EY’s Ram Kumar Narasimhan: AI adoption must start with clear business strategy

He emphasised the importance of focusing on solving business challenges first before adopting new technologies.

To improve customer experiences and modernise operations, companies in Southeast Asia are investing heavily in digital technologies. This behaviour was mainly driven by the industry’s rapid adoption of artificial intelligence (AI). But in determining success, technology alone is not the sole deciding factor. 

Sharing his perspective on this is Ram Kumar Narasimhan, Asean Digital and Technology Transformation Co-leader at EY. Having extensive experience leading large-scale digital and technology-enabled transformation programmes and adopting the latest technologies, including agentic AI, he underscored that meaningful transformation can only be achieved when organisations start with a clear understanding of their business challenges and align their technology strategy to address them.

Narasimhan’s knowledge on the matter came from his experience working with organisations in telecommunications, airlines, gaming and entertainment, consumer products, and retail. His expertise spans customer experience transformation, cloud modernisation, and enterprise applications, helping businesses build digital capabilities that support long-term growth.

As he joins the judging panel of the Asian Technology Excellence Awards 2026, Narasimhan provides insights on how organisations can successfully scale transformation, the future of AI in Southeast Asia, and the qualities that distinguish truly outstanding technology initiatives.

What makes Southeast Asia’s technology landscape unique when it comes to scaling complex digital and technology transformation programmes?

Southeast Asia’s technology landscape is defined by diversity. Whilst markets differ in regulation, language, culture, market size and consumer behaviour, they share several characteristics, including mobile-first consumers and fast-growing local and regional digital ecosystems. These dynamics are driving organisations to modernise legacy systems and adopt new technologies. Further, as many operate across multiple markets across Southeast Asia (SEA), the challenge is balancing scale with localisation. 

Successful transformation programmes are built on a common technology and architectural core, with enough modularity to adapt to local regulatory requirements, data practices and consumer expectations. Organisations that get this balance right can turn SEA’s complexity into competitive advantage, using diversity to accelerate innovation and scale more effectively across markets.

In your experience, what typically separates successful large-scale technology transformation programmes from those that struggle to deliver expected outcomes?

Successful transformation programmes start with a clear definition of the business outcomes that organisations aim to achieve, supported by measurable KPIs and rigorous tracking metrics. They have visible executive sponsorship and empowered programme leadership teams to drive decisions at pace. Strong programme foundations also matter. These include shaping the product, designing customer and employee journeys, establishing the operating model, and architecting the right technology and data platforms. 

Equally important is disciplined execution. Deep involvement of executive sponsors and programme leaders in understanding the constraints, making the right decisions and resolving issues quickly across business and technology teams contribute to the success of the programme. 

Lastly, organisations should proactively assess changes to processes, roles, skills and ways of working from the outset. Transformation programmes tend to struggle when ambition outpaces delivery capacity, technology decisions are disconnected from business objectives, benefits are not measured continuously or adoption is left until the end.

How do you see organisations’ digital transformation priorities evolving as AI becomes more embedded in their network and operations?

Organisations are moving from isolated AI pilots to adopting AI to drive enterprise-wide transformation, reimagine products and services, and redesign end-to-end operations around intelligence and automation. 

For example, in the consumer products and retail sector, this includes leveraging AI for real-time product or pricing recommendations. In asset-intensive sectors, AI is supporting investment and operational decisions. In customer service, AI is enabling intelligent, omnichannel service experiences that improve responsiveness and service quality. 

Capturing value at scale requires more than deploying standalone AI solutions. AI must be embedded into critical workflows to augment human decision-making and automate routine activities. Trusted data, modern cloud and edge platforms, observability and resilient architecture have become even more important. Organisations will also need stronger governance frameworks to manage security, privacy and risk from the start. 

Ultimately, the focus will shift from proving that AI works to scaling it responsibly and demonstrating measurable improvements in customer experience, productivity and growth.

What will define a truly "AI-enabled" organisation in the next phase of industry evolution across Southeast Asia?

A truly AI-enabled organisation will use AI as an enterprise capability embedded in how the organisation defines, shapes and delivers products and services to customers. It is less about AI tools and technology but more about adoption. 

Such an organisation will know how to use AI to interpret data, redesign decisions and workflows so that people and intelligent systems can work together with clear accountability for outcomes. It will build the foundations for trusted, well-governed data and reusable platforms that can rapidly scale solutions across functions and markets. 

More importantly, it will define clear boundaries for AI autonomy, understand AI-related constraints, decide where AI should and should not be used, and establish controls and guardrails needed for execution. AI-enabled organisations will invest deliberately in workforce skills, adoption and controls as they do in models and infrastructure. 

Organisations will measure AI by sustained business value and stakeholder trust, whilst continually learning and adapting as technology and regulation evolve.

Looking ahead, what emerging technologies beyond AI do you believe will significantly reshape business models and competitive advantage in Southeast Asia's technology ecosystem?

With greater AI adoption, new opportunities will emerge for sovereign AI, energy-efficient compute technologies and data centres. This will create new business models for organisations building and scaling digital infrastructure as demand increases across Southeast Asia. 

Physical AI bringing together robotics, AI and autonomous systems will increasingly address productivity, safety and workforce constraints across industrial and service environments.  

Advanced connectivity, including private 5G and the evolution toward 6G, will enable more responsive and distributed business models across manufacturing, logistics, media and smart infrastructure. Edge computing and digital twins will bring intelligence closer to physical operations, allowing organisations to simulate, monitor and optimise assets in real time. 

Quantum technologies could create longer-term breakthroughs in areas such as molecular and materials discovery, complex optimisation and precision sensing. For SEA’s manufacturing, pharmaceutical, logistics and financial services sectors, these capabilities may give rise to new products and fundamentally different operating models. That said, the most immediate priority is cybersecurity. Organisations should list down their cryptographic dependencies and begin transitioning toward post-quantum standards well before sufficiently powerful quantum computers emerge.

As a judge at the Asian Technology Excellence Awards 2026, what innovations or transformation outcomes will you prioritise when evaluating nominees?

Firstly, I will look at whether the nominee has clearly articulated the business or social problem it set out to solve and how technology was applied to solve the problem. The outcomes should be tangible and supported by evidence, whether through improvements in customer or employee experience, productivity, growth, resilience, inclusion or sustainability. 

Next, I will assess the extent of adoption and scale – whether the solution has moved beyond a pilot and is delivering measurable value. Equally important is how the solution is designed, including its architecture, data foundation, cybersecurity, governance and, where relevant, human oversight, as these are often what determine whether an innovation can scale sustainably and responsibly.

Finally, I will look for originality combined with disciplined execution and a clear path for future growth.