The only video creation platform built for the enterprise

As we enter 2026, artificial intelligence is no longer a curiosity — it’s becoming a strategic force shaping how enterprises create, manage, and scale video content. For highly regulated industries, such as financial services, insurance, legal, and healthcare, the question isn’t whether to use AI in video creation, but which approaches actually work at scale without introducing unacceptable risk.

There are four major AI trends shaping video creation. Here’s the impact regulated organizations can expect.

Trend 1 — Traditional outsourced models using AI tools

What traditional outsourced models look like

Agencies and production partners applying AI to enhance editing, cleanup, or translation in isolated project workflows.

Why it still matters

• Good for high-production, flagship content
• Agencies can deliver better post-production results with AI assistance

The real limitation

• Costs scale with volume
• Workflows remain fragmented
• Compliance and review happen after production, not as part of the process

McKinsey proves planning is critical

This trend represents incremental improvements, not transformation, and as McKinsey & Company’s enterprise AI research shows, most organizations have not moved beyond pilots into scaled use because the underlying workflows weren’t redesigned for AI impact.

Trend 2 — Standalone generative AI video tools

What are Generative AI video tools

Text-to-video, avatars, and prompt-based creation tools that generate content quickly.

Where they work

• Rapid ideation and concepting
• Internal, low-risk content
  

Where GenAI fails for regulated enterprises

• Hard to govern or audit outputs
• Difficult to ensure consistent brand, regulatory, or compliance controls
• Minimal support for enterprise security
  

McKinsey shows GenAI needs to be integrated

McKinsey’s latest surveys show that while 88% of enterprises use AI in at least one function and generative AI experimentation is widespread, most organizations have not yet scaled these efforts or embedded them into core workflows.

This means you can generate faster, but without the right systems in place, you cannot operationalize at the enterprise level.

Trend 3 — Embedded, cloud-based AI across the full workflow

What embedded AI workflows look like

AI capabilities built directly into end-to-end video platforms — from capture through review, approval, and publishing — rather than as separate add-on tools.

Why embedded workflows matter for regulated industries

• Keeps governance, audit trails, and permissions in one system
• Reduces risk and compliance burden by design
• Turns AI from an adjunct tool into an embedded workhorse

Gartner predicts increased AI deployment

Industry analysts are pointing to this shift as critical. Gartner predicted that more than 80% of enterprises will have deployed GenAI-enabled applications in production by the end of the year, reflecting a move from experiments toward practical, embedded AI models.

Moreover, in the coming years, we’ll see task-specific AI agents deeply integrated into enterprise software, rather than as isolated pilots.

This trend aligns with broader AI adoption research showing that the highest ROI comes when AI is built into business processes and workflows, not bolted on

Trend 4 — AI-driven localization & accessibility built in

What built-in AI localization looks like

AI translation, transcription, and accessibility that is part of the core workflow — not a separate step.

Why it works

• One video asset reaches global audiences
• Meets regulatory and accessibility requirements with fewer handoffs
• Reduces reliance on external vendors and lowers cost

Why built-in localization is key

Unlike manual or outsourced models, this trend treats localization as default, not optional — an operational capability, not a special project.

The key distinction in 2026

The biggest evolution isn’t smarter AI models — it’s where AI lives and how it’s managed.

Outsourced + AI-enhanced tools help individual projects. Embedded AI in cloud workflows changes how video is created, reviewed, and scaled.

Multiple industry analysts are pointing to this shift:

• McKinsey reports most organizations are still experimenting with AI and have not yet captured broad enterprise-level impact — largely because use isn’t embedded into workflows.
• Gartner forecasts widespread GenAI adoption, but warns that many early AI projects — especially standalone agentic or hype-driven ones — fail to deliver real ROI without strategic planning and integration.
  
  

In other words, AI that is integrated, governed, and workflow-native will outperform AI treated as a point tool.

What this means for regulated enterprises

For organizations where compliance, brand integrity, and auditability matter:

✅ Build AI inside core systems — not beside them

✅ Prioritize solutions with governance, security, and audit baked in

✅ Treat video creation as an operational capability, not a boutique deliverable

✅ Measure success with business impact — not just experimental outputs

By 2026, the safe, scalable application of AI will be a competitive necessity, not a fringe advantage — but only for enterprises that embed it into end-to-end workflows, not just into isolated projects.

In video creation, tools like Socialive’s AISuite that are built directly into powerful video creation workflows truly stand out. Regulated industries will get the most out of AI in 2026 by using applied, embedded AI to supercharge workflows that are built to scale.

