I spend much of my day engaging with chief marketing officers (CMOs) from startups and emerging companies, and many are reporting growing concerns in the C-suite regarding the implications of generative AI.
Some CEOs speculate that marketing teams can downsize since automated tools can enable smaller teams to handle larger workloads. Alarmingly, a recent survey revealed that 49% of CEOs believe that most or all aspects of their roles could be automated or replaced by AI technology.
In contrast, the majority of CMOs I work with perceive the landscape differently: 81% of marketers surveyed by Norwest in April 2023 expressed no intentions to reduce their team sizes due to generative AI; in fact, 22% anticipate hiring more employees as a result of believing that generative AI will enhance their teams' productivity.
However, it’s important to note that generative AI is not a swift solution—at least not yet. We are still in the early stages of understanding what works, what doesn’t, and how generative AI applications will advance. Critical concerns regarding employee morale and retention, copyright issues, bias amplification, and data privacy remain uncertain.
My advice to CEOs is to collaborate with your CMO before making any staffing changes. Implement focused and measurable trials of generative AI tools to gather insights that can inform your organizational design and marketing strategies.
Here are four actionable steps to maximize your investment in generative AI and enhance business outcomes:
1. Request Regular Updates from Your CMO on Generative AI Usage
Begin discussions with an assessment of how your marketing team is currently utilizing generative AI. You might be surprised by the breadth of its application—content creation, corporate messaging, organizational design, image generation, presentation development, meeting summaries, and beyond. Identifying trends and productivity improvements over time will help determine which tasks can be shifted to generative AI, allowing your staff to focus on higher-level strategic initiatives.
You can track this information through a simple spreadsheet. I’ve created a system to monitor generative AI use cases at our portfolio companies, compiling contributions from marketing leaders into a shared database. This includes date-stamped entries on tools used, effective and ineffective use cases, query optimizations, and other key insights. It serves as a resource for sharing learned experiences among colleagues and CMOs across portfolio companies, and can easily be adapted for any organization.
I recommend establishing a monthly or quarterly update schedule. The rapid evolution of this technology necessitates ongoing dialogue. CMO reports should address:
- The impact of generative AI on productivity.
- The most and least productive use cases to standardize or abandon.
- Key insights that will guide decisions on future generative AI adoption.
- Query hacks that can benefit all users.
- New opportunities expected from ongoing experimentation.
- External data collected from peers and networks for a broader perspective.
You’ll want similar insights from team leads in finance, human resources, and legal, as they are also affected by generative AI.
2. Develop a Plan for the Future Use of Generative AI in Marketing
Given that forecasting the evolution of technology is challenging, it’s crucial to have a clear vision for how generative AI will integrate into your marketing operations. Collaborate with your CMO and marketing team to envision how the advantages created by AI today can free up marketers' time in the future.
From this vision, the team should outline a plan that:
- Establishes priorities among current and potential use cases.
- Identifies and ranks which top-tier tools should be adopted.
- Predicts opportunities for improved efficiency and output.
- Sets specific goals for savings and process improvements, including tracking metrics.
- Creates a development strategy to enhance team members' skills, reallocating time from tasks that generative AI can handle.
- Incorporates lessons learned into policies governing the use of generative AI.
3. Implement a Company-Wide Policy for Generative AI Usage
To derive value from tools, proper usage is essential. Since generative AI applications are still relatively new, establishing guidelines for their application is crucial to educate employees and avoid unintended negative outcomes.
Interviews with CMOs reveal significant concerns regarding accuracy, quality control, data privacy, security, and legal issues. Yet only a handful of companies have developed policies to mitigate these risks, and many have yet to start creating such guidelines.
Without strict policies, employees may use AI tools in ways that unintentionally expose sensitive corporate or client data. Given that the average employee may lack a deep understanding of how large language models function, they could inadvertently share confidential information while querying generative AI tools, similar to initial challenges associated with “shadow IT” in early SaaS and open-source environments.
In addition to crafting a policy, consider investing in enterprise-grade generative AI solutions to minimize risks associated with data exposure. Options like bespoke large language models or secure services such as ChatGPT for Enterprise can safeguard your data and convey the importance of data integrity to staff.
4. Review Generative AI Expenditures in the Next Budget Cycle
Currently, generative AI tools are affordable and can typically fit within your marketing budget, which is often around 10% of total program spending. Popular options like ChatGPT, Jasper, and Bard range from $30 to $50 per user monthly. The availability of numerous new tools allows for ample experimentation to assess their effectiveness.
As these tools mature, expect costs to rise. By then, you should have a prioritized list of standardized tools for your organization.
When planning for 2024, reflect on how generative AI will influence hiring strategies. Which roles can be redefined or enhanced? What training opportunities can be provided for team members seeking new skills? How should job descriptions for new positions be adapted?
Think of AI as a valuable new team member—consider which responsibilities it can assume and which it should not.
Key Takeaways for Generative AI Adoption
We are at the beginning of the generative AI revolution, so it’s essential to avoid premature conclusions. The objective is not to pit generative AI against human talent; instead, it’s about integrating generative AI into marketing functions to capitalize on productivity and innovation opportunities.
Start small, iterate, and learn throughout the process. Stay informed on developments and trends in generative AI and its applications. Ensure data security through robust policies and guidelines.
Embrace generative AI in your organization—it can alleviate marketing teams from mundane, low-value tasks, enabling them to focus on high-value work that demands business acumen, institutional knowledge, and visionary thinking. This shift will empower you to redeploy top performers onto new strategic initiatives.
Generative AI is already enhancing creativity, efficiency, and effectiveness in marketing. However, the expectation that it will replace marketing roles entirely is unfounded. CEOs and CMOs should work together to progressively expand the use of generative AI to derive greater business value from their marketing efforts.
Ranking
