– CEOs believe that generative AI can lead to leaner marketing teams and potential job cuts
– However, the majority of CMOs surveyed do not plan to reduce team size due to gen AI and believe it can make marketing teams more productive
– It is still early to determine the impact of gen AI on issues like employee morale, copyright, bias amplification, and data privacy
– CEOs should partner with their CMO to conduct trials of generative AI tools before making staffing decisions
– Four steps are recommended to optimize investment in gen AI and drive positive business outcomes:
1. Ask the CMO to provide periodic briefings on generative AI use cases
2. Track gen AI use cases and lessons learned in a shared database
3. Establish a regular schedule for updates on gen AI technology
4. Use the CMO’s reports to answer questions and determine which tasks should be allocated to gen AI
I spend most of my days talking to and working with chief marketing officers of startups and young companies, and several report rising tension in the C-suite over the potential of generative AI.
Many CEOs think marketing headcount can be cut as automated tools allow leaner teams to accomplish more. Remarkably, these top-job leaders are contemplating even broader cuts, with a recent survey indicating that 49% of CEOs believe most or all of their own jobs should be automated or replaced by AI.
But the majority of CMOs I work with see it differently: 81% of the marketers Norwest surveyed in April 2023 indicated they have no plans to reduce team size due to gen AI, with 22% of those saying they plan to add headcount based on the belief that gen AI will make marketing teams more productive.
Gen AI is not a quick fix, at least not yet. It’s too early to know what works, what doesn’t, and how gen AI applications will evolve. None of us can be sure what the potential impact will be on key issues such as employee morale and retention, copyright, bias amplification, and data privacy.
My advice to CEOs: Before making any staffing decisions, partner with your CMO to conduct focused and measurable trials of generative AI tools. Then apply the lessons learned to shape both your org design and marketing strategies.
Here are four concrete steps to optimize your investment in gen AI and drive positive business outcomes.
1. Ask your CMO to provide periodic briefings on generative AI use cases
The starting point for any discussion is an assessment of how gen AI is already being used by the marketing team. You might be surprised how widely it has been adopted: content production, corporate and product messaging, org design, image generation, presentation slides, meeting summaries, and more. Over time, you can identify trends and productivity gains to determine which tasks the marketing team should retain and which can be allocated to gen AI to free up staff for more strategic work.
Before making any staffing decisions, partner with your CMO to conduct focused and measurable trials of generative AI tools.
Execution of this task can be as simple as creating a spreadsheet. I’ve developed a system for tracking gen AI use cases at our portfolio companies that marketing leaders contribute to as a shared “database.” It gathers date-marked inputs on the tools being used, best and worst use cases, query hacks, and other considerations. I use it to share lessons learned among colleagues and CMOs at portfolio companies. And it can easily be used within a single organization.
My recommendation is to establish a monthly or quarterly schedule for updates. The technology is evolving too quickly for a one-and-done conversation. The CMO’s reports should answer questions such as:
AI Eclipse TLDR:
The article discusses the potential impact of generative AI on marketing teams and the differing views among CEOs and CMOs. While many CEOs believe that marketing headcount can be reduced with the use of automated tools, 81% of CMOs surveyed have no plans to reduce team size due to gen AI. In fact, 22% of CMOs plan to add headcount based on the belief that gen AI will make marketing teams more productive. However, it is still too early to determine the full impact of gen AI on issues such as employee morale, copyright, bias amplification, and data privacy. The author advises CEOs to partner with their CMOs to conduct trials of generative AI tools and use the lessons learned to shape both organizational design and marketing strategies. The article also provides four concrete steps to optimize investment in gen AI and achieve positive business outcomes.