Over the next decade, the development of artificial intelligence — and, specifically, deep-learning AI — will start to enable us to work more closely with technology.
Whether it is the assessment or purchase of a product or service, or carrying out desk research, it is likely that the first party that we turn to for collaboration will be made of silicon, not skin and bone.
Kevin Kelly, the founding editor of Wired, has said that the AI on the horizon looks more like Amazon Web Services — cheap, reliable, industrial-grade digital smartness running behind everything, and almost invisible except when it blinks off. This common utility will serve you as much IQ as you want but no more than you need.
IBM has just gone live with its AI service called Watson, which, among other things, can act as a collaborator for doctors — advising them on the likely condition based on the reported symptoms; the accuracy levels are far higher than that of the average physician. The legal industry now has a similar AI collaborator helping lawyers.
The question — a matter of when, not if — is how long before AI collaboration enters the marketing space? Imagine, for example, having a guiding voice shaping the marketing and media strategy based on all historical evidence and case studies. This is a more difficult task than that of symptom-to-diagnosis linking, but not beyond the scope of what is imaginable. But there are, arguably, greater AI implications that may ripple up on to the shores of advertising and marketing. With the exponential increase of AI, people are likely to start to rely more on their AI-driven virtual personal assistants for advice on what to buy. In essence, they will start to outsource their decision-making to an algorithm.
We can see glimpses of what the future may hold in today’s VPAs, such as Apple Siri, Google Now and Microsoft Cortana. Although presently very weak, these services already help consumers find information about brands and products, and soon they will automate even more of our lives. As they increase in power (the next iOS update from Apple is rumoured to include some significant upgrades to Siri), they will create new challenges and opportunities for brands as they learn to adapt to the future of AI-enabled marketing.
If the VPA is going to be the ultimate collaborator for people as they navigate their waking worlds, it is important for the VPA to have access to the world of information — and that it is ontologically structured so that it can understand relationships between things. This requires all information about products to be readily accessible so that the deep-learning algorithms of tomorrow can "see" the world. This means, for example, all the products in a grocery retailer will have their product information read and understood — not just name and price but also the essential ingredients, where they were produced and under what environmental and ethical conditions, and how far it was shipped, so that our VPAs can make informed decisions on our behalf.
From this position, our VPAs will know everything. Every ingredient, every location, every price, every possible way of booking, cancelling and amending. They will also have API links to booking engines and, of course, our diaries. Our VPAs will then not just be able to recommend, they will be able to make informed decisions on our behalf, based on what they know about us and when products are likely to have been used up or simply in need of replacement. Eventually, they will make purchase decisions for us, especially for low-interest items where there is little difference between brands.
Instead of marketing directly to the prefrontal cortex, marketers will have to market to algorithms. Maintaining positive brand sentiment will be crucial. Feedback from people — through overheard conversations (text or voice) — will be one of the most important signals that this increasingly sentient-seeming VPA will look to when deciding whether to recommend a product to you. This may also include machine-generated information from Internet of Things devices that are able to assess ingredients (for example, a washing machine that can assess detergent performance).
Even if only half of this comes to fruition, it is increasingly clear that AI-driven collaboration has the potential to radically enhance and reorganise how we work.
Mark Holden is the worldwide strategy and planning director at PHD.
