Securing AI for Business Impact: Overcoming Barriers from Boardroom Ambition to Real-World Results

Data and AI Security: Turning AI Ambitions into Business Value

NTT DATA and CIO.com recently hosted executive roundtables across Australia, India, Malaysia, and Singapore. The goal: to tackle the challenges of bringing AI into production and explore partnership strategies that make AI a genuine business differentiator.

AI Deployment Lags Behind Boardroom Excitement

IDC predicted that by 2030, AI adoption will contribute $19.9 trillion to the global economy and account for 3.5% of global GDP. Optimism is high—over 70% of senior decision-makers in NTT DATA’s Global GenAI Report share a positive view of generative AI. CEOs are prioritizing AI research and implementation, according to Foundry’s State of the CIO Survey 2025.

Yet, despite this enthusiasm, many enterprises struggle to move AI projects from pilot phases to full-scale deployment. Regulatory and compliance concerns slow down sectors like banking and financial services. Healthcare faces organizational hurdles that prevent effective collaboration and integration needed for AI adoption.

Agentic AI and Cyberfusion Centers: Emerging Solutions

IT and security leaders in India are cautiously experimenting with AI, starting with noncritical data due to compliance and regulatory uncertainties. Similar cautious approaches come from Australia and Singapore, where cybersecurity and evolving regulations, especially around shadow AI, remain primary concerns.

Agentic AI and cyberfusion centers stood out as promising tools. Cyberfusion centers unite government, private sector, and academia to share data and expertise, using AI and machine learning to detect and respond to cyber threats, including fraud and insider attacks.

Beyond Cybersecurity: Addressing Skills, Infrastructure, and Culture

Tom Cooper, Senior Director of Cybersecurity at NTT DATA for Australia and New Zealand, highlighted that advanced security strategies not only protect but also support business goals by fostering innovation while ensuring compliance and data integrity. These approaches help reduce operational costs and improve ROI.

Challenges, however, extend beyond security. Leaders in India and Malaysia cite a lack of skills, insufficient infrastructure, and high costs as barriers to AI success. Organizations in Singapore also face difficulties defining AI success, managing change, selecting suitable AI infrastructure, and preparing data for AI to unlock value.

Partnerships: The Key to Moving AI from Concept to Reality

Realizing AI’s economic potential starts with solid IT infrastructure and security strategies that can handle demanding AI workloads and complex threats. Overcoming the AI skills gap often requires partnerships.

Rather than building everything internally, organizations benefit from collaborating with AI and cloud providers to accelerate AI integration and scaling. These partnerships vary by region. Australian leaders seek partners who balance board expectations, employee demands, and regulatory requirements. Indian leaders want close guidance through deploying language models and agentic AI workflows. Malaysian and Singaporean counterparts look for partners to help identify use cases and define success criteria.

True AI Transformation Requires a Shift in Mindset

The biggest challenge is how AI is viewed. Many still see it as a tool for solving isolated problems rather than a catalyst for broad transformation. This narrow approach limits AI’s impact and leads to scattered, uncoordinated initiatives.

To scale and monetize AI effectively, organizations need a clear vision and transformation plan focused on:

• Strategy and governance: Establish frameworks that align AI adoption with business objectives.
• Talent and culture transformation: Build skills and foster acceptance of AI across teams.
• Structural and budgetary adjustments: Adapt organizational design and funding to support AI-driven change.

AI is more than a technology upgrade—it’s a shift in how organizations operate and compete. Boards and business leaders must move beyond “how to implement” toward “how to stand out.” Expert partners can help navigate this transition, avoiding common pitfalls and bringing AI initiatives securely into production for lasting impact.

For those looking to build skills and better understand AI’s role in business, exploring targeted AI training can be a practical next step. Consider checking out the latest AI courses designed to help IT and business professionals advance their knowledge and apply AI effectively.