Michael Cohen is the global chief data and analytics officer at Plus Company, a Quebec-based marketing agency. He’s joining Marketing Brew next week at our event, The Marketer’s (Early) Guide to AI.
Ahead of the event, we had Cohen tell us a little bit about how he and Plus Company are using AI, and what his thoughts are on the possibilities of the tech.
Does your company have policies around using AI? If so, what are the main tenets? Plus Company has implemented a global agile policy and program known as “Acceptable Artificial Intelligence (AI) Use” to guide employees in the use of AI in their everyday work. Probably the most important tenant of this policy is human-centered decision-making and creation. Our employees know that human judgment is the arbitrator of what AI produces, recommends, and carries out. Continuous learning and personal, team, and business process development is ushered through our company’s initiative to provide ongoing and up-to-date training. Individual innovators and leaders across our network delve deep into AI use cases and best practices as part of the quest to transform the way we work and the quality we deliver with the empowerment of AI.
What AI tools are you currently using? In what capacity are you using them? We have a long list of approved, yet-to-be determined, and not-approved software solutions. These solutions rely on a few main types of AI (data augmentation large and small, language models, diffusion models, reinforcement learning, and earning models) and several pure-prediction approaches. They are used for productivity-enhancing solutions for existing tasks, like drafting a paragraph, producing an array of prompted images, or writing blocks of computer code. They are also used for solutions to systematic problems such as missing or unclean data (e.g., late data, walled gardens, or privacy-protected PII data), identifying different and better ways of doing something (making your weakest team members as productive as your strongest), or eliminating unnecessary steps altogether (time sheets).
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What is the best real-life application of AI that you have seen in the marketing world so far? Data augmentation combined with conversational UI/UX to directly give marketing managers market data derived answers to questions, consolidation of creative, communication planning, and data insight for better, cheaper, faster execution.
Generally, the best real-life application is any application that reduces a blend of human hours by orders of magnitude to carry out.
There are plenty of proposed use cases for AI, from customer service applications to improving brand voice to analyzing the customer lifecycle. Which applications are most promising to you? Which ones are least promising? Most promising: Use cases that change antiquated business models like time and materials-based ones (like scalable adoption of automobiles to replace horses).
Least promising: Ones that automate tasks that are only required in a world without AI (like having robots to maintain horse stables across a city).
What advice do you have for marketers and brands that are considering using AI but aren’t sure where to start? Follow two tracks: One that leverages AI to get more productivity and quality out of the employee base, e.g., using AI to produce images, prose, and computer code, and the other that strategizes on what is possible and allows you to rethink what you do, how you do what you do, and where the value to customers and the business might alternatively lay.