Predict potential issues in the audit process by assessing and cross-correlating financial data, seeking out potential discrepancies and highlighting potential risks. Typically this would act as an initial triage approach allowing expensive audit personnel to focus on key areas and higher value tasks.

Identify high-value B2B leads by analysing internal and external data. Internal data will include CRM and sales channel data. External data might include press releases, 3rd party information sources and social media.

Breaking security systems is a growing field of study by a variety of actors - often of the malignant sort. Whether predicting PIN numbers from acoustic signals or spoofing iris images this is a race between attack and defence.

The proliferation of security systems reliant on biometric sensors creates a need for these to be stress-tested. One way of doing this is the creation of faked credentials to fool the system. Clearly there is also a potentially criminal aspect to this work.

Automate categorising documents for disclosure, for example as privileged/non-privileged, flagging them as necessary inclusions, etc.

Codifying legal expertise so that it is more widely available and understandable - potentially deployed through the medium of a text chatbot. Examples might be quick advice on potential bribery and corruption (e.g. what gifts are acceptable), employment law questions or generating NDAs.

Predict the outcomes of legal disputes and proceedings based on analysis of past case records. This can be used to drive likelihood of pre-trial settlement or, indeed, case commencement decisions.
Predict the outcomes of legal disputes and proceedings based on analysis of past case records.

Using AI techniques to automatically redact text in documents - this can potentially save considerable time otherwise requiring legal staff

Ensure that a contract does not contain hidden obligations, liabilities or other legal exposure. And also ensure compliance with increasingly complex and every changing regulations, such as IFRS.

Electronic discovery (also called e-discovery or ediscovery) is when data is sought, located, secured, and searched on a digital device or source with the intent of using it as evidence in a civil or criminal legal case. AI support can enhance this process.

Automate contract reviewing spotting errors, omissions and risks.

AI tools guide lawyers in analysing large IP portfolios and drawing insights from the content especially to protect against infringement. The acceleration of patent searches enables legal focus on the critical issues.

Legal research is the process of finding an answer to a legal question or checking for legal precedent that can be cited in a case or during a trial. Legal research can help identify if a legal issue is a "case of first impression" that lacks legal precedent.

Help manage tracking, management, and billing of time. This is a key driver of business operations at many professional service firms, especially legal organisations.

Law firms use software templates to create filled out documents based on data input from unstructured data sources

Build on feedback from residents to create optimal mood-related visual stimuli in residential or office settings. This may include support for better interior design (using associated technologies including augmented reality) but also may lead to annoying whale music.

Support 3D CAD (Computer Aided Design) software - e.g. Autodesk Dreamcatcher - to build options in to the design process. Environmental, traffic data used to help analyse potential outcomes. Architects / design staff can make educated decisions with visualised data-rich options.

Capture, collate and visualise multiple sources of data to build projected site layouts for architectural purposes. Data sources will include geo-relevant public data sources, private data sets and potentially sensor data.

Collate data from multiple sources (public, private and potentially real time sensor includng aerial or even satellite imagery) to build a clear visualisation of potential building site. Can be used to assess potential risks, visualise opportunities and project planning issues.

Analyse social, traffic data to measure potential impact of new building developments. Modeled outcomes might indicate hazards (e.g. fire evacuation risks) or design features for consideration (e.g. siting of facilities etc)