Key takeaways:

• Super Resolution upscales video from as low as 540p to 4K
• AI-powered feature preserves quality and clarity
• Super Resolution included in Enhance pillar of AISuite
  

Video enthusiasts and video editors know the pain of upscaling content. It’s a pain to make lower-resolution videos look good on a larger screen. You can’t just stretch a 540p video to 4K without serious blurring and drops in quality.

That changes with Super Resolution, Socialive’s newest addition to the AISuite.

Unlock 4K quality from any video

Thanks to Super Resolution, you can upscale videos to 4K with the click of a button. The new AISuite feature preserves the original quality of your content by adding pixels and increasing your video's size. This allows you to record with a lower-resolution camera (like the 720p in most enterprise laptops) and display the video on a high-resolution monitor without losing any quality.

This means old videos captured in lower-end HD, recordings from lower-quality cameras, and even files compressed to lower bitrates for livestreams can be transformed into 4K with Super Resolution.

Think of Super Resolution as a way to digitally zoom in and “blow up” your video. AI adds pixels in the background to create a much larger image without distorting your content.

The benefits of Super Resolution

OK, so that’s the magic of Super Resolution, but the benefits go well beyond the output itself. There are quite a few benefits to both presenters and editors.

No more reshoots

A lower-resolution recording used to result in an instant reshoot. Working with a lower-res camera (like the company laptop) or a presenter who forgot to record at the camera’s highest resolution meant you’d have to try again later. It usually wasn’t until the editor got hold of the file, pulled it into Premiere, and saw the recording in a tiny letterbox at the center of their project preview window.

This doesn’t work — especially if your talent nailed the take.

Super Resolution upscales the file to 4K, whether it was recorded in Socialive or not, saving all the wasted time (and the producer from an awkward conversation).

Second life for older content

The fact that content doesn’t need to have been created in Socialive to apply Super Resolution means that you can bring older videos into 2026-ready quality.

Say you have a video that came from a 2020 livestream. It was probably recorded in either 540p or 720p — 4K is too large a format for livestreams. With Super Resolution, you can now generate a 4K file of that livestream. 

This is especially helpful if there was a great piece of live content that you’d love to repurpose into other pieces of content.

Go big with large displays

Playing low-resolution videos on a big screen is always a no-no. Even if a video looks OK on a mobile device in landscape mode, it would look awful if you tried to use it on an auditorium display.

Socialive has your back in this scenario as well. Super Resolution allows you to upscale the video into a format that will look crisp, clean, and professional on the biggest stage.

What else is available in AISuite

Super Resolution is available now in Socialive’s AISuite. It launches alongside a pair of powerful Enhance features: Studio Voice and Eye Contact.

Studio Voice will give your presenters the sound of recording in a podcast studio — without the expensive equipment. Check out more details about Studio Voice here.

Eye Contact gives your presenters a more authentic look — and they don’t have to worry about the perfect take. Check out more details about Eye Contact here.

Key takeaways:

• Eye Contact automatically aligns a presenter’s gaze
• Focusing on the camera helps presenters connect with the audience
• Studio Voice included in AISuite
  

Sometimes it’s tough to look and feel your best in videos, especially if you have a habit of looking off-screen or are locked in reading a teleprompter.

Eye Contact is here to help.

The AI-powered feature works behind the scenes to keep your eye level in line with your camera. So if your eyes are darting all over the place, we can fix it!

Eye Contact is just one of the many new features prominent in Socialive’s AISuite — here’s how it works.

Keeping your eyes on the prize

For talking head videos with a single speaker, it goes a long way when the presenter looks into the camera. We feel more comfortable with someone who looks us in the eye — we feel like we can trust that person a bit more.

But maintaining eye contact can be tough. For many people, continuous eye contact feels awkward or just isn’t possible. You also have to consider that someone might be reading from a teleprompter or referring to their notes. None of those should be a reason to scrap an otherwise great recording.

Eye Contact cleans up your recording to add that little extra touch of humanity — while using AI.

The great thing about Eye Contact is how subtle it actually is. While the above stills show an obvious moment when the speaker looks away, over the course of a longer video, it feels more natural. You’d hardly notice it if you weren’t looking, but Eye Contact guarantees your speaker will continue to address your audience directly.

Eye Contact in action

Notice in the above video how the speaker's eyes remain on the camera — positioned above his laptop — even as he reads from the teleprompter located in the middle of his screen. He’s an energetic speaker, so Eye Contact guarantees that all of his energy is directed towards the audience.

