Azwan Baharuddin, Country Managing Director, Malaysia at Accenture explains how local businesses can fully unlock AI's potential, driving growth and innovation.
How is artificial intelligence (AI) transforming business operations today?
Gen AI is the new digital. It is already scaling, and it’s continuously going to be able to solve new problems. It’s able to change work and change industries. It’s the only technology capable of driving productivity and growth across an entire enterprise. In fact, we saw generative AI demand drive $3 billion in Accenture bookings in our recently-closed fiscal year.
Among Asia Pacific C-suite leaders, 81% are seeing financial benefits as generative AI use cases scale. The greatest impact has been in product development, customer and workforce engagement, and operational efficiency. Looking ahead, 53% plan to significantly increase AI investments, with the same proportion prioritizing generative AI over traditional AI systems designed for specific tasks.
What sets gen AI apart from traditional types of AI is gen AI can act in an autonomous manner to create new content or create new capabilities based on its training, whereas traditional AI is typically only used to analyze data provide predictive forecasts.
Gen AI will have its greatest impact if it is trained on an organization's data, granting it a deep understanding of the business, its products, markets, and customers. It's a powerful tool that will move the needle to create streams of content, identify new operational efficiencies, boost productivity of the workforce and open new avenues for work.
How does AI enhance productivity by turning data into actionable insights?
Companies should start by asking questions: Are you in the cloud? Do you have a modern data platform? Do you have the right security implemented? Gaps in any of these, and other critical areas, will undermine a company’s ability to scale generative AI.
We suggest that organizations should understand the concept of 'digital core'; and assess where their technology stands in relation to the industry and the requirements for using generative AI. Based on the assessment, they should create a plan to maximize the potential for success in reinvention and develop strategies to build new capabilities, including handling unstructured and synthetic data and integrating multiple foundation models.
We also suggest prioritizing cybersecurity by involving the CIO early in the technology lifecycle and fostering a strong security culture. Additionally, we recommend assessing risk and reward relationships with partners and exploring opportunities for co-creation to accelerate progress. Finally, we suggest setting a goal to allocate over 50% of technology investments toward building new capabilities and rigorously measuring progress to ensure sustained growth and innovation.
What industries in Malaysia are leading in AI adoption, and what can others learn from their approach?
While generative AI demand is strong across industries globally, it is particularly pronounced in public services, communications and media, and financial services (banking and insurance), with growing adoption in life sciences and consumer sectors like CPG and retail. These industries use AI not just to boost efficiency but to drive innovation and better serve stakeholders.
A key takeaway is their focus on building a robust digital core—cloud as the enabler, data as the driver, and AI as the differentiator. This interoperable system integrates enterprise platforms, automation, and security to rapidly develop new capabilities. For organizations adopting generative AI, the digital core becomes a competitive advantage, enabling agility and delivering value in an increasingly AI-driven world.
How does the government’s allocation of RM10 million to the National AI Office reflect its commitment to AI development?
The Malaysian government's allocation of RM10 million to the National AI Office in the 2025 Budget reflects its strong commitment to advancing AI development in the country.
This funding is aimed at positioning Malaysia as a regional leader in AI innovation and digital transformation. It highlights the government's focus on nurturing high-tech sectors such as AI, robotics, and IoT, while also fostering local talent through tax incentives and R&D support.
This approach is designed to accelerate technological progress, enhance operational efficiency, and attract foreign investment—key steps in ensuring Malaysia remains competitive in the global AI landscape. By investing in both technology and people, the government is laying the groundwork for a sustainable AI ecosystem that benefits businesses and workers alike.
Why is it essential for businesses to adopt AI-ready technologies as part of their digital transformation strategies?
Adopting AI-ready technologies is essential for businesses as part of their digital transformation strategies because AI is no longer just a tool that responds to commands—it’s becoming more agentic.
Agentic AI systems represent a leap forward, as they can autonomously collaborate with humans or other AI agents to complete tasks and make decisions based on the environment or specific goals. This shift from reactive AI to proactive, learning, and self-improving AI systems is the future of business innovation. In practical terms, businesses can harness AI agents that work together on big-picture goals, such as using AI to identify hidden operational vulnerabilities or drive process reinvention.
For instance, in software development, AI agents specializing in design, testing, and documentation collaborate with super agents to build entire systems, going beyond simply answering questions to actually getting things done. By adopting AI-ready technologies, businesses can unlock enormous opportunities to improve efficiency, innovate faster, and gain a competitive edge.
What challenges might companies face when integrating AI into their operations?
According to Accenture findings, the number of companies that have AI-led processes has nearly doubled to 16% in 2024. Still, many companies struggle to scale use cases.
Some face challenges related to building a strong data foundation, such as it being too hard to scale with proprietary data (70%) or data assets aren’t ready for gen AI (61%).
Others (78%) indicate AI and gen AI are advancing too fast for an organization’s training efforts to keep pace.
