From using motion capture tech to allow the Indian cricketing star Rahul Dravid to give personalised coaching tips for children to an algorithm trained on Shakespeare's handwriting powering a robotic arm to rewrite Romeo and Juliet, artificial intelligence is rapidly revolutionising the global advertising industry. Those AI-created adverts, for the Cadbury's drink brand Bournvita and the pen maker Bic, were produced by agency group WPP, which is spending 300m annually on data, tech and machine learning to remain competitive. Mark Read, the chief executive of the London-listed marketing services group, has said AI is "fundamental" to the future of its business, while admitting that it will drastically reshape the ad industry workforce. Now Read has announced he is to leave at the end of this year, after almost seven years as chief executive and more than 30 at WPP, as the company struggles to keep pace with its peers and also counter moves by big tech to muscle in to the AI-driven future of advertising. For ad agencies, the upheaval originates from a familiar source.

Wind power producers (WPPs) participating in short-term power markets face significant imbalance costs due to their non-dispatchable and variable production. While some WPPs have a large enough market share to influence prices with their bidding decisions, existing optimal bidding methods rarely account for this aspect. Price-maker approaches typically model bidding as a bilevel optimization problem, but these methods require complex market models, estimating other participants' actions, and are computationally demanding. To address these challenges, we propose an online learning algorithm that leverages contextual information to optimize WPP bids in the price-maker setting. We formulate the strategic bidding problem as a contextual multi-armed bandit, ensuring provable regret minimization. The algorithm's performance is evaluated against various benchmark strategies using a numerical simulation of the German day-ahead and real-time markets.

Forecast reconciliation is considered an effective method for achieving coherence and improving forecast accuracy. However, the value of reconciled forecasts in downstream decision-making tasks has been mostly overlooked. In a multi-agent setup with heterogeneous loss functions, this oversight may lead to unfair outcomes, hence resulting in conflicts during the reconciliation process. To address this, we propose a value-oriented forecast reconciliation approach that focuses on the forecast value for individual agents. Fairness is ensured through the use of a Nash bargaining framework. Specifically, we model this problem as a cooperative bargaining game, where each agent aims to optimize their own gain while contributing to the overall reconciliation process. We then present a primal-dual algorithm for parameter estimation based on empirical risk minimization. From an application perspective, we consider an aggregated wind energy trading problem, where profits are distributed using a weighted allocation rule. We demonstrate the effectiveness of our approach through several numerical experiments, showing that it consistently results in increased profits for all agents involved.

The head of the world's biggest advertising group was the target of an elaborate deepfake scam that involved an artificial intelligence voice clone. The CEO of WPP, Mark Read, detailed the attempted fraud in a recent email to leadership, warning others at the company to look out for calls claiming to be from top executives. Fraudsters created a WhatsApp account with a publicly available image of Read and used it to set up a Microsoft Teams meeting that appeared to be with him and another senior WPP executive, according to the email obtained by the Guardian. During the meeting, the imposters deployed a voice clone of the executive as well as YouTube footage of them. The scammers impersonated Read off-camera using the meeting's chat window.

WPP is the transformation company. We use the power of creativity to build better futures for our people, planet, clients, and communities. Working at WPP means being part of a global network of more than 100,000 accomplished people in 110 countries. We create transformative ideas and outcomes for its clients through an integrated offer of communications, experience, commerce, and technology. WPP and our award-winning agencies work with most of the world's biggest companies and organisations – from Ford, Unilever and P&G to Google, HSBC, and the UN.

Artificial intelligence is bringing profound transformation across the media and communications industry. It already forms a huge part of how content is delivered, as algorithms work to understand our behaviours and preferences. These insights are hugely valuable in understanding consumers and making communications more effective but can also pose their own challenges. "The digital advertising market is worth about $350 billion a year and growing," says Perry Nightingale, head of creative AI at creative transformation company WPP. "And we already see a lot of AI, particularly on the targeting side. Algorithms are constantly working around us to recommend the next piece of content to consume. But because of the way those algorithms work, we have to make a huge amount of content before they become effective. We need hundreds and hundreds of variations of an advert before it becomes worthwhile to split them up and show to different people, which all need to be created in the same amount of time and for the same cost."

This month, advertising giant WPP will send unusual corporate training videos to tens of thousands of employees worldwide. A presenter will speak in the recipient's language and address them by name, while explaining some basic concepts in artificial intelligence. The videos themselves will be powerful demonstrations of what AI can do: The face, and the words it speaks, will be synthesized by software. WPP doesn't bill them as such, but its synthetic training videos might be called deepfakes, a loose term applied to images or videos generated using AI that look real. Although best known as tools of harassment, porn, or duplicity, image-generating AI is now being used by major corporations for such anodyne purposes as corporate training.

Last month, WPP, the holding company for multiple agencies and networks including Oglivy, GroupM and Kantar, released its annual results for 2019. The company put forth a number of objectives across various business units, but one line especially caught our eye: "In the next two years, we plan to train 50,000 people to be able to articulate the power of artificial intelligence and its value to clients, and to accredit 5,000 data scientists, engineers and creative technologists in the key marketing technologies." Training a full staff on AI is no easy task, but to undertake an initiative to train 50,000 people is something that takes enormous coordination. "Our AI skills development program is very exciting and spans executive education," said WPP's CTO Stephan Pretorius. To make its AI training goals a reality, WPP is currently developing a graduate diploma with Oxford Saïd Business School and rolling out a data science academy created in partnership with General Assembly.