By Khaled Nuseibeh, Hala CEO

Artificial intelligence has quickly become part of the marketing conversation. New tools promise faster production, lower costs and endless variations of creative output. But for companies operating in real-world services, the technology itself is not the most important question. The real question is whether it helps communicate what actually happens on the ground.

In mobility, that distinction matters. When someone books a taxi, the experience is defined by whether the car arrives when it is supposed to. If it does not, no campaign can compensate for that. That reality shaped how we approached Count on Hala, a recent campaign designed to support new user acquisition while reflecting how the service operates across Dubai every day.

Hala runs hundreds of campaigns each year across different customer segments. In a fast-moving, highly competitive market like Dubai, speed and adaptability are essential. Artificial intelligence provides companies with a way to move faster, scale creative output and respond to changing market dynamics without losing clarity or relevance.

The campaign used AI across the creative execution, generating visuals, layouts and voiceovers for content deployed across out-of-home screens and targeted digital channels. However, the strategic direction, messaging framework and approvals remained firmly with our team.

Rather than positioning AI as the centre of the campaign, we focused on communicating measurable operational insights such as pickup speed, fleet scale and reliability. Messages such as “90% of taxi pickups in under five minutes” or “Meeting in 20 minutes? Taxi in 3” translated everyday service performance into clear, relatable moments.

Early campaign indicators reinforce the impact of this approach. In the first month following the launch, Hala recorded a 27.8% uplift in bookings, 19.2% increase in new users, and a click-through rate approximately 5x higher than previous campaigns, reflecting stronger engagement with the campaign messaging and visuals.

AI allowed these insights to be translated into creative assets quickly across multiple formats. But the technology itself was not the story. Running the campaign highlighted several practical lessons about how AI fits into busy marketing teams today.

1. Build campaigns around operational performance, not creative concepts

AI will amplify whatever information it is given. If the underlying service is inconsistent, the campaign will expose that quickly. For this campaign, the creative concept began with operational data, pickup speeds, fleet capacity and everyday travel scenarios across Dubai. These insights formed the foundation of the messaging rather than an abstract creative idea. In sectors such as mobility and transport logistics or aviation, marketing cannot exist separately from operations. Customers experience the service within minutes of seeing the campaign. If the message and the experience do not match, a brand’s credibility will quickly disappear.

2. Use AI to produce campaigns faster without changing the strategy

The campaign began with a simple idea: reliability. In a city like Dubai, where people are constantly on the move, everyday convenience matters. Artificial intelligence helped the team turn that idea into campaign content much faster than traditional production would allow. Instead of coordinating multiple shoots, locations and long approval timelines, operational insights could be turned into clear messages quickly. Lines such as “Meeting in 20 minutes? Taxi in 3” could appear across digital screens, social media and billboards within hours rather than weeks. The team still defined the message, tone and brand standards, while AI helped speed up how quickly those ideas could be produced and shared across the city.

3. AI creative for billboards and outdoor advertising still needs technical expertise

One common misconception about AI-generated creative is that it removes complexity from production. In reality, it often introduces new challenges. Early AI-generated visuals worked well for digital placements but were not always suitable for large-format outdoor advertising. When scaled for outdoor displays, some images were grainy and lacked the resolution required for high-visibility formats.

Achieving the required quality meant using several paid subscription tools and refining outputs across multiple stages. AI can accelerate creative exploration, but production expertise remains essential to ensure the final output meets the standards expected of large-scale advertising.

4. AI marketing still requires strict legal oversight and brand governance

The faster content can be produced, the more important governance becomes. Before launching the campaign, strict internal guidelines were established around how AI could be used. These covered cultural sensitivity, representation and compliance with UAE advertising standards.

All platforms used were vetted to ensure appropriate commercial usage rights, and every output was reviewed in collaboration with legal teams before publication. Regardless of which tools are used, the brand remains responsible for everything that appears in a campaign.

5. AI allows marketing teams to focus on insight-led storytelling rather than asset production

The most noticeable shift from the campaign was internal. Traditionally, marketing teams spend significant time producing individual creative assets. AI changes where that time is spent, instead of focusing on manual production, the team concentrated on identifying the insights that matter most to our customers; people who are moving around the city, whether its short journeys or tight schedules, their need is for reliable transport in everyday situations.

Artificial intelligence then made it easier to translate those insights into multiple creative executions across different formats. For a platform operating in a competitive market and running campaigns across multiple audiences throughout the year, that shift can make a meaningful difference.

