AI Use Cases 

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.

Optimise premiums and risks by granular understanding of the individuals and their propensity to claim.

Determining threshold level at which to flag compliance risks with the aim to minimise both 'false positives' and 'false negatives' both of which carry a cost

Monitor and analyse interactions with customers to flag compliance risks. This could include phone, messaging and email interactions, as well potentially as on 3rd party platforms (such as social media).

Detect potential insider trading through monitoring data flows (e.g. social media, market activity) from company insiders or close contacts.

Analyse legal documents and extract important data points and clauses - potentially to inform further workflows or simply to focus legal experts on the most relevant areas of work.

Determine whether there are patterns of activity that suggest money laundering and compliance risks. Investment in Anti Money Laundering (AML) increasingly a regulatory focus (and cost) for banks operating in international systems.

To ensure legal compliance with variosu age restrictions technology can abe used to analyse facial features and determine or predict a person's age. This can help retailers automate the selling of age-restricted items, such as alcohol or tobacco.

Determine whether a transaction should be blocked because it involves some kind of fraud (e.g. credit card, identity, etc.). Detect suspicious customer activity comparing to their normal behaviours and also to behavioural norms in their customer segment.

Analyse legal documents and prepare first draft response. This will be most deployable in circumstances of repetitive and small scale legal challenges around a constant theme.

Automated checking for GDPR compliance is a significant issue as the regulation rolls out across Europe. Minimising compliance risk and data loss whilst not investing expensive resources in checking all instances requires automated tools.

Protect communications like emails or phone conversations with advanced multilayered cryptograhy to sustain defences against hacking attacks and / or raise the alarm to ensure relevant intervention

While intended to assist the hearing impaired, this may have additioanl widespread applications. The technology must work in real-time and may be used on portable devices, which adds the challenge of limited available compute power.

Assist developers by using AI to help them accelerate code development by automatically spotting errors

Monitor application KPIs and performance for resource management to identify issues before they become widespread or too costly

Leverage speech library-SDK-APIs to quickly and cost-effectively to quickly and cost-effectively build new applications and system deployments.

Leverage image recognition library-SDK-APIs to quickly and cost-effectively build capacity and support new system deployments.

Leverage speech recognition library-SDK-APIs to quickly and cost-effectively build new applications and system deployments

Leverage deep learning library-SDK-APIs to quickly and cost-effectively build capacity and support new system deployments.

AI can be used to automate aspects of project management such as reporting, progress tracking, version control, production roll out, resource estimation, risk prediction etc

AI writes code autonomously usually within set parameters to enable rapid scaling of new applications and tools

Leverage Natural Language Processing library-SDK-APIs to quickly and cost-effectively build new applications and system deployments.

Automate testing of web applications and apps as part of continuous development - opportunities include ensuring less downtime and continued business improvement as well as potentially A/B testing at scale

Knowledge management systems can be configured to predict and provide relevant information at an apporpriate moment based on different indicators such as calendar or other contextual information. This has the potential to signifciantly improve user efficiency and effectiveness - and occasioanlly disorientation (although typically such a feature can be disabled in standard software configurations).

Network packets must be correctly identified and routed in order to maintain network functionality including controlling traffic flow, operationalising firewalls, and measuring networks.

Personalise screens, reports and dashboards for IT development team members depending on the role - different functions will receive information optimised to their needs.

Frequently, currently in parallel with human QA team software is tested pre-launch for potential issues - especially where it might have an impact on other software in the stack. The AI enables a wider variety of relationships to be tested than humans alone can perform, frequently at a far faster rate.

Minimisation of compute resources to achieve low latency and reduced energy usage. This will be a critical of growing Edge computing applications.

Synthetic datasets is a way for researchers to train machine learning programs when sufficient real-world data is unavailable, difficult to obtain, or raises ethical or privacy concerns. Certain use cases for AI lend themselves better to synthetic datasets than others.