The benefits of Eye Contact

So, outside of subtle adjustments, how does Eye Contact help video creation? Well, if you’ve ever worked with a nervous speaker, you’ll feel the impact immediately.

Time savings

There’s no need to worry about reshoots because of darting eyes. Nervous speakers tend to look across the screen, trying to find something comfortable they can latch onto.

Likewise, if you have a subject-matter expert or speaker who is trying to nail precise messaging, you may want them to read from a teleprompter. But reading from a prompter is an art form — most people will end up reading line by line, their eyes cruising along and pinging back and forth like a typewriter.

Eye Contact fixes that automatically.

What else is coming with AISuite

Eye Contact is just one of the major new features launching in AISuite.

Studio Voice will give your presenters the sound of recording in a podcast studio — without the expensive equipment. Check out more details about Studio Voice here.

Key Takeaways

• Financial services now operate in a video-first world, but video difficult to scale
• Traditional production essential for high-end content, but struggles to meet modern demands of volume and speed
• Generative AI introduces security, compliance, and brand risk for regulated firms
• Embedding applied AI into enterprise video workflows enables safe scale, consistent quality, and measurable ROI
• 2026 signifies shift for AI to transform video into a strategic enterprise capability

The world is video-first, expectations have changed

For decades, financial services firms have known that video builds trust. It humanizes complex information, enhances credibility, and helps advisors and leaders connect in moments that matter.

What has changed is not belief in video; it’s now an expectation that firms use video.

Clients, advisors, employees, and regulators now expect:

• More frequent communication
• Faster response to market and regulatory change
• Greater executive and advisor visibility
• Authentic, human connection — delivered consistently

In a video-first world, more video drives more trust, greater visibility, and faster velocity across the enterprise.

Yet most financial services organizations are still figuring out how to design and implement video creation models built for a social-first, digital native world.

Why traditional production still matters, but can’t scale alone

Traditional video production — whether delivered through internal studios or trusted agencies — remains critical in financial services.

Traditional video production is intentionally designed for:

• High-impact moments
• Flagship storytelling
• Maximum brand control
• Reputation-critical communications
  

For these moments, higher cost, longer timelines, and rigorous review are not inefficiencies — they are the right tradeoff.

But traditional production was never designed to support:

• Daily advisor communication
• Ongoing executive visibility
• Field enablement and marketing
• Learning and communication at scale

The demand for video continues to grow, but this has exposed a negative relationship between the volume and velocity of video production. When demand goes up, so does the time it takes to get each video out the door. The resources required to meet demand also go up.

This is not a talent problem. It is a workflow mismatch.

This is a workflow problem, not a video problem

Historically, firms that tried to scale beyond traditional production resorted to stitching together fragmented tools: recording here, editing there, routing approvals manually, and managing compliance through spreadsheets and email threads.

The result:

• Slow time-to-market
• High cost per video
• Inconsistent quality
• Heavy reliance on specialists
• Increased compliance risk

Video worked, but it didn’t scale.

This is the gap that Cloud-based video platforms like Socialive began closing: providing centralized, secure environments to capture, collaborate, and publish video with built-in governance.

Still, manual steps remained. And in regulated industries, manual steps are where risk and cost accumulate.

The dual-workflow reality of enterprise video

By 2026, leading financial services organizations recognize a simple truth:

One video workflow is no longer enough.

Two workflows now CAN coexist — each serving a distinct purpose.

• Traditional Production
  
  • High-profile moments
  • Studio or agency-led
  • High production value/cost
  • Long production cycles
  • Manual review processes
• Embedded, Applied AI in Workflow
  
  • Everyday communication
  • Advisor-, employee-, and exec-led
  • High volume, cost-efficient
  • Fast time-to-market
  • Compliance built-in

Traditional production remains essential. But the future of enterprise communication depends on embracing a new workflow — one designed for scale without sacrificing quality or compliance.

This is where AI becomes transformational.

Standalone generative AI is not the answer

In an effort to close this gap, many organizations are exploring standalone generative AI tools.

These tools deliver on speed and lower costs vs. traditional production, but that speed comes with very real risk for regulated industries.

Generative AI introduces fundamental challenges:

• Likeness and biometric misuse. Using likeness of real faces and voices in public GenAI tools erodes authenticity and client trust.
• Unreliable and biased outputs. GenAI can generate confident, on-brand content that is factually wrong, unsubstantiated, or biased — creating regulatory, suitability, and conduct risk.
• Data leakage and “shadow AI.” When employees paste scripts, client details, or internal insights into public tools, non-public personal information (NPPI) and IP can be retained and reused by external models with no way to control or audit that data.
• Higher-risk approvals and longer timelines. Because outputs are unpredictable and firms remain fully accountable under FINRA and SEC rules, compliance must review GenAI-assisted content more deeply, increasing approval burden rather than reducing it.

