What is a Production Strategy Audit
A production strategy audit is a structured review of your intake, ownership, workflow rules, and quality controls so you can increase output with AI support without increasing risk, rework, or approval delays.
If you lead content production at a brand or an in-house agency, you are already under pressure to publish more, across more formats, at a faster pace. Todd Dunham at Prologis describes in 2026 Industry Voices report – why that pressure keeps rising in B2B marketing. “Yes, without question. Strong high-quality content is the lifeblood of modern B2B marketing, without it brands get lost in the noise but with it they stand out in hyper competitive industries. We compete in many adjacent markets with unique target segments so we need to generate content for all the commercial lines we support and content needs to be fresh, timely and relevant so it’s constantly being updated.”
AI will change how you handle this workload, but the report is clear about where most organizations are not ready. Fewer than 30% say they have the internal expertise to evaluate or govern AI effectively. Only 36% say employees have been trained on the skills needed for AI transformation.
So the first question is not, “Which tool should you pick?” The first question is, “Do you have the operating discipline to use AI in production without losing control?”
Section 1: Assign Ownership Before You Touch Workflows
If you cannot name owners, you cannot control outcomes. AI increases the number of people, tools, and paths that content can move through. That makes unclear ownership expensive.
Run this ownership check and write the names down.
- Who owns AI use rules for creative production
This person decides what AI may generate, for which asset types, and under which review conditions.
- Who owns risk and review
This person defines what gets checked, who checks it, and what cannot go live without sign-off.
- Who owns brand quality
This person owns “what good looks like” for voice, design compliance, and consistency across channels.
- Who owns training
This person ensures people know how to use AI within your rules, and how to verify outputs.
If any answer is “shared,” treat it as “unclear,” then fix it.
Section 2: Fix Intake Quality, Because Inputs Control Outputs
AI does not rescue weak briefs. It produces faster versions of unclear direction, then your reviewers spend more time correcting it.
Audit your last 30 to 50 briefs and score them against five fields.
Objective
Can you explain the job in one sentence?
Audience
Do you know who it targets?
Channel and format
Do you know where it runs and what you need delivered.
Constraints
Does the brief state what you must avoid, and what must be verified.
Single approver
Do you have one accountable approver, not a chain of feedback.
If you tighten intake, you reduce revisions and approval time. You also make AI output easier to check.
Section 3: Apply AI In Production Based On Risk
You need a clear line between work that must stay human-led and work where automation should start.
Use this three-tier split.
Tier 1: Brand-defining work
High scrutiny, high risk if wrong.
Tier 2: Campaign versions and local variants
Medium risk, high volume.
Tier 3: Routine and repeatable work
Lower risk, high volume.
Start AI use in Tier 3. Keep human review. Expand only after you hit targets.
Track four measures for 30 days before you expand:
- Approval cycle time
- Revision rounds
- Rework rate
- Brand compliance issues
If any of these get worse, you do not have a tooling issue. You have a workflow and ownership issue.
Section 4: Read Your AI Maturity Honestly
Todd is direct about where most organizations sit today. “With how rapidly AI is evolving, I’d venture to say that we’re all in the infancy stage. Without a crystal ball, it’s hard to know what will emerge next. However, we have definitely embraced AI technology and have incorporated it in varying levels across graphic design, audio production, video production, copywriting, social media automations, and email marketing.”
He also makes an important quality point that leaders need to repeat internally. “Although AI is no substitute for a seasoned eye in terms of quality, accuracy or voice, it has definitely been an effective tool in improving efficiency and expanding our capabilities.”
If your leadership team expects AI to replace review and judgment, correct that expectation now. AI helps when you define use cases, standardize inputs, and keep accountability clear.
Section 5: Run A Skills Check That Matches What You Produce
The report highlights a training gap across the market. Only 36% say employees have been trained on the skills needed for AI transformation.
You should not respond with generic training. Train the work your team actually does.
Start with two tracks.
Track 1: Rules and review
- What AI may be used for
- What AI may not be used for
- What reviewers must check
- What evidence reviewers need
Track 2: Input quality
- How to write briefs that produce usable output
- How to write prompts that match your brand voice and channel format
- How to verify AI outputs before they hit review
If you improve inputs, you reduce rework fast.
Section 6: Prepare For What “Digital Native” Really Means
Todd’s skills advice is practical and relevant for brands and in-house agencies that still think in static formats. “Creating more digitally native experiences. Not going all the way to UX/UI design but moving along the spectrum from static to digital to help clients innovate and bring new fresh ideas to them about how they can think differently about static creative and how it can play in a digital world. It’s more than placing QR codes in creative. It’s about identifying what’s coming next that will keep clients ahead of the curve as the evolution toward more digitally native content continues.”
If you want a simple action from this, do this exercise.
Pick one high-volume asset type you produce today, then define:
- The static version you already ship
- The digital version you should ship next
- The team inputs required for each
- The review checks required for each
This turns “digital native” into production decisions, not a trend statement.
A Short Audit You Can Run This Week
If you want AI to increase output without losing control, run this audit in order.
- Assign owners for AI use rules, review rules, brand quality, and training
- Improve intake quality with a five-field brief standard
- Split work into three tiers, start AI in routine work first
- Define review checks by tier, then measure approval and rework
- Train your team on rules, inputs, and verification
- Identify one asset type to shift from static to digital-first output
If you want the full set of leadership perspectives, the readiness data, and the practical operating guidance across strategy, operating models, AI enablement, and skills, download the 2026 Industry Voices report now.
