Industry executives and experts share their predictions for 2022. Read them in this 14th annual VMblog.com series exclusive.
2022: The AI/ML Tipping Point for Financial Planning
By Sanjay Vyas, Chief Technology Officer at Planful
After nearly two years of
unprecedented challenges for finance professionals, the coming year may finally
deliver some good news. In 2022, out of the box AI and Machine Learning (AI/ML)
solutions supporting the Office of the CFO will be more accessible and
intuitive than ever before, giving organizations the means to strategize their
futures more confidently. And in a big way.
In the world of business planning,
AI/ML can be used for everything from spotting major market trends months or
even years in advance, to fixing erroneous budget numbers throughout massive
amounts of data. While the uses for AI/ML have been unfolding for some time,
several factors will drive their broad and permanent application in 2022.
The role of the Office of the CFO has changed. Finance professionals are becoming more vital to operations than
ever, primarily because they are gaining the tools and skills to deliver deep business
insights, previously only provided by trained data scientists. It's worth
pointing out that financial data is unique in business decision-making. It
offers immense strategic understanding if one knows where to investigate. That
role is now becoming a requirement within the Office of the CFO.
Fortunately, due to advancements
in AI/ML technology planners don't need to be data scientists to uncover these
insights. Intelligent and easy-to-use technology enables finance professionals
to identify tendencies, spot anomalies in huge amounts of data, and make more
accurate forecasts--even in highly dynamic business environments. The adoption
of AI/ML will effectively expand and increase the value of FP&A far beyond
the number-crunching days of old.
It's important to note, however,
that generic AI/ML cannot be used as a bolt-on solution. Financial data
contains patterns that can only be understood by the algorithms inherent in
native, finance-optimized AI/ML. Without it, those patterns can be missed altogether.
Recent uncertainty has been a game-changer. There's no turning back from the changes wrought by the
tumultuousness experienced in the business landscape lately. Events over the
last few years have resulted in CFOs being under more pressure than ever to
deliver accurate projections to steer the business through any scenario.
Further, from the wholesale migration of enterprise platforms to the cloud to
the introduction of sophisticated collaborative tools, finance organizations
are shifting to function very differently from the way they did just a few
short years ago.
Automation has helped ease this
paradigm shift. It's much easier for highly dispersed teams to find errors and
exceptions in terabytes of information when they have intelligent tools at
their disposal. Furthermore, AI/ML can adapt over time to address data in
unique industry verticals like legal, retail, or manufacturing. The
introduction of AI/ML has actually created a virtuous cycle of innovation. As
more enterprises avail themselves of these tools and subsequently demand more
from them, the pace of enhancements and expansions is multiplying, increasing
their appeal.
AI/ML is generating new uses and new value. AI is transformative, precisely because of the incredible range
of new uses it fosters. Within Finance teams, AI/ML is accelerating workflows
and increasing collaboration; but vendors are also using the technology to
provide more tailored customer support, improve documentation searches, enable
customer forums, and much more.
It will be critical for teams to
use AI/ML in order to make high-velocity decisions by finding new ways to
automate more decisions and collect information faster. The smartest and most forward-looking
CFOs have done more than grow accustomed to the uncertainty in the business
landscape-they are evolving and growing alongside it. They have acquired the
right people, processes, and technology to accelerate decision velocity and
ensure their businesses thrive.
As finance teams become
increasingly virtual, the applications for AI/ML will continue to develop.
AI/ML, along with other technologies, will likely impact hiring patterns as
well, making hybrid and remote workers a more practical and even desirable
possibility than ever before.
Scalability and speed are increasing. AI/ML are transformative in the way they change user
expectations. In the financial world, the accuracy of analysis increases with
the amount of historical data that's available. If three years of data creates
a good plan, eight years will create an even better plan.
Data from every corner of the
business also increases value. Marketing, customer success, engineering, and
many other sources are being added, putting greater demand on AI/ML tools.
Fortunately, the platforms are keeping up; new data fabric is enabling
processing times one-tenth of where they were just a short time ago.
Decision-makers want accurate, actionable insights, and they want them now.
AI/ML tools are delivering, and that trend will only continue.
If necessity is the mother of
invention, it's little wonder there has been so much creativity these past
several years. The world has been forced to find new answers to new
problems-and finance is no exception. As a result, a new golden age for finance
is emerging, largely facilitated by AI/ML.
With luck, when finance teams look
back on 2022, they will remember it as not only a year of continued
uncertainty, but also the year their roles became more significant, incisive,
and perhaps even easier. Those will be pleasant memories indeed.
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ABOUT THE AUTHOR
SANJAY VYAS is Chief Technology Officer for Planful, the pioneer of end-to-end financial close,
consolidation, and financial planning & analysis (FP&A) cloud software.
A highly accomplished technologist, Vyas has served in engineering and software
development leadership roles at SaaS firms for nearly 25 years. He holds
multiple patents in payment authentication and analytics of unstructured data
and is the co-author of "The Cloud Security Rules: Technology Is Your Friend.
And Enemy."