For regulated enterprises, speed without governance isn’t a desirable system — it’s a risk.

This creates a false choice — control without scale or scale without control.

The solution: applied AI embedded in the video workflow

The path forward for financial services isn’t more experimentation with AI tools. The way forward for the enterprise is to use applied AI embedded directly into the video creation workflow. This approach is purpose-built for regulated environments because it delivers predictability instead of variability, and control instead of novelty.

Embedded, applied AI works because it is designed to:

• Enhance real human video, not fabricate it
  Applied AI improves the quality, clarity, and consistency of video created by real advisors and executives, preserving authenticity and trust rather than introducing synthetic likenesses or deepfakes.
• Produce consistent, reviewable outputs
  Applied AI operates within defined parameters. Its outputs are repeatable and expected, allowing compliance teams to review once, standardize oversight, and approve faster — instead of re-evaluating unknown behavior every time.
• Keep data fully governed and auditable
  Because AI is embedded inside enterprise-grade systems, sensitive scripts, communications, and NPPI remain within controlled environments with full visibility, logging, and accountability.
• Reduce compliance friction instead of increasing it
  Predictable AI behavior enables automation of disclosures, policy checks, and routing — turning compliance from a bottleneck into an integrated part of creation.
• Scale everyday video without scaling risk
  Applied AI allows organizations to dramatically increase video output without increasing staff, cost, or exposure. This comes by removing manual, repeatable steps from the editing, enhancement, and review stages.

In regulated industries, the value of AI is not creativity — it’s predictable execution at scale.

Applied AI embedded into the video workflow transforms video from a risk-managed exception into a trusted, repeatable enterprise capability.

Why 2026 is the inflection point

In 2026, AI moves from experimentation to infrastructure.

By embedding AI across the entire video lifecycle — from capture and enhancement to compliance, approval, and distribution — financial services organizations can finally scale everyday video without compromising trust.

Video is no longer limited by production capacity. It becomes an enterprise capability

Enterprise video trends shaping financial services in 2026

1️⃣ AI becomes the connective tissue of video workflows

AI now spans the full lifecycle of video creation, replacing fragmented tools and manual handoffs with a unified workflow.

Data: Deloitte reports that the vast majority of financial services executives now consider video essential for both client and employee communication.

Impact: End-to-end AI workflows can drastically reduce production time, enabling teams to focus on insight and strategy rather than mechanics.

2️⃣ ROI replaces experimentation

The conversation around AI has shifted from pilots to performance.

Data: McKinsey reports that embedding generative AI into enterprise workflows can deliver 30–50% productivity gains and reduce costs by 20–40%.

Impact: Video becomes a predictable ROI driver — not a discretionary spend.

3️⃣ Everyday video becomes enterprise-ready

Video is no longer reserved for campaigns or marquee moments.

Data: HubSpot reports that most consumers say seeing an advisor on video increases trust.

Impact: Advisors, executives, and employees can now create frequent, high-quality, compliant videos — transforming video into a daily engagement capability.

4️⃣ Compliance is embedded, not bolted on

Compliance has historically been the primary constraint on scale.

Data: FINRA reports a sharp increase in digital content reviews in recent years.

Impact: AI-driven disclosures, policy checks, and automated routing reduce review cycles while strengthening governance.

5️⃣ Quality enhancement happens in real time

Credibility in financial services is visual as well as verbal.

AI now enhances video and audio automatically by improving lighting, clarity, sound, framing, and gaze — without studio intervention.

Impact: Every advisor and executive looks and sounds professional, creating consistency and confidence at scale.

6️⃣ Human + AI co-creation becomes the standard

The future isn’t automation alone — it’s collaboration.

AI handles enhancement, editing, compliance routing, and versioning while humans focus on storytelling, insight, and authenticity.

Impact: Teams create more video, more often, with higher impact and far less friction.

The bottom line: video is a strategic solution

Traditional production will always play a critical role in financial services. But it cannot carry the full weight of a video-first world on its own.

In 2026, firms that succeed are those that complement traditional production with an agile, AI-embedded video workflow, enabling everyday communication at scale, without compromising trust, compliance, or quality.

This is how video advances beyond just a medium — video becomes a strategic enterprise capability built for the speed of trust.

See examples of how financial services leaders are operationalizing compliant video at scale on our page: Socialive for financial services.