It uses your own work
Real documents and real tasks, so people leave with a skill set they have already used on their own job. That is practical AI implementation, the part that can turn into a competitive advantage.
AI
AI training in Dubai, built on your team's own work
Your people already use AI tools like ChatGPT, often on personal accounts and sometimes with client files. Training that works starts from that reality, not from theory about how the models work.
Tell us what you need
A senior person reads this and replies within one working day. No call centre, no drip sequence.
The form did not load.
It is our end, not yours. Email us instead and it reaches exactly the same person.
Support@adnika.comPlatforms & clients
The stack we work in, the clients we keep
The platforms we build and run campaigns in, and the clients whose numbers we publish with their names on. These are tools we use, not partner badges.
The problem
An introduction to artificial intelligence
Ninety minutes on transformers, machine learning and prompt engineering, given to a room of people who wanted one answer. Were they allowed to paste a client brief into a chatbot, and if not, what could they use instead? Nobody answered that, and nobody's Monday changed.
Why most training courses on AI do not land
It teaches AI technologies, not the task
People need practical help with their own job and a clear view of where the risks are. General AI education and AI fundamentals are interesting, but neither changes how anyone works on Monday.
It ignores that people are already using it
Staff already use AI tools at work, usually on personal accounts and sometimes with material that should never leave the building. Training that starts from zero misses the real risk sitting in front of it.
There is no policy behind it
People leave enthusiastic, with no idea which tools and uses are sanctioned. Without written rules nobody can say what responsible AI use means at your company, so usage stays informal and unmanaged.
It is one session for everyone
Finance, marketing, operations and legal each have different jobs for AI and different risks to manage. A single session for everyone ends up serving whichever group the trainer has worked with before.
What is included
What the training covers
Every session is practical training in generative AI, aimed at one role and built on your own material. The learning objectives are agreed in advance.
Current usage audit
We find out what people already do with AI, on which tools and with what material. It is gathered without blame, because the point is to find the exposure and the real opportunities, not to punish anyone.
Role-specific sessions
Teams whose work differs get separate sessions, because marketing, sales, operations, human resources management and legal each apply AI differently. Each role also has its own list of things it must never paste into a chatbot.
Hands-on training on your own work
Teams work on real documents, real briefs and real tasks from their own jobs. The practice covers real-world applications, not a demonstration exercise.
Where it is unreliable
We teach where generative AI fails as plainly as where it helps: invented facts, confident wrong answers, false citations and arithmetic. Staff who understand these failure modes stop mistaking fluent output for high-quality work and get better results from any AI model.
Data handling rules
What may go into which tool, from a healthcare team's patient notes to commercially sensitive client files. The tools are global products but teams across government and the private sector still need rules of their own. We also cover the difference between a consumer account and an enterprise one.
Acceptable use policy
A written policy short enough that people read it, delivered with the training rather than promised afterwards. It sets out a few AI principles in plain words, for your managers to sign off.
Verification habits
How to check AI output before anyone relies on it. This habit separates staff who benefit from these tools from those who create problems. We hold our own client reporting to the same rule. The Adnika Dashboard: one live view of a client's ads, analytics and CRM data, with AI recommendations reviewed by the strategist.
Champion and follow-up
One person per team goes deeper, takes the more advanced AI questions and joins the follow-up session a month later. That session covers what people tried and where they got stuck.
What we leave out
We skip AI and machine learning (ML) theory, Python, computer vision, natural language processing and predictive analytics. Building AI systems is AI engineering, a subject for an AI engineer or a university course. Nobody needs to understand how AI works inside, pick up engineering skills or learn AI from scratch to use these tools well.
Technology
The AI tools and skills your teams practise
The generative AI tools your people already have access to, the tasks each role uses them for, and the governance around them.
Tools
The assistants your team has or should have.
- ChatGPT, Gemini and Microsoft Copilot
- Consumer versus enterprise accounts
- AI-enabled features in your software
- Document and collaboration tools
Application
Different for each role, and never a substitute for design skills.
- Drafting, editing and creative work
- Research and data analysis
- Image and video generation
- Meeting notes and document processing
Risk
Taught as explicitly as the benefit.
- Invented facts and false citations
- What may go into which tool
- Security and client confidentiality
- Disclosure to clients and colleagues
Governance
Delivered with the training.
- Acceptable use policy
- Approved tool list
- Escalation route for questions
- Review process for output
How we work
How training is delivered
First we find out what is already happening, then we teach the specific jobs. Delivery methods, the course structure and the schedule are agreed with you before anything starts.
Without blame
We ask what people already do with these tools and with which material. The questions are anonymous and asked without blame, because the exposure you do not know about is the one that matters.
