• Being an operator in the age of AI

• How AI is changing marketing workflows

• Automation, busy work, and real value

• Stakeholder engagement as a core skill

• Decision-making and project ownership

• Creativity and productivity with AI

• What this means for marketers going forward

In this episode of Visionary Voices, I sat down with Whit Harwood, VP of Growth Strategy at MediaLink, to talk about what it really means to operate in modern marketing as AI becomes more embedded in how work gets done.

Throughout our conversation, Whit repeatedly came back to a central idea: being an effective operator matters more than ever. Tools are changing quickly, but the ability to move projects forward, make decisions, and work with people across an organisation still sits at the core of meaningful impact.

Rather than focusing only on specific AI tools or trends, we explored how the role of marketers is evolving, and what it might look like to build a career where you can adapt as automation reshapes the work around you.

How AI is changing marketing workflows

Whit and I discussed how AI is already starting to influence marketing workflows, from content production to analysis and reporting. While some tasks are becoming faster and more automated, the conversation highlighted that AI is not replacing the need for marketers, but is likely to change where their time is spent.

Instead of manually handling repetitive tasks, marketers may increasingly work alongside automation, using AI to support research, ideation, or execution. That potential shift raises questions about what skills will matter most when the basic execution becomes easier to delegate to software.

Whit framed this as an opportunity for people who are comfortable taking responsibility for outcomes rather than just completing tasks on a checklist. When the mechanics become more automated, understanding why a project matters and how it contributes to broader goals becomes even more important.

Automation, busy work, and real value

A big theme in our conversation was how automation can expose the difference between busy work and real value. Many roles include a lot of activity that looks productive but does not necessarily drive meaningful results. As AI tools take on more of this executional layer, what remains visible is the actual contribution someone makes to a project.

Whit suggested that this shift may surface who can truly move work from idea to implementation. When software can handle formatting, drafting, or pulling data, the differentiator becomes who can interpret information, prioritise, and decide what to do next.

This does not mean that foundational skills are less important. If anything, understanding the basics of marketing, strategy, and operations gives people better judgment about how to use automation wisely.

Stakeholder engagement as a core skill

Beyond technical skills, Whit emphasised the importance of stakeholder engagement. Projects rarely exist in a vacuum, especially in larger organisations. Being able to bring the right people together, communicate clearly, and align around a shared direction is a core part of being an effective operator.

In the context of AI, this becomes even more relevant. As teams test new tools or rethink workflows, there are often concerns, conflicting priorities, and different comfort levels with change. Someone who can listen, explain trade-offs, and keep momentum going can make a meaningful difference.

Our discussion pointed to this blend of communication and ownership as a key area where humans continue to add distinct value, regardless of how capable AI tools become.

Decision-making and project ownership

Another thread we explored was decision-making. AI can surface options, generate ideas, or provide analysis, but it does not remove the need for humans to choose a direction and take responsibility for it.

Whit described the importance of people who are comfortable owning a project from start to finish: defining the problem, mapping out the steps, making trade-offs along the way, and adjusting when reality does not match the original plan.

AI may give operators more leverage, but it does not replace the judgment required to decide what matters, in what order, and why. That judgment is often developed through experience, feedback, and exposure to real constraints rather than purely theoretical learning.

Creativity and productivity with AI

We also touched on how AI intersects with creativity and productivity for marketers. On one hand, AI can help people generate more ideas quickly, test variations, or explore different angles on a brief. On the other hand, there is a risk of over-relying on tools and losing the human perspective that makes work resonate.

Whit noted that the most interesting use cases often come from people who are curious and willing to experiment, but still apply their own taste and understanding of the audience. In that sense, AI becomes a collaborator that can speed up parts of the process while the person remains responsible for the overall quality.

Rather than replacing creative thinking, AI might free up time and mental space for higher-level exploration, provided people are intentional about how they integrate it into their workflow.

What this means for marketers going forward

As we wrapped up, our conversation kept coming back to the idea of being an operator who can navigate change. Tools, platforms, and tactics will continue to evolve, but the ability to take ownership, work with stakeholders, and move projects forward is likely to stay valuable.

For marketers, that may mean focusing less on mastering a single tool and more on building adaptable skills in communication, decision-making, and project management. AI can enhance what they do, but it does not remove the need for people who can connect the dots and see the bigger picture.

Whit’s perspective offered a grounded way to think about the future of marketing in an AI-influenced environment: not as a story of replacement, but as a shift in where human operators spend their time and how they demonstrate their value.