Artificial intelligence (AI) adds efficiency to any number of marketing applications, from content to conversational chatbots. For organizations looking to harness these capabilities, here are some ways to get started. "You do not, and should not, try to create this yourself in-house from scratch," said Jim Lecinski, clinical associate professor of marketing at Northwestern University at The MarTech Conference. One important way AI can boost marketing functions is helping the team make better predictions instead of singling out campaign targets and goals "by hand." "We've all sat in conference rooms for years and made decisions based on staring at cells in a spreadsheet," said Lecinski.

At many firms, the marketing function is rapidly embracing artificial intelligence. But in order to fully realize the technology's enormous potential, chief marketing officers must understand the various types of applications--and how they might evolve. Classifying AI by its intelligence level (whether it is simple task automation or uses advanced machine learning) and structure (whether it is a stand-alone application or is integrated into larger platforms) can help firms plan which technologies to pursue and when. Companies should take a stepped approach, starting with rule-based, stand-alone applications that help employees make better decisions, and over time deploying more-sophisticated and integrated AI systems in customer-facing situations. Of all a company's functions, marketing has perhaps the most to gain from artificial intelligence.

A lack of artificial intelligence and machine learning usage in digital marketing is causing a significant issue for marketers looking to deliver personalised experiences to customers, according to Gartner. In its new report, the analyst firm revealed that almost two-thirds (63%) of digital marketers struggle with this issue, from a survey of 350 marketing leaders from November 2020 through December 2020. One of the main problems is that digital marketing leaders are scaling their use of AI and ML to align with customer retention and acquisition goals rather than across the marketing function. This contrasts with another statistic: 84% of digital marketing leaders believe using AI/ML enhances the marketing function's ability to deliver real-time, personalised experiences to customers. Gartner says many digital marketers believe bringing automation, scale and efficiency to marketing activities across channels is the greatest value of AI/ML tools. "A comprehensive personalisation strategy and roadmap can be deciding factors in the results marketers achieve from their personalisation efforts, yet most marketing organisations lack an effective personalisation strategy – let alone one that is explicitly linked to desired business and customer goals," says Gartner for Marketers vice president analyst Noah Elkin.

Imagine a future in which a smart marketing machine can predict the needs and habits of individual consumers and the dynamics of competitors across industries and markets. This device would collect data to answer strategic questions, guide managerial decisions, and enable marketers to quickly test how new products or services would perform at various prices or with different characteristics. The machine learning algorithms that might power such a device are, at least for now, incapable of producing such promising results. According to a group of researchers, the envisioned "virtual market" machine could become a reality but would still require one missing ingredient: a soul. The "soul" is our human intuition, scientific expertise, awareness of customer preferences, and industry knowledge--all capabilities that machines lack and intelligent marketing decisions require.

This intelligent machine would collect the data it needs to answer strategic questions and guide managerial decisions.

Marketers have traditionally embraced new technology, finding ways to apply it in creative ways. Though artificial intelligence (AI) is the latest example of innovative technology, it is fundamentally different in that its potential effect on the overall marketing function is transformative. AI shows great promise, and marketers are still learning how to use it effectively and integrate it with, or use it to complement, the processes they're already using. A similar trial-and-error effort took place during the early days of the Web, when companies were experimenting with how to use it as its capabilities evolved. AI will likely significantly re-shape parts of the marketing function as it evolves and as organizations find new ways to apply it.

Marketers have traditionally embraced new technology, finding ways to apply it in creative ways. Though artificial intelligence (AI) is the latest example of innovative technology, it is fundamentally different in that its potential effect on the overall marketing function is transformative. AI shows great promise, and marketers are still learning how to use it effectively and integrate it with, or use it to complement, the processes they're already using. A similar trial-and-error effort took place during the early days of the Web, when companies were experimenting with how to use it as its capabilities evolved. AI will likely significantly re-shape parts of the marketing function as it evolves and as organizations find new ways to apply it.

One of my favorite topics to discuss with other marketers is how both the art and science of marketing are changing. While the design and creativity of marketing is very exciting to me -- new interactive ways of creating and producing content, in this article I want to focus on the science of marketing -- the techniques used behind the scenes to improve marketing results for organizations. Specifically, I would like to focus on how machine learning intersects with the marketing function. Machine learning, as a technique, involves predictive and prescriptive techniques of data analysis to identify patterns and detect behaviors. The massive data volumes that are accessible to marketers -- whether Instagram or Twitter activity data, vehicle or device data, home automation data, or even spending and transaction data -- is data that can be collected and used for marketing purposes.

There is no question about it, artificial intelligence is changing how customers interact with brands and develop through the buyer journey. For many customers interacting with AI has become the norm, whether they realise it or not. As artificial intelligence continues to develop businesses are implementing it more across their digital marketing platforms. Chatbots are massively changing the way the consumer communicates with a business. Chatbots are becoming the norm on social media for many businesses and can help with a major part of the customer journey.

Business-to-consumer (B2C) businesses have made it a priority to incorporate machine learning into customer-facing functions, integrating it into sales and marketing. For business-to-business (B2B) companies, however, translating data into actionable marketing strategies can be a more difficult proposition. Selling to organizations invariably requires embarking on a much longer and more complex journey, culminating in an order of much higher value than in the consumer realm. With hundreds of thousands, if not millions, of dollars at stake, a misguided marketing investment could lead to financial losses. "The availability of data and the importance of having the focus on the full customer journey is coming a little later to the B2B world," says Laura Beaudin, a partner at Bain & Co. "A lot of expectations in terms of customers manifested themselves in the consumer world before they brought those expectations to their business-purchasing world."