28
Want to Innovate?
How's Your Data?
B Y C H R I S T O P H E R Z E G E R S
A
s we turn the corner into
2020, firms are competing
to distinguish themselves as
innovative partners to their clients. For many,
this means they are focusing on innovative
service delivery models
1
, one of the four
key areas ripe for innovation (and which
also includes cost, product and channel
innovation).
2
For law firms in particular,
service innovation means creating more
flexible leverage models and more creative
pricing, leveraging technolo to streamline
operations, focus on client and practice
profitability, and more targeted business
development.
These are ripe use cases for AI — and
why it may seem on the surface that firms are
rushing to implement AI. However, a recent
report from Gartner shows that AI adoption
is stymied — deployment is actually less than
last year, with the total percentage of CIOs
saying their companies have deployed AI at
19%, but lower than the 23% of companies
that thought they could roll out AI by now.
That's because data quality and
governance are our biggest challenges to
innovation in general as well as specifically to
the adoption and implementation of artificial
intelligence. The leading reason for stymied
adoption is data quality and governance
which, according to the report, comprise
nearly half of the maturity challenges to
adoption.
Data Quality Stymies Innovation
Our technolo has always been a bit behind
the curve when it comes to managing data
and we have always required manual
steps inserted to fill key gaps-- but now the
sheer volume of data itself, combined with
the proliferation of unstructured data is
simply staggering and render obsolete any
process that requires manual input. This is
yet another argument in favor of advanced
technologies such as artificial intelligence.
