Latest news with #SidBhatia
Tahawul Tech
5 days ago
- Business
- Tahawul Tech
Do you want to get the most out of Agentic AI? Dataiku GM lists the three boxes you need to tick for success
Sid Bhatia, Area VP & General Manager – Middle East, Turkey & Africa, Dataiku, has written an op-ed that lists the THREE architectural boxes every organisation should tick in order to get the most out of Agentic AI. In the United Arab Emirates (UAE), AI is now an everyday tool. We use it as individuals, and we use it as professionals. Among the businesses that use it, the more successful implementers follow a Universal AI adoption path that changes the corporate culture from within and infuses the workforce with AI literacy. Stemming from this enthusiasm, analysts foresee AI in the UAE as a multibillion-dollar segment, with generative AI (GenAI) alone taking about US$383 million in 2025 and more than US$2.5 billion in 2031 — a CAGR of nearly 37%. But AI itself has changed. As businesses have come to understand the limitations of GenAI and the importance of taking an operationally centric approach to tool procurement, decision makers have begun to explore the idea of having AI agents with modular autonomy take over from other forms of AI. The UAE's agentic AI market garnered revenues of around US$34 million in 2024. By 2030 it is expected to be worth more than 10 times this figure — some US$352 million. At a CAGR of almost 48%, agentic AI, in the UAE at least, will be adopted at a faster rate than GenAI. As with GenAI, or any AI, or indeed any technology, procurement of agentic AI is no guarantee of success. We must be diligent about how we build our architecture, the ideal example of which, I believe, has three basic characteristics. Flexible AI waits for nobody. At its current speed of evolution, modern business IT environments find it difficult to keep pace. To stand a chance, CIOs must look at how easy or difficult it is to maintain their tech stacks. If a new version of the GPT core model arrives on the market, will it be easy to adopt, or will it require weeks of overtime work from the DevOps team and others? To streamline adoption, enterprises should ensure that the underlying framework, in which AI agents will operate, is flexible enough to support plug-and-play models. Modular architecture is crucial to the success of almost any modern technology; but if the regularity of recent versions of GPT is anything to go by, then the journey organisations will take with agentic AI is likely to be marked by particularly frequent upgrades. Architectures should be crafted around four layers: the generative model layer, the feedback layer (which implements learning loops across multiple models), the deployment layer, and the monitoring layer. Matches models to jobs To apply the FOMO principle to AI procurement is to invite disaster. The individual or team that oversees the organization's Universal AI journey should be laser-focused on business issues first and AI only as the means to overcome challenges. Organisations should be fully cognizant of what issues are being addressed by AI. Is it an exercise in optimisation? Is it the addition of a completely new business capability or a new product or a new service? Whatever is being added, it should come with a net-positive value. The AI procurement team should work with targeted beneficiaries to ensure everyone knows how to measure success and what constitutes a risk. For example, giving GenAI-powered virtual assistants to sales or customer-service employees may lift their productivity, conversion rates, and even profitability ratings. But these benefits may be neutralised if employees share sensitive data with a cloud-native model. Thankfully, formal metrics like answer correctness and B-score allow analysis of models for their suitability in a use case. 'LLM as judge' — where AI models are used to monitor the effectiveness of other AI models — is also viable. Backed by strong governance The AI journey is fraught with risk. Today, we see many organisations prioritizing speed over security, and we see AI budget growth outpacing that of IT budgets. The introduction of AI must align with the compliance obligations and financial limitations of the enterprise. The only way to achieve this is through appropriate governance. Governance has a broad remit. On the security side, it can mandate content-filtering to ensure customers are never exposed to output that would be damaging to the organisation's brand. On the financial side, it can prescribe dashboards that monitor costs and categorise them by project and user. So critical is governance to AI success that some modern AI platforms include it as part of the suite — signaling that solutions vendors now consider it as important as the building of ML models. Even when AI was in its infancy, some industry leaders were calling for 'responsible AI' that cracked open the black box and presented models' innermost workings for scrutiny. Guardrails and trust go hand in hand. Security builds trust with customers. Cost-effectiveness builds trust with the C-suite. The path to Universal AI We can have the AI future we want, but only if we apply due diligence. By ensuring we take the right steps towards security and cost-effectiveness we can introduce agentic AI in ways that produce the right results. It may be the talk of the town right now, but we must adopt agentic AI strategically if we are to prosper from its merits.
