AI has become one of those topics that you cannot escape. It shows up in boardrooms, earnings calls, LinkedIn posts, and even backyard barbecues. Every company seems to be appointing a chief AI officer, and every department is establishing its own AI champion squad.

Whether AI will eventually replace humans in many disciplines remains a polarizing debate, but its impact as a productivity tool is already undeniable. That impact extends well beyond process automation. AI is fundamentally changing the way we synthesize information, generate insights, and make decisions, often at a scale and speed that humans cannot easily match.

More importantly, AI is beginning to reshape the way marketing organizations are structured and how marketing work gets done. Responsibilities that were once divided among multiple specialists can increasingly be handled by a single marketer working alongside AI. As a result, teams are becoming leaner, workflows are becoming more integrated, and the distance between strategy and execution is shrinking rapidly.

With that perspective in mind, I want to share a few observations from my own experience and some of the ways in which AI is already influencing the way I think about designing marketing functions, developing teams, and building processes and governance.

Writing and communication

As organizations grow, marketers become increasingly specialized, and dedicated content teams inevitably emerge. Before long, writing becomes somebody else's job.

When I led large marketing teams, I spent a great deal of time fostering true collaboration. I often encouraged team members to develop both majors and minors, areas of deep expertise alongside broader skills, so that nobody retreated entirely into their own cocoon. In my view, strong communication skills have always been one of the defining characteristics of great marketers.

Today, with the help of AI, we simply do not rely on proofreaders in the same way we once did. I still occasionally use copy editors for highly creative promotional campaigns, but many tasks that once required dedicated content specialists can now be handled directly by the marketers responsible for developing and executing campaigns.

As a result, I now spend more time coaching marketers to use AI throughout the creative process and helping them overcome the fear of writing itself. In my own work, I have found AI useful at virtually every stage of the writing process.

During the analytical phase, AI helps synthesize information, identify patterns, and organize ideas. During the creative phase, it helps refine tone, explore alternative approaches, and overcome the occasional bout of writer's block.

Its greatest contribution, however, has been in the mechanics of writing itself. AI can eliminate obvious grammatical mistakes and ensure consistency with whatever style guide an organization chooses to adopt. More importantly, it allows marketers to focus less on the mechanics of writing and more on the audience's experience. Clarity, precision, tone, structure, and flow all play an important role in determining whether an idea is engaging, persuasive, and memorable.

This same shift has transformed the way I work as well. I spend a great deal of time developing materials ranging from articles and presentations to panel discussion frameworks, go-to-market strategies, campaign plans, and executive communications.

I have always been an analytical thinker. Structuring and sharpening arguments come naturally to me. Expressing those ideas clearly and elegantly has always required much more effort.

AI changed that. I often find myself having lengthy conversations with AI, not simply to improve the quality of the writing itself, but to challenge my own assumptions, identify gaps in my reasoning, strengthen supporting evidence, adapt ideas to different audiences, and ensure that my ideas are grounded in substance rather than fluff.

But the conversation is only part of the process. I still review everything word by word, often through many rounds of revisions. More often than not, I discover nuances that the AI has missed or subtle changes that improve the precision of the argument.

While AI has dramatically accelerated the process, it has not eliminated the need for time and reflection. Many of my deliverables still take days to complete because I continue to rely on the same discipline I always have: stepping away, returning with a fresh perspective, and revisiting the work repeatedly until the ideas feel complete.

In many ways, AI has changed the mechanics of writing, but it has not changed the fundamentals of communicating well.

Creating derivative assets

In my blog about storytelling, I wrote about the importance of creating derivative assets from a single piece of content. This is one area in which I have found AI to be particularly valuable because it reduces costs, shortens turnaround times, and enables campaigns to move with much greater speed and flexibility.

Creating text-based assets such as LinkedIn posts and webinar abstracts is now relatively straightforward. Reviewing webcast transcripts has become dramatically easier. What was once a tedious and labor-intensive process can now be largely delegated to AI. Themes can be identified quickly, key points can be summarized, and new articles, emails, and social posts can be created in a fraction of the time.