- Anonymous usage survey
- Tools currently in use catalogued
- Material being submitted identified
- Immediate risks flagged to management
On real tasks
Each team practises applying AI to its own work and its own documents. Every role gets its own use cases and its own risks, instead of one curriculum for the whole company.
- Sessions built per role
- Real documents and briefs used
- AI applications specific to each team
- Risks specific to each team's material
Together, not later
The session and the written policy arrive together. People leave knowing how to integrate AI technologies into their work and what is sanctioned.
- Policy delivered alongside training
- Approved tools made clear
- Hands-on experience with their own work
- Verification habits practised, not described
On what they tried in real work
We look at what people used, where they got stuck and what the policy did not cover. That second session often teaches more than the first, because people bring real problem-solving questions from their own work.
- Follow-up session after a month
- Real usage reviewed
- Policy gaps closed
- Champions supported per team
Why us
Why this training changes Monday
Because it starts from what people already do with AI, not from an AI literacy course outline or an innovation workshop.
By role, because the risks differ
What finance must not do with AI differs from what marketing must not do. A single session for everyone leaves most of the room listening to examples from someone else's job.
The policy arrives with the training
People leave knowing what is sanctioned on the day, instead of waiting for a policy promised for later. Most organisations have never told their staff this, and it changes how people work with AI.
We teach where it is unreliable
We show invented facts, false citations and confident wrong answers on your own material, so people see them before a client does. Staff who understand these failure modes let AI remove delay while they keep the decision-making.
Industries
Proven results across sectors
Every number below is the count of case studies we have actually published in that sector, and the best result among them. Nothing is a counter.
Selected work
Programmes behind this work
:quality(80))
German Medical Center
Two disconnected websites rebuilt as one bilingual WordPress site with a HubSpot funnel behind it.
+73% increase in leads
View Case Study 
+73% increase in leads:quality(80))
Roxana Aesthetics
Seventy-two treatment pages in Dubai’s most contested clinical category, built inside DHA advertising rules.
View Case Study:quality(80))
Elora Polyclinic
One site carrying aesthetics, dentistry and surgery — three audiences, three routes, one design system.
+230% organic traffic
View Case Study :quality(80))
Arabland
A Dubai property platform with filterable listing search, a map of the city and a mortgage tool.
+220% organic traffic
View Case Study :quality(80))
Concept Plus
A scroll-scrubbed WebGL scene experience spanning six divisions — and still a PageSpeed of 90.
PageSpeed 90 on WebGL
View Case Study :quality(80))
Bafco
Office furniture on Shopify, serving a single-chair buyer and a corporate fit-out from one catalogue.
+320% organic traffic
View Case Study :quality(80))
A2 Sweden
A smart-lock catalogue with parallel routes by product, by industry and straight to the flagship.
+180% organic traffic
View Case Study Where this sits
The rest of our AI services
Training makes the rest of the AI work land, whether that is AI strategy, a chatbot, automation or a wider digital transformation.
The hubAIAI solutions applied where they change a number, with the governance and measurement that stop AI adoption becoming an expensive experiment.Everything in this service
- AI strategy & consultancyDeciding where AI earns its cost before anybody buys a licence.
- AI chatbots & agentsAssistants grounded in your own content, with a human handover.
- AI marketing automationAI inside the workflow, where it removes a real manual step.
- AI sales automationResearch, enrichment and drafting, so reps spend the day selling.
- AI content generationAssisted production with an editor still accountable for the output.
- AI knowledge baseYour documents made answerable, with citations back to the source.
- AI corporate trainingYou are hereWorkshops that leave a team using AI on Monday, not just impressed.
Client stories
What clients say
On camera and in writing — swipe through the founders and teams we’ve helped design, build and grow.
In their words
★★★★★
GMC is thrilled to extend our heartfelt appreciation to Adnika! Collaborating with Ehsan and his team has consistently been an absolute delight. Ehsan's dedication and commitment have ensured that German Medical Center remains an exceedingly satisfied and happy client, especially regarding their Hubspot Onboarding, Digital Marketing, Website Development, Content Creation and Social Media Marketing. Adnika is indeed the Best Digital and Growth Marketing Agency in UAE!
★★★★★
Adnika provided us with their Inbound Sales and Marketing solutions through Hubspot. They helped us generate more qualified leads for our sales team, drive website traffic, increase customer engagement, and grow our customer base. Adnika is a reliable partner that has always taken our specific goals and needs seriously.
★★★★★
Adnika has helped us plan, implement and optimize ad campaigns on Facebook and Instagram. Adnika is truly committed to Performance Marketing. They provided us with a fantastic dashboard with detailed KPIs that helped us track the campaigns’ performance in real time. Adnika also gave us helpful and dedicated support during the whole project, and the campaigns turned out to be a great success. We highly recommend working with Adnika's growth experts.
