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The impact of machine learning & AI on advertising in a privacy compliant age


Sian Williams, Audience Strategy and Planning Director at MediaCom North, explains how AI offers a future of increased automation, faster decision-making and ‘hyper-personalisation’ that will make marketing comms more effective and businesses more efficient.

Robots are science fact not fiction, machines may well inherit the earth, and artificial intelligence can actually enhance the way we engage with human intelligence.

As more interactions become digitised, the data landscape is only getting bigger and AI, and within it machine learning, will increasingly fuel that growth. The two terms are often used inter-changeably but whilst AI creates the structure of computational human intelligence it is machine learning that, sans specific programming, delivers on how quickly and effectively data will be processed and decisioned against. If AI is the brain itself, full of raw potential, then machine learning is at least one of the ‘cortexes’ able to process information and develop intelligence and skill by using one ‘experience’ to inform another.

AI as a whole has been creeping up on us for a long time – we use it every day, both knowingly and unknowingly, as we do very normal, mundane things: opening our phone, reading our social newsfeed, as we search, as we shop, as we travel, as we desperately seek for something we haven’t already watched on Netflix. It is increasingly woven into the fabric of our everyday lives, constantly processing increasingly vast amounts of data to determine the best outcome, best message and offer the best experience (or at least try to).

AI-led consumer solutions are adding to the range of touchpoints a marketer has to think about. Voice assistants like Alexa and Siri may not have become as indispensable as anticipated but it’s worth being cognizant that perhaps we’re not really that far off having to worry about soft drink recommendations being made by the smart fridge. Certainly these touchpoints are playing a larger and more normalised role within the brand ecosystem – chat bots on social/within apps are helping business bridge the gap in areas where human interaction cannot be scaled efficiently or effectively by using AI to solve common problems or filtering queries to the right place. In a very real and scalable way AI is now a representation of the brand voice and defining a core part of the brand experience.

Perhaps the biggest impact lies in the act of anticipation – being able to process data from a customer or consumer profile to accurately predict what they want before they even consciously know it themselves. The principle of this has been in place for a long time with digital first businesses like Amazon and ASOS long using behavioural data and tech to inform the next decision in product and comms. Within the realm of analytics AI is enabling us to make communications smarter based, not only on predictive outcomes, but also ‘prescriptive’ ones where we can essentially scenario plan to impact it. Emerging AI software is taking this to the next level – a state of ‘hyper personalisation’ based on increasingly sophisticated learning against an ever-growing base of interactions and purchase behaviours. Arguably the only limit to this is the speed and scale at which we can capture good quality data to feed the beast.

In the advertising world AI has really been core to business success and innovation for a while – AI powered programmatic is our reality now. Amongst others, Google, Facebook and Amazon are continuing to pioneer their products based on increasingly sophisticated capability. From an agency perspective, algorithms can be customised based on a client’s specific priorities to drive more meaningful programmatic performance.  For advertisers AI and machine learning enables us to process more information at a larger scale – faster decision-making across micro details that may not be discernible to the human eye. The faster and more accurately we can identify, categorise, and predict, the more relevant, timely, and persuasive we can make our communications.

AI is also playing a central role in the road to automation, helping lighten the load in terms of regulating, and measuring, for example, auditing account set ups and bridging the measurement gap by running informed models for outcomes and impacts. It will play a crucial role in the way we govern data in the first place by regulating quality and security. Quite simply, used well it has the power to make our marketing communications better and our business operations more efficient.

The growth of AI isn’t, however, going to make our world any less complex. AI is not immune to the over-arching challenges of privacy and the scrutiny that comes with data regulation. The potential of intelligent, scalable targeting that is also anonymised through predictive modelling is key as we find our way in the mist of the post-Privacy era but the increased ability to manipulate and influence, especially when that AI is operating based on a ‘known’ record, is more questionable. AI as a whole certainly isn’t exempt from privacy concerns – live facial recognition tech, for example, has been in question for a long time with many voicing concerns over state surveillance and becoming a ‘walking ID card’.

Governments and regulatory bodies have turned their attention to assessing the potential vulnerabilities of AI based programs. It looks like there will ultimately be development of agreed standards for the development and utilisation of AI but within that there’s also a job to do to fully understand the impact of bias in data and algorithms and how it can monitored and measured to  diminish any negative impact. We don’t want the all-consuming data beast to turn into a socio-politically insidious monster, although arguably based on the various controversies of the last few years that particular monster may have already bolted from its troll-pit.

From an advertiser’s perspective then, the way forward is going to get both easier and harder as AI is used to solve for ever more sophisticated use cases such as mass personalisation. At the very least we’ll need to work to ensure we have the ‘right’ data inputs, the right rules to sort and process that data at scale and the connection to creative automation to match with speed and relevance. All of this needs to be done with a sharp lens of ethics and compliance.

It’s not easy but with a clear view of your audience, data and tech strategy it can be built – the right person may actually see the right message at the right time – and AI done right, based on quality information and respect for the consumer, could actually be a means to making our marketing if not more human, then at least more humanistic.

Sian Williams is Audience Strategy and Planning Director at MediaCom North

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