be checking on the security of keys, and pursuing fraud much more aggressively, since they’ll be able to review every single transaction (with a little help from artificial intelligence) — but it will still be an audit, and as the number of individual blockchains climbs, the number of potential audits will, too, creating a large pool of work for future-enabled firms.

Some of this opportunity is already rising from an unexpected source: “The creators of crypto-assets actually want regulators and auditors to show up,” said Asgeirsson: They want trusted CPAs and accountants to put their seal of approval on their innovations, confirming their value for the public.

“The auditing role is not going to go away, and in the near future, it’s going to be more important than ever to help demonstrate the value in these areas,” said Quaranta.

Blockchain’s impact won’t be limited to changing the audit, though. “Internal procedures will become streamlined as blockchain-enabled ‘smart contracts’ execute automatically,” explained Greg LaFollette, a strategic advisor at CPA.com. “Both internal and external processes will be impacted as transpositions, coding errors and misclassifications fade into distant memories.”

And over the long term, he predicts both ubiquity and enormous value for the profession: “By 2027 the ‘trust protocol’ (enabled by blockchain) will be an integral part of everyday life. It will be as deeply ingrained in our personal and business lives as the Internet is today. CPAs in public practice will see huge time savings as the necessity of testing, authentication, verification and substantiation procedures are virtually eliminated. That time will allow the profession to center more on becoming the ‘trusted advisor’ that our clients want and need.”

Don't panic!

By this point, it should be clear that both AI and blockchain could radically change what the accounting profession does and how it does it, but if past technological innovations are any guide, they’re more likely to shift jobs than to eliminate them.

“Even when machines do take over an activity, that doesn’t mean that jobs don’t remain in those areas. In fact, sometimes they grow,” Baron said. “And new methods of doing traditional accounting work can bring us explosive growth.”

To participate in that growth, however, accountants will need to readjust their skill sets somewhat, and be open to new ideas, approaches and methods. Among other things, they’ll want to work on their data science skills, Katsnelson suggested

LaFollette had some simple, valuable advice for those who want to prepare for the advent of AI and blockchain: “Read. Avoid getting caught up in minutia — remember to focus on the tool, rather than the code that powers the tool. Most of us do not understand the computer code that makes spreadsheets work — nor should we. However, we do understand how to use the tool!”

He also warned against diving in without adequate preparation. “Shy away from the ‘bright, shiny object’ syndrome. Don’t chase after every new product or service that claims to be ‘blockchain’ or ‘artificial intelligence,’” he said. “Work carefully with your culture leaders and influencers to make sure your staff are fully informed that the firm is aware, studying and planning. And encourage each and every staff member to do the same.”