Hospitality Net
06-05-2025
- Business
- Hospitality Net
Sid Bhatia has been appointed General Manager at Moxy Sydney Airport
Moxy Sydney Airport, part of the Marriott International group, is pleased to announce the appointment of Sid Bhatia as its new General Manager. With over 20 years of experience in the hospitality industry, Sid brings a wealth of knowledge from roles across Australia and New Zealand. His previous positions include General Manager at Vibe Hotel and Cluster GM for TFE Hotels in the Northern Territory, where he successfully navigated the challenges of the pandemic and helped position the properties as market leaders. In 2022, he was a finalist in Hotel Management magazine's General Manager of the Year award. Sid joins a dynamic team at Moxy as the hotel continues to redefine what travellers can expect from an airport stay—combining fun, functionality, and relaxation just minutes away from their next journey.
Tahawul Tech
14-04-2025
- Business
- Tahawul Tech
Dataiku executive believes emergence of DeepSeek heightens the need for ‘AI Optionality'
Sid Bhatia, Area VP & General Manager, Middle East, Turkey & Africa at Dataiku, has penned an op-ed for April's edition of CNME, in which he argues that one of the lessons that can be learned from DeepSeek, is the fact that 'AI Optionality' is going to be key. Do you remember ChatGPT? Do you remember when it was the new kid on the block? How times have changed in the world of generative artificial intelligence (GenAI). DeepSeek has been around for some 18 months, but the echoes of New Year celebrations could still be heard as the Chinese startup hit the headlines this month. It released its GenAI assistant as a free app, claimed a development cost of less than US$6 million, and wiped hundreds of billions of dollars in market capitalization from companies like NVIDIA and Microsoft. In the United Arab Emirates (UAE), private enterprises face a future that will be dominated by AI, with GenAI alone projected to be a US$2-billion segment by 2030. When trying to grab a share of that value, UAE enterprises must be mindful of the user data horded by AI vendors like DeepSeek — ranging from prompts to uploaded files — and the implications for compliance with regulators inside and outside UAE borders. The nation's AI innovators must therefore develop flexibility in their own infrastructure that will allow them to avoid vendor lock-in and innovate freely, on their own terms, while meeting their compliance obligations. DeepSeek's rocket-like rise illustrates just how much GenAI — itself a disrupter of the larger AI industry — has changed in the two years since OpenAI's ChatGPT captured our imaginations. We continue to see leaps forward in the quality of models. Capabilities are becoming progressively more advanced and features that were turning heads just six months previously are standard fare today. Cost and value As boundaries are pushed, the costs of building a production-ready model are plummeting. It is this very selling point, remember, that made DeepSeek so impactful. Cost-effectiveness also allows AI to be democratized more readily, leading to faster time-to-value for AI investments. Throughout these developments, open-source AI has been building momentum and producing admirable results that are made available to a global community of innovators. The geography of that community is diverse, again leading to more opportunities in more markets. If the adage, 'the only constant is change' is true of life, it is doubly true of technology and even more so of AI. But stakeholders in the field of GenAI must check the bulletin boards hourly for the latest breakthrough. If an organization is in the process of adopting GenAI, its decision-makers must obtain, maintain, and retain the flexibility in their infrastructure to accommodate the dizzying pace of change. The benefits of a flexible AI infrastructure include allowing an organization to address the speed of change, as today's breakthrough becomes tomorrow's baseline. While due diligence must, of course, be baked in, plug-n'-play adoption should be the goal. When a new model or capability becomes available, the Everyday-AI enterprise should be able to embrace it without having to rebuild its AI infrastructure. Organizations must be able to protect their investments so that value is created today, tomorrow, and next year. Training and inference costs continue to evolve. More flexible architecture means more cost-effective solutions. Pivoting from one model to another or switching providers in an instant are other benefits of a flexible infrastructure. Organizations can optimize AI investments as they optimize performance. And when tweaking the AI stable, businesses will find that each AI solution is at home in its own unique infrastructure. Legacy hardware may be sufficient for some; others may need specialized equipment and resources. Flexible architecture allows the organization to take full advantage of its existing infrastructure while procuring new tools as needed, assured by the knowledge that they will be compatible with existing systems. The power to pivot Because change is the only constant, uncertainty reigns. Risk is everywhere and must be managed. In GenAI, risk takes the shape of changes in model availability, performance, and cost, or in new regulatory requirements. A flexible platform is capable of maintaining multiple model options, allowing Everyday AI organizations to quickly turn the key on new models when previous ones become inviable. With the right flexibility, enterprises can innovate more quickly because their environment is built for experimentation. New models can be prototyped, tested, and released with relative ease. What I am describing is a futureproof foundation for core AI abilities that allows addition and subtraction without the need for a fundamental rebuilding of underlying elements. Tool agnosticism is a critical component of effective AI-driven organizations. Such enterprises keep using the same storage and processing systems, so their previous investments continue to add value. They then integrate emerging AI models (open-source or proprietary) and adjust resources to fit. We sometimes refer to this flexibility as 'optionality'. It is our ticket to the AI future we will all share. Optionality will decide our place in that future. Are we set to be a spectator or a player?
