Expert Witness Journal Issue 64 December 2025 - Flipbook - Page 87
parties and legislators adopt AI arbitration remains
unclear, not least because doubts must exist as
to the enforceability of AI-written awards, given
legislation in several jurisdictions which expressly11
or impliedly,12 13 requires an arbitrator to be a person,
i.e., a human.
key documents can be analysed for an assessment of
the likely strengths and weaknesses of various case
strategies. Where parties use a legally trained AI
database which has been trained to understand the
concept of legal precedent, the ability to use AI to
stress-test legal arguments may be an invaluable tool
in helping a party to decide whether it is worthwhile
pursuing a matter to arbitration or whether it
is better to seek a commercial solution through
negotiation or alternative dispute resolution.
There are huge opportunities with AI; there is a lot it
can help lawyers do better. As much as practitioners
need to invest in the right tools, however, they
must also invest in the people that will be using
them, encouraging them to incorporate AI into
their practices in a way that is not only appropriate,
e昀케cient and innovative, but that is also ethical and
meets the high standards required by the legal
profession. Any lawyer utilising AI must be conscious
of the quality of both the input and the output, as
well as the limitations of the platforms. The risks in
AI can be enormous, whether the cause be negligent
or malicious.
This model of predictive analytics has been embraced
by the International Chamber of Commerce (ICC)
and the Permanent Court of Arbitration as being
of assistance to parties in coming up with the
most e昀昀ective legal strategies.16 17 18 In construction
disputes, the American Society of Civil Engineers in
2023 tested the ability of AI to analyse and predict the
outcomes of disputes that had already been decided
in adjudication and concluded that the AI predicted
the real result with 95% accuracy.19 Such a use for AI
can help clients who wish to consider their position
before approaching external counsel; however, there
is a limit to the reliability of the (albeit evidencebased) output of AI given constraints in precedent
ingestion and the unpredictability of opposing
counsel’s arguments. The authors therefore doubt
whether AI can ever truly substitute the judgment
and experience of expert counsel when evaluating
the likelihood of success of a case.
Here we discuss both the opportunities and risks
for the international arbitration community as it
embraces AI. The message is clear: while technology
may revolutionise how we conduct disputes, the
revolution only works if the people using the tools
know what they are doing.
Opportunity
LLMs are ideal tools for the complex tasks required
of them by international arbitration:
•
First, the training of the model gives it an
incredibly powerful frame of reference to draw
from when answering queries. When the generic
training data is paired with legal-speci昀椀c
data, the resulting products can be extremely
valuable.14
•
The ability to ingest and analyse large amounts
of data quickly makes AI tools an incredibly
powerful means of increasing e昀케ciency, doing
what would take a human reviewer hours
or more in a matter of minutes in a more
predictable way.15
Arbitrator selection is a natural extension of this use
case for AI in arbitration. AI solutions may provide
parties with the ability to research in depth the
candidates for appointment in their disputes. AI
may be able to collate information on an arbitrator’s
previous awards or decisions—if those can be fed
into a database—and it will also be able to search
online for any public comments or publications that
an arbitrator may have made on a particular issue.
Such intelligence will allow parties to consider both
their likely chance of success with an individual
candidate. It will help parties to identify the
arguments that might be likely to hold sway with a
particular arbitrator and the likelihood of achieving
a successful damages award based on the available
facts and information.20 21 22 23 24
AI has the potential to revolutionise all parts of the
international arbitration life cycle and the work of
practitioners, experts and tribunals alike. It will
allow participants to complete tasks at all stages
of a case with greater e昀케ciency and accuracy,
昀椀nding added value whilst also reducing the cost
of individual actions. Many of the issues that have
been identi昀椀ed by the arbitration community can
be in part addressed by AI. The following are a few
of the areas where AI can support international
arbitration.
The key limitation of AI-assisted predictive analytics
is the volume and quality of the data that it is using to
make its predictions. One obvious restriction is the
limit on the number of awards that an LLM might
be able to review for the purposes of populating its
database as to the decision-making of an arbitrator.
An attraction of commercial arbitration is its
privacy and con昀椀dentiality, with many awards not
being published. Of major institutions, only ICSID
publishes full awards, with others including the
ICC, ICDR, LCIA and SIAC publishing only limited,
redacted or summarised awards.25 The disclosure
of information regarding awards, including the
names of arbitrators, experts and counsel, raises
Predictive analytics
When a dispute is contemplated, a client may wish to
consider its position and its prospects of succeeding
if the matter were to proceed to arbitration. Using AI,
EXPERT WITNESS JOURNAL
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DECEMBER/JANUARY 2025-2026
