AI in B2B Video: Top Takeaways for B2B Marketers Using AI

Originally published in 2025, we're revisiting this research to see how B2B marketers are actually applying these insights in 2026.

Last year, we surveyed 500+ B2B marketers about AI in B2B video. The data showed clear adoption patterns, but the real story is unfolding now. Marketing teams that moved quickly on AI tools are seeing 3-10x engagement gains. Those that waited are still stuck in the same, prolonged video creation cycles they were running in 2024.

Leaders who treated AI-powered video as a productivity win are pulling ahead, and the gap between those teams and the ones still evaluating is starting to show.

In the State of AI in B2B Video Report, we documented how 91% of marketers already use AI in video workflows, with 85% reporting cost savings. Now we're tracking which specific workflows deliver the highest ROI. 

Below, we break down what the 2025 data predicted and what 2026 execution is proving. Read the full 2025 report, and learn how teams are turning these insights into repeatable workflows.

The 2025 survey captured baseline adoption rates. Here's what stood out:

• 91% of marketers use AI in B2B video workflows. The important thing now is that you're using AI for the right tasks. 
• 85% report cost savings. Cost savings matter, but only when paired with better output. The teams seeing real ROI are the ones cutting outsourcing costs while improving high-quality output.
• 90% of marketers are repurposing video into other assets. The ones seeing the biggest gains are repurposing smarter, turning a single recording into weeks of content across channels. 
• 74% of teams reduced outsourcing after consolidating tools. Say goodbye to fragmented, disparate tools. When your workflow lives in one platform, everything moves faster.
• 37% of marketers still cite lack of expertise as a top barrier to AI adoption. The fix is building clear frameworks for when to use AI and when to rely on human expertise.

Saving time means nothing if you're producing more content that doesn't drive pipeline. The teams winning in 2026 are the ones who paired AI adoption with clear video strategy and measurement frameworks that tie video to revenue, allowing them to optimize over time.

The 2025 data showed 91% of marketers using artificial intelligence somewhere in their workflows. That’s incredibly high adoption, but most teams were using AI for surface tasks: cleaning transcripts, drafting blog outlines, maybe pulling a few clips. 

The real opportunity is workflow redesign, especially for video production. The teams that reduced outsourcing by 74% didn't just save budget; they gained speed and control, often leveraging tools like ChatGPT for initial content drafts. If you can ship a highlight reel two hours after an event instead of two weeks later, you're operating in a different market reality than competitors still waiting on contractors.

C-suite buy-in hit 94%, but buy-in only counts when it's backed by budget and integrated into pipeline strategy. If your leadership still treats video as a "nice to have" sitting in the events budget rather than a primary channel with clear metrics, it isn't really buy-in yet.

Where AI delivered the most value in 2025:

• Content creation (blogs, social media posts, etc.)
• Analytics and reporting
• Video production
• Content repurposing
• Email marketing

Three hours weekly adds up fast, but the compounding effect matters more. When you turn one webinar into 10-15 derivative assets (social clips, blog posts, email snippets, LinkedIn carousels), you're building a content engine that runs on captured insights instead of starting from scratch each week.

We recommend auditing your last webinar. How many assets did you create from it? If the answer is fewer than eight, you're leaving distribution on the table.

MAICON (Marketing AI Conference) is a great example of what's possible when you rebuild operations around AI. By streaming their main stage sessions directly into Goldcast, the team used Content Lab to produce same-day session notes for 20 sessions across two days — and grew average social media interactions by 400%.

According to the report, 85% of B2B marketers saved significant costs on video production after incorporating AI. And teams aren't just pocketing the difference. Instead, 79% are shifting spend from outsourcing to AI tools and plan to increase that investment over the next three years.

Budget allocation varied:

• Half of teams allocate 10-25% of marketing budget to video
• 29% allocate less than 10%
• 17% allocate 26-50%

Look at the pattern beneath these percentages. Marketing leaders are treating video budgets as operational infrastructure, rather than project-based spending. Instead of paying per asset, they're investing in platforms that generate multiple assets from single recordings.

One session can produce podcasts, customer testimonials, explainer videos, blog posts, social media content, and webinar talk tracks — all from the same source material. That multiplication effect is exactly what justifies the investment.

Outsourcing still has a place for high-production filming and specialized post-production work. But when your team can handle distribution, repurposing, and most editing internally, you're reserving contractor budgets for work that genuinely requires outside expertise.

Calculate what you currently spend on contractors for video editing, clip creation, and content repurposing. If that number exceeds the cost of an AI video platform, and you're still bottlenecked on output, the ROI case makes itself. Get detailed budget breakdowns in the full report or calculate your potential ROI.

Repurposing delivers higher ROI than creating new content from scratch. The 2025 data backs this up.

90% of respondents were repurposing video content into other assets, and 79% said AI tools made that process more efficient. Turning a single webinar into 10–15 derivative pieces (clips for social media, blog posts, email snippets, audiograms) multiplies your reach without increasing your workload.

