AI and the Video Team 2026: What Wistia’s AI Video Marketing Trends Report 2026 means for medium and enterprise businesses in New Zealand
Letter from Kaushik
When we published our first analysis of Wistia’s State of Video Report 2026, one finding kept pulling at us. AI was changing video production almost everywhere, but it wasn’t replacing the people doing the work. It was clearing the busywork out of their way.
Wistia’s companion report, AI Video Marketing Trends for 2026, is the deep dive on exactly that. It surveyed 503 marketers who work with video and asked a more specific question than “is AI coming.” It asked where AI is actually being used, what it’s changing, and where teams are deliberately keeping it out.
The answers are more interesting than the usual AI commentary. Almost everyone has tried these tools. Far fewer are enthusiastic. Teams are using AI to pressure test ideas and scale output, but holding the line on storytelling, brand voice and judgement. And the businesses getting the most from AI aren’t the ones using it the most. They’re the ones who’ve decided most clearly what it’s for.
This isn’t a summary of Wistia’s research, nor a replacement for it. It’s our interpretation of what the findings mean for organisations in New Zealand that sell expertise, trust and complex services, the businesses for whom authenticity isn’t a nice idea but the entire basis of the relationship. Throughout, we present Wistia’s findings with page references back to the original, then explain what we believe they mean for you.
The headline, if you take one thing from this, is counterintuitive. As AI makes content cheaper to produce, the human parts of your business become more valuable, not less. The leadership question is whether you’re set up to make those human parts visible.
Kaushik Kumar, Commercial Director, Dark Matter
Executive Brief: The report in five minutes
If you read one section, read this.
Wistia’s AI Video Marketing Trends Report 2026 surveyed 503 marketers who work with video. (Wistia, 2026, p.33.) Its real value for a leadership team isn’t the tool list. It’s a clear picture of where AI creates advantage and where it quietly destroys trust.
The defining finding: adoption is near universal, enthusiasm is not. 99% of marketers have experimented with AI, but only 32% describe themselves as enthusiastic about it. (Wistia, 2026, p.7.) That gap is the whole story. Teams are using these tools because they have to, while staying cautious about quality, ethics and brand trust. For businesses that sell on credibility, that caution is correct, and it’s a competitive edge if you act on it deliberately.
Five takeaways for decision makers:
The bottleneck is ideas, not production. 33% of teams say generating new ideas and concepts is their biggest challenge, tied with producing at scale. (Wistia, 2026, pp.5, 14.) AI helps most where you point it at thinking, not just output.
AI is bringing work back in-house. 64% agree AI is keeping video production in-house, and 74% of agencies themselves say they’ve reduced outsourcing. (Wistia, 2026, pp.5, 25.) The capability gap between in-house teams and external specialists is narrowing fast.
Output is up sharply. 91% of teams produce more video since adopting AI, and 37% report doubling output or more. (Wistia, 2026, p.23.) The constraint on volume has effectively been removed, which means volume is no longer where advantage lives.
The real concern is trust, not cost. The top hesitations about AI are accuracy and reliability (18%), fear of AI replacing human roles (17%), ethics (15%) and data privacy (15%). Cost ranks far lower. (Wistia, 2026, p.11.)Teams are judging these tools on whether they protect the brand, not whether they’re cheap.
Teams keep AI for the busywork and humans for the voice. Marketers are open to AI for captions, audio cleanup and editing, but resist it for scriptwriting, brand messaging, voiceovers and avatars. (Wistia, 2026, p.19.)The line is drawn at authenticity.
Why this matters commercially. There’s a single sentence in this report that every executive should sit with. When production speed stops being the barrier, what makes your videos different moves up the ladder. (Wistia, 2026, p.29.) If everyone can produce competent video at scale, competent video stops being a differentiator. What’s left is the thing AI cannot generate: genuine expertise, judgement and trust. For New Zealand businesses competing on depth rather than budget, that’s not a threat. It’s the opening.
