The market is not waiting for enterprises to finalize their AI strategy. Consumer expectations are being reshaped by personalized, always-on services. Agentic AI is already influencing commerce, while multimodal AI is accelerating work on machine timescales. Across APAC, governments are rolling out AI frameworks, and talent needs are shifting faster than traditional planning cycles.
Most organizations, however, are still at early stages of adoption. Our Vanson Bourne 2025 research shows that while 85 percent of APAC organizations are using AI in some form, only 12 percent have fully implemented it. The gap between experimentation and scale points to pilot purgatory: ambition is high, execution is lagging.
This mismatch between the pace of AI-driven disruption and the pace of adoption is now a boardroom issue. Closing it requires a focused AI strategy built around four imperatives: skills, leadership, organizational agility, and innovation practices.
Closing the AI skills and resource gap
Where AI literacy is strong, enterprises can innovate, scale, and compete; when it is weak, AI remains a set of disconnected tools. 40 percent of APAC organizations cite a lack of skilled personnel as a major barrier to AI adoption, and 38 percent struggle to find the right talent.
Addressing this demands more than short-term tool training. Organizations need a clear view of where AI will create value and long-term skills impact. All employees across the enterprise need a basic understanding of AI concepts and ethical implications, while those working closely with AI and sensitive data require deeper technical, governance, and risk expertise. At Dell, for example, the AI@Dell learning series continually exposes team members to evolving AI concepts, building broad literacy while allowing specialists to deepen their skills.
Strengthening leadership alignment on AI strategy
Many AI initiatives stall not because the technology fails, but because leadership is not aligned on the strategy. Our research shows that 36 percent of APAC organizations cite a lack of a clear AI strategy, and 37 percent highlight a limited understanding from top management.
AI is still too often treated as a technical project delegated to IT or data teams, rather than a business-wide transformation. Executives may be familiar with AI at a headline level but lack practical fluency in what it can and cannot do, how to manage risk, and where it can create value in their specific industry.
Only with genuine AI literacy at the board and C-suite level can leaders ask the right questions and make informed trade-offs. AI conversations should be focused on data-backed, outcome-driven business cases: how AI will address specific disruption, improve competitiveness, and deliver measurable ROI. Blueprints and reference architectures make this concrete. Dell’s AI Factory blueprint, for instance, links infrastructure, data, models, and security to defined use cases and outcomes.
Increasing organizational agility for AI integration
Even with skills and leadership support, many enterprises struggle to embed AI into day-to-day operations. 35 percent of organizations face difficulty integrating AI into existing systems, and 34 percent encounter resistance to change.
Obstacles are often structural. Complex legacy IT estates, regulatory and compliance requirements add constraints, especially in regulated industries, fragmented data across silos, with inconsistent quality and governance. Skills gaps and shadow AI projects further slow progress and contribute to change fatigue.
How can organizational agility be improved with AI in mind? Enterprises must simplify and modernize core infrastructure, enabling AI to be intrinsically woven into end-to-end workflows rather than simply added on. Streamlined structures and decision-making processes, supported by cross-functional teams driving full-scale deployment with shared accountability, are crucial to rapidly action AI insights.
To encourage broader adoption, transparent communication from leadership is paramount, clarifying AI’s impact on roles, performance metrics, and how human insight will combine with AI recommendations to achieve better outcomes.
Adopting proactive AI innovation practices
Many leaders admit to not knowing what their industry will look like in three to five years, making proactive collaboration and ecosystem engagement core strategic disciplines to hedge against ambiguity. Organizations should systematically scan for emerging AI technologies, regulatory developments, and ethical considerations, and engage with industry groups, consortia, and public-private partnerships. Working with academia, startups, and technology providers can provide early access to new ideas, tools, and talent, and help test new approaches at lower risk.
This must be matched with a culture of continuous learning and human-AI collaboration. AI tools should be deployed widely but responsibly, with clear guardrails, training, and governance that encourage experimentation while protecting customers, data, and brand. This helps enterprises anticipate disruption rather than simply react to it, and channels diverse external signals into innovation and product roadmaps.
These four imperatives are tightly connected. Stronger leadership alignment makes it easier to invest in the right skills. Better skills and governance increase agility for integration. Active ecosystem engagement feeds into more relevant strategies and use cases. APAC enterprises that approach AI holistically will be best positioned to move beyond pilot purgatory. They will not just keep pace with AI-driven industry disruption; they will help shape the next generation of industry leadership in the AI economy.
Sumash Singh serves as Managing Director for South Asia & Emerging Markets at Dell Technologies. In this role, he oversees the region’s strategic operations, driving business continuity and sustainable growth. He leads the team in aligning regional initiatives with global objectives, ensuring customers and partners have the right technology solutions to move their businesses forward.
An industry leader with over 25 years of technology experience across Asia Pacific, Japan, and Southern Africa, Sumash is passionate about team development and building strong stakeholder relationships. He excels at navigating complex business environments and fostering high-performing teams to deliver transformative, AI-driven outcomes for enterprise organizations. Throughout his career, his strategic vision has positioned him as a trusted advisor committed to empowering customers and industry stakeholders.
Before assuming his current position, Sumash was the General Manager of Dell’s Independent Software Vendors (ISV) business for Asia Pacific, Japan, and Greater China. As a member of the regional executive leadership team, he developed strong software ecosystem partnerships to help customers achieve tangible progress. His tenure at Dell includes leading the Data Protection Sales and Global Digital Cities for APJC, Data Centre Infrastructure Solutions Group (ISG) business in South Asia, and he served as Country Manager for EMC Malaysia prior to its merger with Dell in 2016.
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