The more interesting development, however, has been in video production, which has traditionally been one of the most expensive and time-consuming aspects of content marketing. Today, much of that work can be completed in a matter of hours, often with little involvement from dedicated video specialists.

In B2B marketing, we are rarely trying to produce a Hollywood movie. More often, we are simply trying to capture a moment that encourages someone to watch a webcast, download an article, or start a conversation.

AI tools can quickly identify the most compelling moments from a webcast and transform them into short clips for digital channels. I have found the same approach useful for live events. Rather than filming an entire session, we often record only the audio and use AI to identify the most compelling excerpts. Those clips can then be paired with supporting visuals and quickly incorporated into relevant campaigns.

Of course, I never relinquish complete control. Hallucinations still happen, context still matters, and every asset still goes through multiple rounds of review before publication.

Demand generation and CRM enrichment

Demand generation depends on data quality.

In almost every campaign, marketers face a trade-off between gathering more information and reducing friction for prospects. The fewer fields we include on an intake form, the higher the conversion rate tends to be. As a result, our databases are almost always incomplete.

In the past, junior marketers spent countless hours researching and enriching records manually. Today, AI can classify companies, identify industries, standardize job titles, map accounts to existing opportunities, and uncover relationships that might otherwise go unnoticed.

Many of these tasks previously required pivot tables and even custom coding. Today, they can often be completed in minutes.

More importantly, better data and faster analysis are making demand generation more integrated and more agile. Rather than treating content, events, sponsorships, social media, and email campaigns as separate activities, marketers can increasingly view them as connected parts of a single demand generation strategy.

Better data-driven insights also allow teams to adjust more quickly as pipeline priorities and market conditions change. Rather than waiting weeks to understand what is working, marketers can assess pipeline impact more quickly, refine execution, and reallocate resources while campaigns are still underway.

ROI analysis and reporting

Of all the applications I have discussed, this may be the area that excites me the most because I believe the opportunity is enormous.

As marketers, we spend an extraordinary amount of time gathering data, building reports, reconciling numbers across systems, and trying to understand what is actually driving results. Campaign data, website traffic, email performance, pipeline metrics, and event attendance all tell part of the story, but assembling the complete picture can be surprisingly time-consuming.

AI has already helped my team reduce some of that burden.

We now routinely use AI to analyze campaign data, identify patterns, compare performance across campaigns and vendors, and extract insights that might otherwise take hours to uncover manually. Rather than spending time manipulating data, I can spend more time thinking about what the data actually means and what actions to take.

The process is still imperfect. Data often resides in disconnected systems, and the lack of connectivity and integration continues to create friction. While AI capabilities are becoming increasingly embedded within enterprise software platforms, seamless workflows remain a work in progress. Nevertheless, I am optimistic that these gaps will gradually disappear as AI becomes more deeply integrated into the tools we use every day.

More importantly, I believe AI is shifting marketing measurement away from reporting and toward decision-making. Rather than simply explaining what happened, marketers will increasingly be expected to understand why it happened and determine what should happen next.

Like many other applications of AI, the greatest benefit is not that the technology replaces human judgment. The real advantage is that it enables better decisions to be made more quickly.

Final thoughts

The question is no longer whether AI will change the way we work. The question is how willing we are to change with it.

Throughout my career, I have watched marketing become increasingly specialized. Content teams create content. Operations teams manage technology. Analysts interpret data. Demand generation teams execute campaigns. Each function develops its own processes and priorities, creating fragmentation and distance between strategy and execution.

AI is changing that equation. Marketers now have access to tools that allow them to plan, create, execute, and optimize campaigns more holistically than ever before. 

In many ways, AI is helping marketing become a more integrated discipline.

I do not believe this means specialists will disappear. Human creativity, experience, and judgement will remain essential. But I do believe the most successful marketers will become versatile and adaptable as the boundaries between disciplines continue to blur.