What strategies can companies implement to ensure their employees are prepared to work alongside AI technologies?
Generative AI’s potential is realized when people are at the heart of reinvention, which requires companies to lead differently.
Accenture research reveals that adopting responsible, people-centric approaches to gen AI could unlock an additional $10.3 trillion in economic value. However, 3 in 4 organizations lack true people-centric change plans, only 5% provide AI training at scale, and two-thirds of leaders feel ill-equipped to manage this change.
The real accelerator of generative AI is not the technology itself but the people. Organizations must first reimagine how gen AI will impact workflows and the workforce, identify which areas will be most affected, and understand the skillsets needed. This allows them to develop comprehensive strategies for skilling and training their workforce, enhancing experience and expertise, and fostering a culture of continuous learning.
Ultimately, with gen AI, organizations can work smarter, not harder, with leaders focusing more on empowering their teams to thrive than just directing them.
In what ways might the landscape of employment change as more companies adopt AI-driven processes?
The net effect of gen AI on jobs will not be to eradicate them, but quite the opposite – it will create a new set of high-value human work tasks. There is an anticipated surge of demand for AI and machine specialist roles, with studies predicting a 40% increase in the next 3 years, alongside significant rises in demand for data analysts and digital transformation specialists.
What responsible AI practices should businesses adopt when implementing AI solutions, and what steps can be taken to ensure ethical AI usage?
There is a quote that goes - “When you invent the ship, you also invent the shipwreck”.
Business leaders are seeking greater governance of generative AI initiatives in an environment where technology, regulation and business adoption are accelerating exponentially and simultaneously. The key is to embed responsible practices across the design, development, deployment and the use of scaling of generative AI across the enterprise.
Some of the key steps include:
- Establish AI governance and principles: Agree and adopt responsible AI principles with clear accountability and governance for responsible design, deployment, and usage of AI.
- Conduct AI risk assessment: Understanding the risks of an organization’s AI use cases, applications, and systems through qualitative and quantitative assessments (e.g., fairness, explainability, transparency, accuracy, safety, human impact etc.).
- Enable systematic testing: Perform ongoing testing of AI for fairness, explainability, transparency, accuracy, safety leveraging best of breed Responsible AI tools and technologies and enable mitigations.
- Ongoing monitoring & compliance of AI: Ongoing monitoring of AI systems and overseeing RAI initiatives while executing mitigation and compliance actions.
- Workforce Impact, sustainability and privacy/ security: A responsible AI compliance program will need to engage cross functionally to address workforce impact, compliance with laws, sustainability, privacy/ security programs across the enterprise.
ASEAN is becoming a competitive digital economy. How can Malaysia distinguish itself as a leader in AI within the region?
Malaysia is poised to become a regional AI leader by strategically investing in key AI technologies, fostering public-private partnerships, and prioritizing talent development.
The RM10 million allocation to the National AI Office in the 2025 Budget is a significant step toward this goal, supporting the creation of the ASEAN AI Safety Network. This initiative will play a pivotal role in driving responsible AI practices across the region, laying the foundation for the ASEAN Responsible AI Roadmap (2025-2030), which will ensure ethical and beneficial AI developments for all member states.
Additionally, the Ministry of Trade, Investment, and Industry (MITI) is strengthening Malaysia’s digital infrastructure by targeting 3,000 smart factories under the New Industrial Masterplan 2030, further reinforcing the country’s commitment to AI-driven industrial transformation.
As Malaysia prepares to take on the ASEAN Chairmanship in 2025, it presents a unique opportunity to deepen strategic collaborations, particularly in AI, with ASEAN and global partners, With these initiatives, Malaysia is positioning itself as a central hub for AI innovation and governance, driving not only technological advancement but also regional leadership in AI.
How does Accenture envision the future of AI shaping Malaysia's growth and innovation?
Accenture sees AI as a transformative catalyst for Malaysia’s future, driving economic growth, boosting workforce productivity, and fostering innovation.
By adopting AI with responsible practices, Malaysia can unlock its full potential and emerge as a regional leader in the digital economy. This includes enhancing existing processes and creating new opportunities for businesses and the workforce.
As part of its Center for Advanced AI, Accenture is playing a pivotal role in this transformation by introducing a network of AI Refinery hubs. These hubs bring deep engineering expertise and the technical capacity to leverage agentic AI systems, which will drive the transformation of large-scale operations. The hubs will focus on the selection, fine-tuning, and large-scale inferencing of foundation models, addressing key challenges such as accuracy, cost, latency, and compliance when scaling AI deployments.
The future of AI lies in collaboration and continuous learning. Agentic AI systems will evolve beyond automating tasks to autonomously collaborating with humans and other AI agents to achieve complex, real-time goals. These systems will seamlessly integrate into teams, enabling organizations to tackle big-picture objectives.