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Across the board, AI adoption is on the rise. A
recent EY survey of US CEOs and business leaders found that most
senior enterprise decisionmakers (85%) classify themselves as artificial
intelligence optimists, while the financial services industry in particular is
benefiting significantly from an uptick in AI adoption.
One area of
financial services quietly undergoing a revolution in AI and automation is tax and
accounting. To gain a better understanding of how AI is being used in tax
today, we sat down with Charles Brayne and Harvey Lewis from EY. Charles is
EY’s UK Chief Tax Innovation Officer and Partner and has a dual role. On the
one hand, he works with clients to help them adopt new tax technologies and on
the other, he oversees the implementation of AI technologies within EY’s own
tax business. Meanwhile, as EY’s UK Chief Tax Data Scientist, Harvey works
directly with tax and law professionals to create and deliver new AI tools and
applications, as well as provide strategic oversight for their automation
tax is enormously complicated in so many ways, it’s also very systematic and
logical. We’ve found that a lot of what we do is enormously susceptible to
being performed in a very different way using various branches of AI, such as pattern-based
machine learning, Natural Language Processing (NLP) and Natural Language
Generation (NLG), all of which we’re investing in heavily. In all likelihood what
we do as tax professionals will be fundamentally transformed in the next 3-5
C: A lot of
the routine work in tax is around compliance, data cleansing and data
processing; being able to identify risks and anomalies, and produce returns. We
are now starting to use technology to deliver this work in a fundamentally
different way. People are going to be using a range of technologies to produce
those outputs. You could see fewer people doing tax compliance and accounting
in future because so much of it will be driven by technology, or at the very
least, those people will have more time to focus on the outputs of that work
and what it means for the business.
H: For me, there are two primary benefits for AI in tax. The
first is that it allows you to deliver old services in new ways. If you think
about some of the conventional tax or law-related services that organisations
provide, AI can make them much more efficient by orders of magnitude.
The second is that entirely new services are possible when
you apply these technologies. We can look at the data and tasks that we perform
and apply AI to enable something very different, so whether that’s screening
new information sources for changes in tax legislation or helping tax
professionals complete interviews with engineers claiming R&D tax credits.
There’s a wide range of applications for these technologies that allow us to go
much wider and deeper into these services.
isn’t just about tax professionals, but tax authorities as well. We are
starting to see fiscal authorities invest in these technologies to analyse
large volumes of data, make sense of it, and to understand where the tax
revenue may be falling short. The UK as well as fiscal authorities around the
world are investing very heavily in technology to support new ways of
implementing enforcement and collection mechanisms, using more data sources
than ever before. So actually, the technology is starting to change the very
nature of tax compliance regimes around the world.
aspect is that forward-thinking finance leaders are recognising that what we
used to think of as tax compliance processes are really finance processes at
heart, because a lot of this classification and categorisation work can be done
by a finance professional using the right technology. This is leading to quite
a profound reshaping of the relationship between the tax and finance function,
including a fresh look at where tax professionals should be focusing their
attention in order to add the most value.
challenge here isn’t about starting – it’s about sustaining. I think it’s
relatively easy to start: you can define a set of use cases, you can find some
technology, and you can start the process. It’s much harder to sustain that and
scale it across the business. You will have to start with the right use cases –
those that really add value. For the clients we work with, picking on a
“difficult” use case such as the way the tax department delivers compliance,
then demonstrating that an AI-driven approach can be scaled globally has been
very powerful. The key is to have sustainability in mind from the outset. With
cloud and server-based infrastructure, you can scale very rapidly, so the way
in which you implement the technology is really important for the way you can
sustain growth across the business.
Catch Charles and Harvey's keynote, 'Lessons from implementing AI in a people business', at 09:30 on the Implement stage at The AI Summit London, June 13. Find out more