AI-generated clips and text assets saw explosive growth in 2025: video clips generated via AI jumped 2,903% year-over-year, while text assets grew 11,462%. That's a fundamental shift in how B2B video marketing content gets made.

AspenCore is a great example of what this looks like in practice. Before Content Lab, producing one video clip took about two hours. After adopting it, that time went down to five minutes. Plus, one LinkedIn post created through Content Lab outperformed an entire 39-post static graphics campaign.

Start with your most recent webinar or customer interview. Pull a few key moments, turn each into a 60–90 second clip, and publish them as LinkedIn posts over the next week. Track engagement against your typical text-only posts. We think the results will speak for themselves.

The 2025 data revealed that 74% of B2B marketing teams reduced their need to outsource after adopting AI video tools. This points to something bigger than cost savings: workflow consolidation.

Prior to AI, most teams stitched together 3-5 separate tools: one for recording, another for editing, a third for hosting, a fourth for repurposing, and a fifth for analytics. The fragmentation created predictable problems. Data silos made ROI measurement nearly impossible. Manual handoffs stretched turnaround times to weeks. Version control became an absolute headache.

Consolidation solves all of these problems. When your workflows all live in one place, you eliminate the friction of platform-hopping. You can execute faster, analytics are unified because all data shares a single source, and your team only has to master one system instead of five. 

Goldcast's integrations with Salesforce, HubSpot, and Marketo also mean engagement data flows directly into your CRM in real time, so follow-up sequences trigger automatically rather than sitting in a to-do list.

To fix fragmented workflows, map your current workflow. Count how many tools you're using from recording through distribution. If that number exceeds three and you're spending more than a couple of hours per week on handoffs, consolidation will deliver meaningful time savings.

Last year, 9% of marketers reported avoiding AI tools entirely. Other teams who were using AI were worried about where things were heading.

Survey respondents flagged specific issues:

• "AI is not as smart as it's billed. It constantly makes mistakes that a human would not."
• "We believe AI is not able to tell OUR story the way it needs to be told."
• "Our services are technical and too many mistakes can be made."

A year later, those concerns turned out to be well-founded. The market is now flooded with AI-generated video content, and teams that adopted AI without editorial standards are producing generic clips that get scrolled right past. The teams that stand out are the ones that set quality standards before they scaled.

Top challenges identified in the survey:

• Lack of expertise: 37% of marketers cite a lack of expertise as a major challenge in adopting AI for video production.
• Cost and buy-in barriers: High costs (34%), limited tool availability (29%), and lack of leadership buy-in (24%) remain top barriers to AI adoption.
• Difficulty scaling: 36% say video takes too much time, while 35% say the size of their production team limits their ability to scale.

Let’s address these in order. First, the expertise gap remains the defining challenge. Teams that struggled in 2025 are still struggling now because they never built clear frameworks for when to use AI versus when to invest human effort. 

If you're scaling AI video production in 2026, establish editorial standards first. Define what "on-brand" means for your video content, and set quality thresholds that clips must meet before publication. You should also build review processes that catch AI mistakes before they damage your credibility.

Second, the cost and buy-in barriers from 2025 have decreased as platforms matured and early adopters demonstrated ROI. If your leadership still hesitates on budget, show them engagement data from small tests rather than asking for large upfront commitments.

Third, the scaling challenge usually comes down to workflow design rather than team size. Most teams that struggle to scale video production are doing it manually. When you replace those manual steps with AI-powered tools, one person can do what used to take three. That’s how you scale without adding new team members. 

It's worth underscoring that human-generated ideas remain more relatable than AI outputs. Use AI for the tedious work like editing, formatting, repurposing. Reserve human effort for creative storytelling, strategic positioning, and quality control. 

A year ago, 84% of marketers said they believed AI would be critical to their marketing strategies over the following 1-3 years. That timeline puts us squarely in the adoption window now.

If you're still evaluating AI video tools, you're no longer early, but the good news is that the playbook is clearer now than it's ever been:

Begin with repurposing. Audit your existing video library before creating new content, and recognize that existing webinars, event recordings, and customer interviews represent ROI you've already paid for. Extract value from what you have before investing in new video production.

Map your current workflow. Document where handoff delays and data gaps slow your process. If clips take two weeks to reach social media, or if engagement data lives in three separate tools, you’ve got your targets. 

Be sure to balance AI and authenticity. Reserve automation for tedious execution work like editing, formatting, distribution. Your team should always own storytelling, positioning, and brand voice. Teams that reverse this produce generic AI-generated content that fails to differentiate.

Finally, measure what matters. Build measurement frameworks that connect your B2B video content to actual buying-stage movement. Goldcast's Analytics and Dashboards make it possible to track both, from in-event behavior all the way through to influenced pipeline, without stitching together data from multiple sources.