Automating the collection of customer data including product preferences, demographics, and personal information. This data may be collected under the guise of a loyalty program or app, with AI being used to extract the relevant information.

Consider automation of delivery and other transportation cases through drones and other automated vehicles

Automate generation of articles - for example using national data sets and then producing local variant articles from this. The same can be done for press releases.

Optimise release dates and location targeting for film (or movie) launch rollouts. Typically this will involve analysing consumer data such as social media traffic and search patterns to ascertain interest and 'word of mouth' on the product.

Taking a 2D image this technique allows for the creation of a 3D model of the objects captured in the photos. This obviouasly works better on images of objects with known characteristics - like humans for example.

Building subscriber income is a key part of many media publisher strategies - especially as print disappears, online advertising pricing pressure increases and 3rd party traffic generators like social media sites or search engines change their algorithms at will. Whilst these conversion rates are typically in low single percentage points any increase can drive significant revenue to the bottom line. Typically the models will score customer propensity to respond to different types of advertising and commercial propositions, perhaps at different times, and offer these up accordingly. For many sites this will also drive the cut-off moment for free access. This is a shift to a more flexible variant on traditional Freemium (some content is free, some paid for), Metered (a certain amount is free) or Hard (everything is charged for) models.

In the race between online marketers and people keen to avoid being marketed to neural networks have been deployed to subvert ad blocking software (by, for example, working out which images might avoid being blocked). Ad blocking software has increasingly deep penetration amongst consumers which poses a challenge to online publishers. Subverting ad blockers is unlikely to be the last lap in this particular race.

Based on customer's media interests and viewing history, automate the creation of the media image (e.g. from a movie) that is most likely to drive click-through to the media product - although the technique has wider uses in optimising the purchase funnel in ecommerce.

Optimise pricing for services or product offerings based on customer-specific data. This may include previous purchase decisions or wider data accessed from 3rd parties.

Automate generation of conversational media content for audio driven interactive programming on conversational platforms (e.g. Alexa). This is for entertainment purposes.

Identify pertinent features like copyright infringement or audience age suitability in media content. This will support deployment of control tools (eg deletion) especially on high volume video viewing sites.

Use customer behaviour pattern data to predict and recommend media content that customers will want to consume. This may be further optimised to business imperative - for example what will enhance likelihood of subscription renewal rather than instantaneous gratification.

Using AI to automatically classify businesses for inclusion in a corporate listing database. Key financial and business data will be categorised at the same time. This may be an initial step in building an investment process where other steps may also be automated (potentially with AI).

Software which automates the work of human moderators to identify abuse and misconduct in online messages between video game players on community boards.

Generate research for news content - stories may emphasise AI (negatively or positively) or simply be data journalism on large data sets

Being a news anchor involves the single task of reporting - essentially reading out a script. Therefore, AI can work for automating news presentation on TV and other media, using natural language generation and processing.

Companies use AI to automatically flag and remove user content on social media and other platforms which violates regulations and government mandates

Successful social media sites tend to have more content available for users than all but the most addicted (and socially restricted) could possibly read. This means that they have to use multiple indicators to power the algorithms that rank the content displayed. In this they are in a constant battle to stay one step ahead of the content marketeers trying to game the system.

In a world where information is at anyone's fingertips plagiarism is a constant challenge, especially in academic circles. NLP can be used to match content and identify suspect material.

Discover new trends in consumption patterns (e.g., viral content). Increasingly this sort of data-driven approach is driving editorial decisions - potentially to the detriment of risk-taking originality.

Personalise advertising and recommendations to target individual consumers. This might be based on a wide spectrum of data (mobile, social media, location, etc.) but much will be based on website analytics and tracking widget deployment.

Autogenerate captioning on video or audio files. This speech to text service potentially saves significant human effort but will work less well in languages that have not yet had the full research effort of - say - English and Chinese, where error rates remain a challenge.

Improving audio quality - for example by eliminating background noise or static - has numerous follow-on applications: helping deliver better outcomes from translation or hearing impairement support devices, delivering cleaner data for NLP products and providing better consumer experiences.

Predict viewership for new content to optimise editorial investment decisions. The focus may be on single items of content or wider strategic approaches to content generation.

Use communication data - written and spoken - to construct a digital personality for ongoing remote interaction. Whilst largely a gimmick at this stage - able to capture tone of interactive style but little of any underlying thought processes - the potential for building out artificial constructs of departed loved ones, or simulacra of advisers or leaders may soon no longer be simply in the realm of science fiction.

AI is used to generate the computer game experience - building larger worlds and ever more impressive challenges for gamers.

Detect potentially dangerous electrical current surges. This potentially enables systems and devices to automatically react in an appropriate fashion to minimise risk to users and devices.

Identify vermin and propose appropriate treatment approach - for example this can be deployed as an app using Google's image classification

Predict and promote the next appropriate offer for a customer to maximise chance of driving desired behaviour (e.g. sales, click-through, retention offer acceptance etc).

Customer response to warranties generates a lot of data that can be mined to predict potential specific quality issues and to predict risk across the product portfolio.