AI is changing creative production, but the strongest message from the 2026 Industry Voices webinar was clear: the tool is not the starting point.
The real starting point is structure.
That means clean data, defined workflows, stronger governance, better measurement, and people who still know what good creative work looks like.
In the webinar, Claire Palk, Head of Growth Marketing at We Are Amnet, was joined by Christi Simoneaux, Director, Creative Special Projects at Oldcastle APG; Todd Dunham, VP, Marketing Operations & Strategy at Prologis; George Friedman, Senior Director, Creative Content Development & Production at Tonic at Highmark Health; and Anil Noorani, Founder and CEO of TKM Consultants.
The discussion built on the themes from the 2026 Industry Voices report, Future Proofing Your Creative Production Strategy, and explored how AI is reshaping production from the perspective of in-house agency leaders, marketing operations, creative production, and industry advisory teams.
The full webinar is now available to watch on demand. Here are some of the key takeaways.
AI Readiness Starts With Data
One of the strongest early themes was data.
Christi Simoneaux explained that her team is preparing for wider AI adoption by focusing on the foundations first. She described the work underway around data cleanup, product information, brand guidelines, DAM structure, and connected systems.
As Christi put it, “as anybody who has used AI knows that the output is only as good as the prompts and the data.”
That line captures a major point for creative production teams. AI does not automatically create better output. It works from the inputs, structure, and rules it is given.
Christi also explained that her organization is “in a massive data cleanup mode,” with a focus on SKU information, enriched marketing data, and brand guidelines. For a business with “11,000 plus SKUs,” that foundation matters before enterprise AI tools are implemented at scale.
The lesson is practical: AI readiness starts before the tool. It starts with clean data, clear brand information, and a reliable source of truth.
Automation Will Expose Weak Data
George Friedman reinforced this point from a regulated healthcare perspective.
At Tonic at Highmark Health, the data challenge has an added layer of complexity because the organization operates in a highly regulated environment. George explained that as teams improve their MarTech stack, CRM capability, and automation, the quality of the data becomes more visible.
He said, “you can’t automate if your fields don’t line up or if things don’t work properly.”
That is a simple point, but it is one many teams overlook. Automation does not hide poor data. It exposes it.
For creative production and marketing teams, this means AI adoption will depend on the quality of the systems underneath it. If teams want automation to support better briefs, faster content delivery, more relevant messaging, or stronger customer experiences, the data needs to be accurate and usable.
Workflow Definition Comes Before AI
Todd Dunham brought the conversation back to process.
He explained that many companies have focused on launching tools before fixing the foundations. In his view, data matters, but so do processes and workflows.
Todd said, “The processes and workflows are critical,” and added that teams need “really well-defined workflows” because an AI tool will “model whatever that workflow definition is.”
That is one of the most important takeaways from the webinar.
AI creates value when it is added to a workflow that is already understood. If the workflow is unclear, inconsistent, or poorly governed, AI will only reproduce that lack of structure.
Todd also spoke about the need to understand “the right place to plug an AI tool in.” This is where many creative production teams need to pause. AI should not be added everywhere at once. Leaders need to know where it will improve the work, where it will create risk, and where human review must remain central.
AI Adoption Is Also a Change Management Challenge
The panel also discussed the human side of AI adoption.
Christi shared that some team members have already embraced AI, while others are still unsure how to use it properly. She said there are people who have “just taken it and and run with it” and others who are still “unsure of of how to properly utilize it.”
That uneven adoption is familiar across many organizations. Some people are already experimenting with AI every day. Others are still cautious, unsure, or waiting for clearer guidance.
Todd also spoke about anxiety around AI. He said there is “a fair amount of anxiety,” especially because many people compare their progress with technology companies or the most advanced AI users.
His recommendation was clear: continuing education matters. He said, “now more than any time in my career is a time for continuing education.”
For creative production leaders, this means AI strategy cannot only be about software. It also needs training, internal support, change management, and clear expectations around how teams should use AI in their day-to-day work.
AI Value Needs Better KPIs
Another important section of the webinar focused on measurement.
Many teams are still measuring AI value through speed, time savings, and efficiency. Those metrics matter, but Todd argued that the next stage needs to be broader.
He said the focus should move toward “how it’s impacting our business KPIs,” including “revenue impacted, pipeline impacted, how much rework reduction, error reduction in our workflows, brand compliance.”