Chapter 1: Everyone’s In, Few Are Sure
The most revealing number in this report is a gap. 99% of marketers have experimented with AI. Only 32% would call themselves enthusiastic about it. (Wistia, 2026, p.7.)
That’s not contradiction. That’s maturity. The hype phase is over and teams have moved into something more useful: cautious, practical adoption. They’re using AI because the workload demands it, while keeping a clear eye on the risks. 68% now use AI extensively and consider themselves advanced users, so this isn’t reluctance born of inexperience. It’s reluctance born of knowing exactly what these tools do well and what they don’t.
What are teams actually nervous about? Not cost. Not complexity. Trust. The biggest hesitations are uncertainty about the accuracy and reliability of AI output (18%), fear of AI replacing human roles (17%), ethical implications (15%) and data privacy (15%). (Wistia, 2026, p.11.) Cost concerns sit near the bottom at 9%.
Executive insight. Your team’s hesitation about AI isn’t a sign they’re behind. It’s a sign they understand what’s at stake for the brand.
For organisations that sell expertise and trust, this caution is an asset, not a brake. The businesses that will be embarrassed by AI over the next few years are the ones that used it indiscriminately, published content that felt hollow, and eroded the very credibility they were trying to scale. The businesses that win will be the ones who adopted AI with clear rules about where it belongs.
What this means for New Zealand businesses. We tend to be pragmatic adopters rather than early hype chasers, and in this case that instinct serves us well. The opportunity isn’t to use AI more aggressively than your competitors. It’s to use it more deliberately, with explicit guidance for your team about where it helps and where it must not go. Confidence comes from clarity, not enthusiasm.
Questions for your leadership team:
Do our people have clear guidance on where AI is welcome and where it isn’t?
Are we treating caution as a weakness to overcome, or a standard to protect?
If a customer discovered exactly how a piece of our content was made, would we be comfortable?
Chapter 2: The Bottleneck Was Never Production
For years the assumption behind content marketing was that the hard part is making the stuff. Wistia’s data says otherwise.
When asked about their biggest challenge, teams pointed to generating new ideas and concepts (33%) and producing at scale to meet demand (33%), well ahead of budget, time or staffing. (Wistia, 2026, p.14.) The constraint isn’t the camera or the edit. It’s knowing what’s worth making.
This reframes where AI actually helps. The most common use is right at the front of the process: 51% use AI in the ideation stage or to draft scripts and outlines, and 42% use it for audience research and trend analysis. (Wistia, 2026, pp.5, 18.) Teams aren’t mainly using AI to replace production. They’re using it to think faster, to pressure test ideas before committing budget, and to understand their audience before they write a word.
Executive insight. AI’s biggest contribution isn’t making content faster. It’s helping you decide what’s worth making in the first place.
There’s a subtle but important implication here for how you brief and resource marketing. If ideas are the bottleneck, then the most valuable input your business can provide isn’t a bigger production budget. It’s access to the people who actually understand your customers and your domain. AI can draft a script in seconds, but it can only draft a good one if it’s working from real expertise. The raw material still has to come from your experts.
This connects directly to the argument in our first report. Most organisations already hold more knowledge than they could ever publish. The barrier was always the effort of turning that knowledge into finished assets. AI lowers that effort dramatically. Which means the businesses that have captured their expertise, the recurring customer questions, the hard-won lessons, the genuine point of view, are suddenly able to turn it into content at a pace that was impossible before.
What this means for New Zealand businesses. Point AI at the front of your process, not just the end. Use it to interrogate ideas, research your audience and draft from your experts’ raw material. The businesses that treat AI as a thinking partner in pre-production will get more from it than those who only use it to speed up the edit.
Recommended actions:
Before resourcing more production, audit whether your real constraint is ideas or output. For most teams it’s ideas.
Use AI to turn existing assets, your reports, transcripts and customer questions, into first-draft scripts and concepts.
Keep your subject matter experts as the source of the thinking. AI drafts, experts direct.
