In every comms review I’ve sat through this year, the pattern repeats. An AI draft lands in the room. Heads nod at the fluency, then someone asks the question that matters: “Would this convince the people who actually decide?” That pause is the gap between speed and substance.
Closing it is less about clever prompting and more about teaching AI what your brand stands for, who your audiences are, and how your organisation judges’ success.
The problem isn’t speed – it’s context
Generic models can write clean copy, but they don’t carry your history: message houses, do-not-say lists, escalation protocols, or the hard lessons from past campaigns. They don’t know your priority titles, how you define “quality coverage,” or what a credible proof point looks like in the UAE. Without that context, outputs feel interchangeable – easy to admire, hard to approve.
Enterprise AI earns its place when it is grounded in a “truth set” that captures how your brand works: guidelines and tone, approved phrasing, KPI definitions, the best five campaigns and the three post-post event reviews that changed how you operate. When models learn from this, first drafts land closer to usable, route-to-market plans reflect what succeeded before, and issues work benefits from precedents that are relevant, not generic.
Equally important is measurement that mirrors your standards. Volume and sentiment have a role, but mature teams’ weight for relevance: the right titles, the right audiences, the right signals of commercial impact. If the system can’t optimise to those, it’s optimising to noise. And throughout, humans stay in charge – editors and strategists call the shots; the system shortens the road to an informed draft and keeps institutional memory within reach.
Story of a typical UAE comms team
Picture a consumer brand with a bilingual footprint and a quarterly product cadence. The team loads its truth set – brand book, bilingual phrasing, coverage quality rubric, five standout launches, three difficult moments – into a secure workspace.
Planning starts with evidence: the model surfaces which messages lifted quality-weighted coverage in the GCC, which formats mapped to audience engagement, and which timings worked around peak moments in the local calendar. Drafts emerge already close to tone and cultural expectations, reducing rewrite cycles.
When an issue breaks at 3am, the system pulls relevant escalation steps and previously approved language; the first response is calmer, tighter, safer. Reporting maps directly to the KPIs leadership cares about, so budget conversations are anchored in outcomes, not output.
What changes in the real world
In practice, the gains show up fast. Planning starts with evidence: patterns across past plans, assets and results reveal which messages, formats and timings lifted performance in the GCC and which didn’t, so proposals begin informed, not guessed. Message discipline scales when tone, claims and cultural sensitivities are embedded, letting teams move faster without fraying the guardrails.
At 3am, response comes with context as escalation trees, approved language, and comparable incidents surface instantly, producing a calmer, tighter, safer first draft. And reporting earns budgets when recommendations map to what leaders value: the right titles, the right audiences, and the right commercial signals.
Ambition is good; governance is better. Put guardrails before gadgets: practise consent and custody by ingesting only what you own or are allowed to use, keeping logs, and knowing where data lives. Maintain review loops so outputs are treated as drafts and corrections teach the system your standard – not a generic internet norm. Build local fluency with a UAE layer terminology, transliterations, and cultural cues – so copy respects context across Arabic and English.
Start by choosing a single business outcome say, lifting quality coverage on two priority lines next quarter. Assemble a tight “truth pack” with brand and messaging, your five best campaigns, and clear KPI definitions.
Codify two end-to-end workflows campaign planning and issues response spelling out inputs, roles, and signoffs. Pilot with a small cross-functional squad and track two metrics: time to first usable draft and variance from brand standard. Close the cycle with plain reporting on what improved, what didn’t, and the single rule you’ll change for the next sprint.
Why this matters in the UAE, now?
This market moves quickly and expects visible outcomes. Teams that succeed blend established practice tight briefs, single sources of truth, disciplined measurement with AI that respects brand memory and local nuance. Juniors ramp faster because the playbook is encoded; seniors spend more time on judgement and stakeholder craft, less on version control.
No one needs to put any institution down to make the case—the work proves itself when drafts convert to decisions and recommendations hold up in the C-suite.
In a credibility economy, sounding right is table stakes. Being right on message, on market, on metric wins budgets and builds brands. AI helps when it understands your world. Teach it well, set strong guardrails and you’ll feel the shift where it counts: fewer rewrites, faster decisions, and outcomes you can stand behind. The point isn’t automation; it’s amplification of human judgement, accelerated by context.
By Prashant Shivram Iyer, CEO and Co-Founder – M37labs and EBIC.AI – a comprehensive enterprise performance management platform for PR and communication industry.
