FEATURE: TRANSFORMING THE ENTERPRISE WITH AI
From left to right: Tarkan Diraz, Director of Application, Data and AI, NTT DATA MEA, Walid Gomaa, CEO Omnix, Stefan Leichenauer, VP Engineering, SandboxAQ and Ashraf El Zarka, Vice President and Regional Managing Director, MEA and Pakistan, UiPath
Saran B Paramasivam, Regional Director Middle East and Africa, Zoho
“ We have found this most impactful for ecommerce brands, where customers can go to a website and engage with AI-powered customer service agents that does not just find what they are looking for but can present them with products they didn’ t even realise the store carried, based on their understanding of the shopper’ s needs,” adds Huber.
“ Taking this a step further, imagine a virtual sales associate that not only remembers past purchases but also suggests products based on the shopper’ s mood, upcoming events, or
MANY ORGANISATIONS STRUGGLE TO LINK THEIR AI INITIATIVES TO TANGIBLE BUSINESS OUTCOMES, LEADING TO STALLED STRATEGIES AND HALTED INVESTMENTS.
even social media trends they follow. That is where AI is taking us,” continues Huber.
“ The first step is identifying what matters most to stakeholders. AI’ s impact should be framed in a way that resonates. Your CFO will care more about financial efficiencies than process automation, while your CEO may focus on AI’ s potential to enhance reputation and innovation. Clear metrics, such as time savings, cost reductions, and risk mitigation, help quantify AI’ s value,” says Hany Mosbeh, Senior Vice President MEA and APAC, JAGGAER.
Equally important is demonstrating the risks of inaction. Competitors are already implementing AI, and standing still is not an option. If internal buy-in is slow, case studies from other organisations can serve as proof of success.
Choosing the right implementation approach, whether building in-house, hiring a specialist team, or partnering with an established vendor, depends on organisational needs. A well-structured implementation plan, with clear milestones and continuous stakeholder communication, ensures AI adoption stays on track.
“ Measure impact at key intervals, immediately, after six months, and beyond. This helps refine future AI strategies and turns AI into a long-term business enabler,” continues Mosbeh.
Making an enterprise AI-ready starts with a clear strategy. A readiness assessment helps identify gaps in data quality, legacy system integration, and company culture. While diving into AI, experimentation is encouraged and can yield early insights, building an enterprise-grade solution requires a well-mapped strategy.
“ Define a clear AI objective, whether focused on productivity, growth, efficiency, or effectiveness, and prioritise high-impact, low-cost proof-of-concepts. Embrace a start small, scale fast mindset to transition from pilot to production and avoiding POC purgatory,” says NTT DATA’ s Diraz.
“ AI strategies must evolve with business needs and technology advancements to ensure sustainable, long-term value. Success comes from a structured, yet adaptable approach tailored to enterprise goals,” adds Diraz.
Enterprises should adopt a holistic AI strategy by first aligning AI initiatives with overall business objectives and securing executive sponsorship. Begin by assessing current AI readiness to pinpoint gaps in data quality, infrastructure, and talent. Establish a
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