Chapter 3: The Line Between Machine and Human
The most strategically important page in this report is the one that shows where teams welcome AI and where they refuse it.
Marketers are most open to AI handling the repetitive, behind-the-scenes work: caption, subtitle and translation generation, audio cleanup like noise reduction, and general editing such as trimming and transitions. They’re noticeably less keen on AI for the things that carry the brand: scriptwriting and messaging, voiceovers and narration, design and branding elements, and virtual presenters or AI avatars. (Wistia, 2026, p.19.)
The dividing line is authenticity. Teams are happy for AI to reduce human effort. They’re wary of it reducing the human element. As Wistia’s own head of production puts it, AI now generates the storyboard, but humans still decide whether the idea is any good.
Executive insight. The teams getting AI right aren’t asking what it can do. They’re deciding what it should do, and protecting everything on the other side of that line.
This is the single most useful idea in the report for a leadership team, because it’s directly actionable. You don’t need a sophisticated AI strategy. You need a clear boundary. Decide, explicitly, which parts of your content production AI is allowed to touch and which parts stay human. Captions, transcription, translation, format resizing, rough cuts, those are safe and high value. Your point of view, your voice, the actual judgement in your content, those stay with your people.
Get this boundary right and AI becomes pure leverage. It removes the friction that stopped your experts sharing what they know, without diluting the authenticity that made them worth listening to. Get it wrong, publish AI-generated opinion in a synthetic voice, and you scale the production of content that quietly tells customers you couldn’t be bothered.
What this means for New Zealand businesses. Write the boundary down. A simple one-page guide that says “AI yes” on the left and “humans only” on the right will do more for your content quality than any tool subscription. In markets built on relationships and trust, the authenticity you protect is the product.
Recommended actions:
Draft a one-page AI usage boundary: tasks AI handles, tasks that stay human.
Put captions, transcription, translation, resizing and rough editing firmly in the AI column.
Keep scripting, brand voice, point of view and on-camera presence firmly human.
Chapter 4: The Work Is Coming Home
One of the clearest shifts in this report is structural. AI is pulling video production back inside the business.
64% of teams agree AI is keeping video production in-house, and the most striking figure comes from agencies themselves: 74% say they’ve reduced outsourcing. (Wistia, 2026, pp.5, 25.) 27% of teams report that non-specialists, marketers without editing skills, now contribute directly to video creation. (Wistia, 2026, p.25.) The skills gap that once forced businesses to outsource is closing.
The output gains are real. 91% of teams produce more video since adopting AI, with 37% producing twice as much or more. (Wistia, 2026, p.23.) And Wistia’s own platform data found that customers using AI for behind-the-scenes workflows and repurposing saw five times more plays than those who didn’t. (Wistia, 2026, p.24.)
Executive insight. AI isn’t reducing the number of people in video. It’s increasing the number of people who can contribute to it.
It would be easy to read “production is coming in-house” as bad news for external partners, and for some it will be. But the more accurate reading is that the nature of the work is changing. Routine production is becoming something an in-house team can handle with AI support. What remains genuinely valuable from outside is the work AI can’t do: strategy, original creative thinking, the flagship pieces that carry your brand, and crucially, the judgement about what’s worth making at all.
For a leadership team, this changes the resourcing question. The choice is no longer “in-house team or agency.” It’s deciding which work belongs where. Use internal capability, now amplified by AI, for the steady stream of educational and social content. Reserve external expertise for strategy and the high-stakes pieces where craft and judgement matter most.
A note of caution from the data, though. 27% of teams say the shift to AI has created growing pains around roles and ownership. (Wistia, 2026, p.22.) Bringing work in-house without clarifying who owns what creates friction. The capability arrives faster than the process to manage it.
What this means for New Zealand businesses. Treat AI as a way to expand what your own team can do, then be deliberate about what you still send out. The businesses that win won’t choose between internal and external. They’ll combine both, with a clear line between routine production and high-judgement work.