★★★★★
We really enjoyed working with Adnika’s team. Not only are they talented, but they all take the time to understand whom they're working with, what they're trying to accomplish, and how to help the business achieve its goals. The quality of work we've experienced has made a huge difference for us and helped drive new business.
★★★★★
Adnika helped Sea Technology with setting up new digital channels, such as Google Search Ads, to attract more customers and leverage our brand. We are very satisfied with the results and we will continue with the implementation of lead generation, marketing automation, and performance marketing.
★★★★★
Working with the Adnika team has been a real pleasure! Extremely friendly, Ehsan and Elin are always available with prompt replies, valuable insights, patience, a problem-solving attitude, and high knowledge. Super easy to work with them. I highly recommend the Adnika team to help your business!
★★★★★
I am an artist, but I also manage a collective of DJs. In order to promote our services to our clients, we needed Inbound solutions that could attract the right traffic and promote the brand. Adnika built and designed our Inbound processes as well as create and manage campaigns on social media and Google Ads which helped us attract many more customers. I’m very happy!
★★★★★
We've been using Adnika growth marketing solutions only for a few months. They are highly professional, competent, experienced, and creative. Get ready to get to work with this agency. They will come alongside you as a business owner and feel your pain and joy! Get ready to transform your business.
Questions
AI training in Dubai, answered plainly
Straight answers on what the training costs, what it covers and who it is not for.
The cost depends on how many roles and sessions you need and how large each group is. How closely the material is tailored to your work matters too. Sessions in two languages take more preparation, and so do the usage audit, the written policy and the follow-up session. We quote after a short call, once the scope is clear, and you keep the scope document whether or not you go ahead.
No, this is training bought by a company for its own teams and built on that company's workflows and documents. People leave able to do their own tasks with these tools and to check what comes back. For your own career development, artificial intelligence courses online, a training institute or a university will serve you better. An AI online course costs far less and suits students as well as working professionals.
It covers the areas where generative AI helps your team's specific work and where it is unreliable. People learn how to check output before using it, what may go into which tool and which tools are sanctioned. Everything is practised on your own documents, and how the technology works inside is left out on purpose. The tools are the ones your team has, usually ChatGPT, Gemini or Microsoft Copilot, plus the AI capabilities inside the software programs you use.
There is no established rule, even though several articles quote one with a percentage attached. They define it in different ways: a share of tasks to automate, a productivity target or a confidence threshold. It shows up in search suggestions because content sites wrote about it, not because practitioners use it. If someone quotes it as a standard, ask which version they mean and where it comes from.
Three skills matter, and the first is knowing which tasks are worth doing with these tools and which are not. The second is describing a task clearly enough to get a usable result, which courses call prompt engineering. We teach it as a simple prompt structure people can reuse. The third is checking output before relying on it, and it matters most while being taught least.
Yes, and we recommend it, because training without a policy leaves people enthusiastic but unsure what is sanctioned. A short policy that people read beats a long document nobody opens. It also gives you a rule for future tools.
The duration is two to three hours per role, enough for practice on real work. Longer sessions cover more ground, but people retain less of it. The follow-up a month later is shorter and often more useful, because by then people have real questions.
Eight to twelve people per session keeps the work hands-on. Beyond that, people stop practising and start watching, so we would rather run three small sessions than one large one.
Yes, sessions run in Arabic and English, and we prepare the materials in both where your team needs them.
The follow-up session shows what people tried in their own work. Beyond that, we look at whether unsanctioned tool use falls, whether the tasks you named get done faster and whether people check output. We agree these measures with you before delivery.
On specific tasks, yes, and you can measure it. Across the board the gains are smaller than the claims going around. Anyone promising a broad productivity figure is quoting a study, not your numbers. Expect real gains on drafting, summarising and document work, and little elsewhere.
Yes, and it is usually the right place to start. We run it as an anonymous survey of the tools people use and the material they put into them. It is short work, and it regularly gives leadership insights into exposure they did not know about.
No, a basic understanding of AI comes from using it on real tasks, and that is where the sessions start. Staff who are new to artificial intelligence learn next to colleagues who already use it. No prior AI knowledge or tech background is needed.
A team can learn the useful parts within a month. That covers which tasks suit these tools, how to brief them and how to check the output. Mastery takes longer, and nobody needs it to use AI well at work. The follow-up a month later shows how far people got.
No questions match — try another search.
Next step
Find out what your team already uses
Ask them anonymously before you commission anything. The answers usually change what the training needs to cover, and occasionally they change the priority entirely.