In almost every sector, AI is already moving from experimentation into everyday systems across the region. Airlines use it to manage disruption. Logistics companies use it to anticipate congestion. Governments use it to plan infrastructure and transport networks.

Marketing will inevitably follow a similar path. AI will not replace traditional production or human creativity. Photography, filmed content and real-world storytelling remain essential, particularly when authenticity and emotional connection to your customer matters.

While we continue to embrace AI within our creative processes, it has not and cannot replace the creative agencies we work with. Human intervention, intuition, and creativity remain at the core of everything we do.

What AI can do is remove some of the friction in how campaigns are produced, allowing teams to respond faster while maintaining accuracy. Dubai is often described as a testbed for new technologies. In reality, the city simply demands that systems work under pressure, across different languages, cultures and moments of high demand. If an AI-enabled campaign can operate effectively in that environment, it is likely to work anywhere.

For companies exploring AI in marketing, the lesson is straightforward: focus on operational reality first. Technology should support how the business performs, not distract from it.

Across the GCC, the real question is no longer whether organisations are using AI, but whether AI is actually doing the work. Most deployments still sit at the surface, assisting employees without changing how execution happens. AI is now moving beyond individual task support into structured workforce roles, where it carries responsibility across workflows, follows business logic, and executes within real enterprise systems. Gartner projects that by 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024.

In the GCC, organisations are under pressure to scale faster, maintain service continuity, and improve cost discipline without adding unnecessary operational complexity. Digital Dubai recently launched the AI Workforce Transformation Program (AI+) to help train 50,000 government employees for an AI-ready workforce.

Shaffra, an AI research and applications company building autonomous AI teams for enterprises and governments, is already deploying this model across the region. The company highlights five business functions where AI is actively executing work inside organisations.

1. Customer service

One of the first functions to absorb AI as a workforce layer is customer service due to high-volume, time-sensitive, process-intensive requests every day. Autonomous AI Teams can handle routine queries across chat, email, WhatsApp, voice, and ticketing platforms while classifying urgency, routing cases, escalating exceptions, and updating records in real time. They can also pull customer history and identify recurring patterns linked to churn, complaints, or policy friction. Customer service teams have handled up to five times more queries through autonomous execution. This shifts customer service from a reactive support function into a continuously operating system that can absorb demand without linear increases in headcount.

2. Revenue operations

A more meaningful transformation is now happening in the commercial engine. Autonomous AI Teams can continuously monitor pipelines, detect stalled deals, flag procurement delays, identify pricing sensitivity, and improve forecast quality using live activity signals rather than backwards-looking updates. They can also support CRM hygiene, proposal workflows, approval chains, and internal coordination between multiple departments around account progression. PwC’s 2026 findings show that 45% of UAE CEOs are already using AI in demand generation across sales, marketing, and customer service. Leadership gets a clearer view of where revenue is genuinely at risk, where process friction is slowing conversion, and where intervention is needed before exposure turns into loss.

3. Human resources

In HR, recurring administrative work, policy enforcement, documentation, and employee support often follow structured paths that can be executed better when properly designed. Autonomous AI Teams can screen applicants, coordinate interviews, manage onboarding steps, answer routine employee questions, and flag missing approvals or documentation before delays compound. They can also support review cycles, workforce planning, and identify bottlenecks and process gaps early. Recruitment timelines are reduced from weeks to hours, while HR leaders review high-impact decisions.

4. Finance and accounting

In the financial department, AI needs to operate reliably within structured processes without compromising strict governance. Autonomous AI Teams can process invoices, support AP and AR workflows, follow up on missing information, review expenses against policy, and coordinate reconciliation and month-end close activities. They can also surface anomalies, identify unusual transaction patterns, and flag control exceptions for review. AI helps increase throughput while preserving auditability, approval discipline, and visibility across the finance operation. This allows finance teams to increase processing capacity without compromising control, shifting their role to oversight from execution.

5. Business operations

The most strategic application sits in business operations – where delivery, dependencies, handoffs, service levels, and internal performance come together. McKinsey’s finding that 84% of GCC organisations have adopted AI in at least one business function suggests the region is already moving into broader integration. Within operations, Autonomous AI Teams track workflows across systems, detect bottlenecks, monitor KPIs and SLAs, identify resource overload, and trigger interventions before issues become delivery failures. They can also support oversight by summarising status, escalating likely delays, and coordinating cross-functional execution in real time. Across Shaffra deployments in the Gulf, organisations have reported up to 80% reductions in operational costs and more than 2 million manual work hours saved monthly.