This is an important shift.
AI value should not be measured only by whether something was produced faster. Creative production leaders also need to know whether the work became better, more accurate, more useful, and more aligned to the business.
For brands and in-house teams, the better question is not only: did AI save time?
The better question is: did AI help the team create work that improved outcomes?
AI Creates Opportunity, But Trust Still Matters
The panel also discussed whether AI is increasing pressure on teams to produce more content.
Todd gave a useful answer. He said, “it’s less about pressure and more about opportunity.”
He described how teams see the opportunity to take one larger asset, such as a white paper, and adapt it into several smaller pieces for different channels.
That is where AI has clear value. It helps teams extend content, tailor it to more channels, and get more from strong source material.
But Todd also warned about the risk. He explained that the goal must remain “putting really high-quality authentic, accurate content in front of your customer,” because poor or inaccurate content damages trust.
This is one of the strongest strategic points from the webinar. AI will help teams create more content, but more content is not automatically better. Content still needs to be accurate, relevant, and worth the audience’s attention.
Operating Models Are Being Disrupted
The discussion then moved from tools and workflows into operating models.
Todd described a major shift across three areas: the tech stack, partners, and the way work gets done across processes and people.
He said, “we’re seeing an enormous shift in the operating model.”
That line reflects the wider challenge facing marketing and production teams. AI is not only changing individual tasks. It is changing the system around the work.
Leaders now need to think about which tools belong in the stack, which partners are right for the next stage, how work should move across teams, and where AI should be added carefully.
George agreed that his team is going through a similar moment and highlighted the need to decide “who should have what tools and when and where that adds the value.”
That point matters. AI access needs to be managed. Not every tool should go to every person at the same time. Teams need a deliberate approach that protects quality, brand, security, and workflow control.
Governance Needs Enterprise and Marketing Ownership
Governance was another major theme.
Christi explained that governance is managed at both creative team level and enterprise level. She said there are rules being set by “our IT teams” and leadership, including guardrails that make some options “not even an option.”
George shared a similar view from healthcare, explaining that tools are reviewed at enterprise level with legal and AI teams involved.
Todd added an important distinction. AI systems may be governed at enterprise level, but content governance sits with marketing teams.
He said, “when it comes to content governance, we manage that on the mark on the global marketing team and on our marketing teams globally.”
That distinction is important for any brand using AI in creative production.
Enterprise teams need to manage security, privacy, IP, tool approval, and system-level risk. Marketing and creative teams need to manage content quality, brand consistency, review standards, approval paths, and customer-facing output.
Both are needed.
Future Skills Still Depend on Human Judgment
As the discussion moved into future skills, one point came through strongly: people still need to know what good looks like.
Christi said, “we still need good writers and you still need to know what good looks like.”
She also noted that some AI-generated copy she reviews is “too long” or “muddled.”
George made a similar point. He spoke about the importance of “cultivating advanced creative expertise and discerning quality.”
This is one of the most important messages for creative teams. AI will become part of writing, design, production, video, content operations, and strategy. But people still need to judge whether the output is clear, accurate, usable, and on brand.
AI will support production. It will not remove the need for creative judgment.
Final Recommendations From the Panel
At the end of the webinar, the panel was asked to give one recommendation.
George focused on quality. He advised people to learn from strong work and build the ability to judge it. He said the key is “understanding quality and discerning quality.”
Christi focused on purposeful change. She said leaders need to recognize whether change is “for change sake” or whether it is “change that moves the business forward.”
Todd focused on learning and openness. His recommendation was to “be open to learning new things” and to lean into “thinking about work differently.”
Anil closed with a reminder about community and shared learning. His recommendation was to “surround yourself with really bright intelligent people” and to “keep talking” and “keep learning off each other.”
That final message captured the tone of the whole discussion. AI is moving quickly, but leaders do not need to work through these decisions in isolation. The best thinking will come from shared experience, open conversation, and practical lessons from teams already working through the change.
This summary only covers part of the discussion.
The full 2026 Industry Voices webinar goes deeper into AI readiness, data, governance, operating models, future skills, measurement, and how creative production teams are preparing for what comes next.
Watch the full webinar recording here
You can also download the 2026 Industry Voices report, Future Proofing Your Creative Production Strategy, here
