The marketing industry stands on the threshold of perhaps its biggest transformation since the introduction of database marketing in the 1970s. With today’s AI tools marketers are now able to bridge the gap between the vast amounts of data companies have collected and leverage these assets to define and execute effective optimized “one-to-one" personalized marketing at scale.
According to the 2018 Accenture-Microsoft AI Marketing Survey, 80 percent of marketing executives believe AI will have a significant impact on the marketing role by 2020,1 and 64 percent believe AI will become fundamental to marketing within the next three years.
What marketing expects from AI
84%
AI-enabled workflow automation enables marketers to focus more time on value generating tasks.
82%
AI enhances data and allows marketers to derive more insights and make informed strategic decisions.
64%
AI automation and insights enables marketers to target campaign spend more effectively (e.g., content bidding).
What is AI, really?
When many people think of AI, what comes to mind is HAL, the computer from 2001: A Space Odyssey, or Skynet from the Terminator franchise: Robots or computers with superhuman intelligence across a variety of knowledge domains, typically used for nefarious purposes. In reality, the kind of AI that companies talk about today is very different, and fortunately much more benign.
Artificial intelligence is broadly defined as a computer system that performs tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and translation between languages.
— OXFORD ENGLISH DICTIONARY
In contrast to the broad, human-like AI portrayed in most science fiction, most successful AI systems today (such as Google Deepmind’s AlphaGo4) are designed to solve narrowly defined tasks, such as playing a game, recognizing faces or recommending products from a catalog.
These systems tend to be characterized by two qualities:
1.
Systems do not have to be explicitly programmed in advance.
2.
Systems can learn from decisions and improve performance over time.
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AI is not something you can “set and forget”
Today’s AI systems are not yet mature enough to autonomously adapt and extrapolate beyond the use cases for which it is designed. AI must be guided and taught, by people. Common sense is an innately human capability; teaching it to a machine requires clearly defined objectives, optimized for specific situations. Algorithms and governance provide the necessary guardrails to keep AI on track; even the most innocuous application can lead to embarrassing, and potentially disastrous, consequences. AI can, for instance, reinforce outdated gender roles or further racial stereotypes if a company fails to create ethical governance systems for AI design and use.
Thoughtful intervention and close human-machine collaboration are small challenges to overcome to realize the full potential of AI.
What can AI do?
What kinds of tasks can AI perform? AI and Machine Learning systems act intelligently in four interconnected ways, each of which has a variety of high-value applications.
Understand the world
Computer vision
Face recognition
Listening
Remote sensing
Optical character recognition (OCR)
Interaction with humans
Natural language processing (NLP)
Gesture recognition
Speech recognition
Speech synthesis
Machine translation
Content generation
Test & decide
Predictive modeling
Bandit experimentation
Reinforcement learning
Unsupervised learning
A/B testing
Expert system
Take action
Agents
Recommender system
Digital Marketing execution
API-bound integration
Robotics
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Using these techniques, AI systems can explore highly complex and varied options for customer engagement very quickly, and continuously optimize their performance as more data becomes available. This means marketers can set parameters and allow the AI to optimize and learn to achieve precision.
How can AI fulfill its marketing potential?
Marketers should consider two things integral to getting the most from AI technology: The readiness of individual marketers to adopt and embrace AI, and the readiness of marketing organizations to adopt an AI-centric approach to marketing.
Marketers of the future will still bring the traditional marketing competencies of creativity, ideation and customer empathy. In fact, these skills will become more important when AI systems automate many of the mechanical and quantitative tasks that consume marketers’ time. That said, marketers will need to continue to grow skills in data and analytics to guide decisions made by increasingly sophisticated AI systems.
As organizations equip the workforce with AI, employees will need to learn how best to work productively and benefit from it. As humans and machines collaborate, marketers should increasingly delegate tasks to machines and focus more on the outcomes they hope to achieve. As AI matures, so can the complexity of the tasks delegated to machines.
This marriage of human ingenuity with intelligent technology will enable companies to go beyond simply boosting productivity to developing differentiated customer experiences and creating entirely new products, services and markets.
Accenture estimates that human-machine collaboration could boost business revenues by 38% from 2018-2022 (as much as 50% in the CPG and health sectors) and lift global profits by a total of $4.8 trillion by 2022.
— 2018 ACCENTURE MICROSOFT SURVEY
It’s time to prepare for an AI future
As AI works its way across the marketing organization, it promises to dramatically change the way marketers work, hire, learn and organize. In fact, 84 percent of marketers surveyed think AI will make their role more effective.11 It also has virtually limitless potential to add value to the marketing organization overall: Repetitive work will get done faster and more accurately, decisions will be informed by more intelligence, and the entire marketing chain will be optimized.
The stakes have changed. A majority of marketers believe AI will be a keystone component of marketing. Established strategies will be accelerated and powered by AI in ways that are not yet possible with current systems. Marketing teams must fully embrace and embed AI into their DNA. Only then will they be equipped to quickly adapt to a dynamically evolving customer landscape.
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