Recommended actions:
Identify which content your in-house team can now own with AI support, and bring it home.
Reserve external partners for strategy, flagship creative and high-stakes pieces.
Clarify roles and ownership before scaling, to avoid the friction a quarter of teams reported.
Chapter 5: What Happens When Everyone Can
This report ends on the question that matters most, and it’s worth quoting the spirit of it directly. AI has shortened timelines and automated workflows. But it hasn’t answered the bigger question: what happens when everyone can produce video at scale? (Wistia, 2026, p.29.)
When production speed stops being a barrier, what makes your videos different moves up the ladder. The differentiator shifts to the things humans do best: unique ideas, a sharper understanding of your audience, and the taste and judgement to know which videos are worth making at all. AI can help you produce more. It cannot reliably predict what will resonate.
This is the same conclusion our first report reached from a different direction, and the convergence is the point. As content becomes abundant, content stops being the advantage. What becomes scarce, and therefore valuable, is genuine expertise, authentic voice and earned trust. Wistia’s CEO frames it plainly: AI should enhance, not replace, the human element, because trust and authenticity still come from people. (Wistia, 2026, p.29.)
Executive insight. When everyone can make video, the businesses that win are the ones with something worth saying.
So the strategic question for a leadership team isn’t “how do we use more AI.” Most of your competitors are already doing that, and the playing field on production is levelling fast. The question is “what do we know, and how do we make it visible.” AI is the multiplier. Your expertise is the thing being multiplied. A large multiplier applied to nothing still gives you nothing.
The cost of getting this wrong. Businesses that chase AI as a volume play will flood their channels with competent, forgettable content and wonder why it isn’t building trust. Businesses that treat AI as leverage on genuine expertise will pull quietly ahead, publishing more of what only they could say. The gap won’t be visible at first. Then it will be the whole market.
A question for your next board meeting. If AI gives every business in our market the ability to produce video at scale, what will make ours worth watching? If the answer is our expertise, the priority isn’t more AI. It’s making that expertise visible while everyone else is busy making noise.
References
Primary source: Wistia. (2026). AI Video Marketing Trends for 2026. Based on a survey of 503 marketing professionals who work with video, conducted 16 September to 1 October 2025 in collaboration with Datalily (p.33). Available at: wistia.com
Adoption and enthusiasm: 99% have experimented with AI, but only 32% are enthusiastic; 38% are open to it; 68% use AI extensively as advanced users (p.7)
Ideas are the biggest challenge (33%), tied with producing at scale (33%) (pp.5, 14)
51% use AI in ideation or to draft scripts and outlines; 42% use AI for audience research (pp.5, 18)
Hesitations centre on trust: accuracy and reliability 18%, fear of replacing human roles 17%, ethics 15%, data privacy 15%, cost only 9% (p.11)
Where AI is welcome (captions, audio cleanup, editing) versus resisted (scriptwriting, brand voice, voiceovers, avatars) (p.19)
64% agree AI is keeping production in-house; 74% of agencies have reduced outsourcing; 27% of non-specialists now contribute (pp.5, 25)
91% produce more video since adopting AI, 37% by 2x or more (p.23)
Wistia customers using AI for behind-the-scenes workflows and repurposing saw 5x more plays (p.24)
27% report growing pains around roles and ownership (p.22)
Top tools: ChatGPT 57%, Gemini 38%, Adobe Firefly 25% (p.8)
AI budgets: 49% expect their dedicated AI budget to increase; smaller-budget firms are 5x more likely to plan a decrease (p.9)
The forward view: when production speed is no longer the barrier, differentiation moves to human judgement; AI should enhance not replace the human element (p.29)
About Dark Matter. Dark Matter helps medium and enterprise organisations turn internal expertise into educational content that builds trust, strengthens positioning and shortens the path to commercial conversations. We believe every organisation already holds enough knowledge to become the obvious choice in its market. The challenge isn’t creating more expertise. It’s making the expertise you already have visible