Walk into any modern content setup today, whether it’s a podcast studio, a corporate webinar room, or a hybrid event environment, and you’ll see a familiar pattern, one that reflects how fragmented the content production stack has become.

A microphone connected to an interface.
An interface connected to a laptop.
A laptop running multiple layers of software to mix, switch, stream, and record.

It works, but it’s rarely seamless.

Because the biggest challenge in content creation today isn’t access to tools, it’s understanding how they all fit together.

The Real Problem: Too Many Tools, Too Little Clarity

The rise of podcasting and video content has created a new kind of friction. Users are no longer asking what they can create; they are asking how to make the tools work together.

Recording audio separately, syncing video later, transferring large files to high-end machines, and relying on multiple software layers have become the default workflow. It works, but it is inefficient, expensive, and prone to failure.

The expanding ecosystem of devices, features, and formats has made even basic setup decisions unnecessarily complex.

When it comes to products from RØDE, users & creators already recognize the product’s potential to simply clarify and help elevate the overall workflow experience.

From Tools to Unified Systems

This is where the shift begins to stand out.

What we are seeing is not simply the addition of new features, but the consolidation of functions.

Mixer. Recorder. Audio interface. Video switcher. Stream encoder.

What traditionally required a stack of hardware and software is now being brought into a single console environment.

For creators, that simplifies production.

For enterprises, it changes how content infrastructure is designed.

As this shift gains momentum, it is also being acknowledged at a leadership level.

“Real innovation isn’t about adding more; it’s about removing friction and enhancing workflows.

With the introduction of platforms like the RØDECaster Video, we’re starting to see audio and video unified in one system, unlocking faster, more focused creative output.”

Kalinda Atkinson,
Global Marketing Director, RØDE

Why This Matters Beyond Creators

This shift is not limited to podcasters or streamers. Enterprises are increasingly building in-house content studios, executive communication channels, internal video platforms, and hybrid event capabilities as part of their broader communication strategy.

In these environments, complexity quickly becomes a bottleneck. Multiple tools often translate into longer setup times, increased points of failure, and a growing dependency on technical operators to manage what should ideally be straightforward workflows.

A unified system begins to reduce that friction, allowing teams to focus less on managing the process and more on the output itself.

The End of the Laptop-Centric Setup

One of the most significant changes is subtle: the laptop is no longer central.

With recording, streaming, and switching built directly into the console, content can now be produced without relying on external software or intermediary platforms. Audio and video routing happens natively within the system, removing the need to manage multiple layers of tools.

This, in turn, reduces reliance on tools like OBS Studio and lowers the need for high-performance machines in the production chain.

Broadcast Capabilities, Simplified

Features that were once limited to broadcast environments are now being integrated directly into compact systems. Capabilities such as multi-camera switching, ISO recording with separate tracks for each input, audio-based automatic switching between speakers, and network-driven video workflows like NDI are no longer confined to high-end production setups.

For enterprise teams, this translates into professional-grade production without the need for dedicated control rooms or complex broadcast infrastructure.

Modularity Signals Long-Term Thinking

Another important shift lies in how these systems evolve over time.

With expansion options such as adding video capabilities to existing audio consoles, RØDE is enabling a more modular approach to production. Instead of replacing entire systems, users can extend them based on their needs.

This becomes particularly relevant for organizations that may begin with audio-first content using consoles such as the RØDECaster Duo or RØDECaster Pro II, gradually expanding into video production with consoles such as RØDECaster Video, RØDECaster Video S, or even the RØDECaster Core, and scaling internal media capabilities over time. The result is a more flexible investment model that reduces upfront costs while supporting long-term growth.

A Shift in the Competitive Landscape

On the surface, this still appears to sit within the audio hardware category. In practice, however, it competes with something far broader.

As these systems begin to handle capture, processing, and output within a single environment, they start to overlap with production software ecosystems, video switching platforms, and content workflow tools.

The implication is clear: when orchestration happens within the system itself, the need for external layers begins to diminish.

The Opportunity Ahead

As the layers of complexity fade, creators will have more time for creative storytelling and less time worrying about the setup.

The new products and technology from RØDE not only remove setup barriers, but they also enable creators & enterprises to operate at a full professional standard, accelerating both the creativity and innovation ecosystems.

Srijith KN covers enterprise technology, media infrastructure, and digital transformation across the Middle East.