2022 has been the year AI came to the fore. In an article entitled “From Prediction to Transformation” in Harvard Business Review, Ajay Agrawal, Joshua Gans and Avi Goldfarb write:
In some cases, AI simply concentrates decision-making without changing who has control. Look at the hiring process, which in most large organizations is managed by the human resources department. Traditionally, hiring has involved a great many HR people who make a lot of small decisions, especially about screening applicants, which can require teams of people looking through hundreds of résumés in order to identify promising candidates to interview. Thanks to AI, one HR executive can decide what criteria to use to decide who gets an interview. The basic process and the key decision-maker remain the same, but fewer people are needed.
In other cases, AI radically centralizes decision-making, completely changing how and where it happens. Credit card verification is a case in point. Before the rollout of connected devices that automatically validate cards, merchants would make their own judgments about whether to accept someone’s card. They could reject it if they suspected fraud—for instance, if someone’s signature didn’t match the one on the card or a customer didn’t have supporting ID. And they could readily accept cards from regular customers. But systems driven first by crude database checks and now by AI prediction have automated the process. Credit card purchases are approved according to rules set by a small group of people, most likely a committee, which creates the risk parameters embedded in the programs that run verification devices.
In marketing, AI has already started having an impact – predicting segments to send campaigns, predicting churn, predicting next best actions for customers, helping with subject line optimization and send-time optimisation (for emails). Generative AI is already helping marketers create content and images.
So far, marketers have worked largely on first-party data. With zero-party data, the data models can get even stronger, and help marketers address the most important problem of the next best action for customers. We are delighted when we get an email recommendation or see a product that preempts and piques our interest – the next book to buy, the next web series to watch, the next dress to check out, the next destination to vacation in. Marketers have so far relied on signals from user actions (search terms, links clicked). Once this can be augmented by zero-party data where customers can tell them what they are looking for in natural language or even interactively via a chatbot conversation, the accuracy of predictions can be multiplied – thus creating more transactions and loyalty.
In 2022, we have seen what GPT3 can do. Rob Toews outlines in Forbes what its successor will be capable of: “It is possible that GPT-4 will be multimodal: that is, that it will be able to work with images, videos and other data modalities in addition to text. This would mean, for example, that it could take a text prompt as input and produce an image (like DALL-E does); or take a video as input and answer questions about it via text. A multimodal GPT-4 would be a bombshell. More likely, however, GPT-4 will be a text-only model (like the previous GPT models) whose performance on language tasks will redefine the state of the art. What will this look like, specifically? Two language areas in which GPT-4 may demonstrate astonishing leaps in performance are memory (the ability to retain and refer back to information from previous conversations) and summarization (the ability to distill a large body of text to its essential elements).”
Predictions follow naturally from implementing a Martech 2.0 unified stack and aggregating zero- and first-party data in a single customer data platform. Think of the memorable experiences we have had where an intelligent salesperson in a store guides us to exactly the product we want. Tomorrow’s AI-powered virtual agents will have a “digital twin” for each of us, and software agents will engage us in conversation, predict our next actions, and end us just-in-time alerts. Powered by rapidly improving AI engines, 2023 will be the year this new customer-centric world will start coming to life all around us.