Image: Supply
If any country could become a global AI powerhouse, it’s the UAE. Long before the groundbreaking launch of ChatGpt, it was the UAE that created the world’s first AI ministry.
Since then, the government has never missed the opportunity to encourage private companies to adopt the latest and great things and adopt it themselves. And that shows. One estimate last year shows that the country’s AI market is estimated to be nearly $1 billion ($949.8 million), with a total of $4.3 billion by 2030.
The AI ​​Asset Race has already begun, spurring the hype of the generated AI that has dominated the boardroom compubs for the past two years. Deepseek’s announcement earlier this year highlighted the urgency to move forward and strongly convinced business leaders that they must seriously investigate how to maximize profits from inevitable investments. Some are forecast, but it is projected to continue dedicating its budget to generate AI, which is worth more than $200 million this year and is set to grow to $20 billion by 2030. This is a CAGR of 46.47%, far surpassing the overall AI. By pursuing AI maturity and a company-wide AI culture, decision makers are beginning to become more practical about where to route AI dirhams.
The problem lies in differentiation. AI methods – Genai, Natural Language Understanding (NLU), predictive analytics, etc. are standards and can be essentially commoditized, as Deepseek has recently proven. If a supermarket invests $1 million to try to understand its customers better, it may receive a bump in revenue in a short amount of time, but competitors simply replicate the investment to replicate the benefits.
The competitive edge will cancel each other and everyone is a million dollars poor without continuing profits. The only way to avoid this apparent paradox is through the development of technologies that can occur in any industry, but no one else has or business models that no one else has.
Stand out and move up
First, let’s look at technology-based differentiation. Yes, the models are standard and some powerful models can also be used as open source. However, it is the data that is unique to each business. The data itself (customer, operations, finance, security) can even propose use cases and build a model around it. The winners are those who find ways to go beyond simple automation to save and differentiate the workforce while applying their own data to more sophisticated models. You can also use AI to create richer views from your data. This could be comprehensive, but it can also be awkward preservation.
Business-wise, organizations can consider ways to deliver ubiquitous AI without eating too deeply into the budget. Generation AI is relatively expensive, but not all use cases require GPT-4. If one of the aforementioned supermarkets is to provide customers with 360-degree viewing for a cost of $700,000, for example, then it has a cost advantage over its competitors, and is the top of the list even if you don’t invest in it first. In the real world, even choosing to make a simple decision like a Slimmed Down product, or invest in CPU hardware via GPU, can make all the difference. Next is the operational decision. Are you training and maintaining AI models in the cloud or on-site? Given the cost of calculation, storage and bandwidth for genai in the cloud, in-house hosting may be a better option.
However, when pursuing universal AI, non-technical employees will undoubtedly benefit from more sophisticated tools built on generated AI. Modern solutions allow more employees to increase their value. Furthermore, organizations solve the problems presented by local AI skills gaps.
Recruitment is time-consuming and expensive, and new participating data scientists and AI professionals take longer to projects than business-oriented employees. Collecting requirements is no longer a bottleneck if the person who knows the business best is tasked with implementing their own ideas with the help of generated AI.
The Possibilities of AI: Incremental and Revolution
Already, industry experts have expressed the potential of AI by comparing 10% profits with 10 times profits. AI can increase supply chain efficiency, enhance customer service, reduce manufacturing obstacles, and speed up R&D. A 10% profit is a backing of the old one after the limits. Ten times profits are what the Industrial Revolution takes place. What cars did for transportation, what cloud computing did for the software segment, what smartphones did for payment. Nowadays, generative AI has arrived, and it is becoming chaotic across a variety of industries.
One stumbling block remains with those who choose to embark on a genai expedition, and that is a regulatory duty. Only through proper training and interdisciplinary expertise can UAE companies successfully navigate the legal environment. Governance must be designed and must be designed in advance. Waiting for legal issues to occur can be expensive not only due to the fines that may arise, but also due to the costs of redesigning and re-deploying solutions, retraining staff, and even procuring additional tools.
Fortunately, the right AI platform allows governance to be consistently and accurately applied across your organization. From role-based data access to predefined dataset views, all projects can be established by the steering committee before they become greenlight. Modern AI platforms can even automate monitoring live solutions for new trends that can throw away model shifts and outcomes and lead to negative impacts.
Building an AI business requires will and skills. Don’t say that burning your arms and diving into the next powerful LLM will guarantee results. Mountains of operational, financial and legal shocks await those facing this future of AI. A cool head has to win. Choose an AI pass that suits your individual business and leverage your personality to make that pass unique in the market.
The authors are Area VP and GM – Dataiku from the Middle East, Turkey and Africa
