No tech skill is animating today’s business leaders and workers alike quite like artificial intelligence. As AI redefines the future of work, organizations are faced with the critical task of building, re-skilling, and augmenting their workforce. This is certainly true of the marketing discipline as well.

3 Ways Marketers are Leverage AI

1. Within our existing marketing tools – This is where new features are being rolled out within our existing embedded industry tech stack that augment productivity (like Adobe Express with an embedded AI image generator and AI assistants. AI is being implemented in our standard MarTech tools – from media buying and email automation tools to project management and content platforms). Take the project management AI assistant; we use it for automating answers, summaries, tasks, field completion, milestone creation, and updates.
2. Individualized blue sky use – This is where marketers are creating their own role-specific use cases. Marketers are looking at time spent on manual repetitive operational tasks (very unique to their specific to-do list) and figuring out how to leverage AI. A few examples: one marketer on my team cut down by 85% the amount of time spent on identifying spam leads in a big .csv file. They did a prompt on what to look for and it also provided the Python input. I have another marketer who uses it to draft requirements documents as a starting point, and many content creators are obviously leveraging it.
3. Novel marketing capabilities – This is where AI is unlocking completely new ways to engage audiences, leverage data, and drive innovation. We’re now able to tap into capabilities that previously seemed aspirational but are becoming reality through AI’s rapid evolution. For instance, AI is enabling hyper-personalized marketing at scale, allowing us to dynamically tailor messages, offers, and creative content to individual preferences and behaviors in real-time. Predictive analytics and learning models are also transforming customer insights, enabling us to not only anticipate needs but also actively shape customer journeys in more intuitive, responsive ways. We recently piloted an AI admissions rep (i.e., a simulated representative) who now conducts the initial conversations with students via call, text, and email. Key to this is using the right company-owned data to ensure we give prospects correct information.

AI’s Impact on Marketing Isn’t Just for Increased Productivity; It Also Impacts Cost Efficiency

We’ve seen an 18% decrease in cost per lead through AI-based campaign optimization. By analyzing vast amounts of behavioral and contextual data, AI can now recommend optimal ad placements, creative choices, and delivery timings based on precise customer segment analyses. Continuously optimizing campaigns to improve budget efficiency, while saving time on manual analysis. Important to this:

• Success is predicated on the quality of your AI model – must have quality data inputs from trusted sources. Ideal customer profile and accurate targeting.
• Marketing teams need to be upskilled to have basic data analytics skills. They can’t trust AI if they don’t understand the inputs/outputs.

We Have to Rapidly Close the Skills Gap for AI in Marketing

We see a massive skills gap that the marketing industry needs to address if we want to see a sustainable long term pipeline of tech savvy marketing talent.

At General Assembly, We partner with employers to help them upskill their marketing teams for the AI era. Let me give you a concrete example: we work with Adobe to create a pipeline of young, tech savvy creative and marketing talent. Two new General Assembly bootcamps on marketing and content creation are enrolling students from communities underrepresented in tech – with Adobe covering all costs for them.