Where Can Generative AI Be Used to Drive Strategic Growth?

TL;DR

• Investment in GenAI is increasing, with nearly half of surveyed organisations planning to spend over $1 million.
• Challenges include resource shortages, knowledge gaps, and IT constraints.
• GenAI use cases are expanding across traditional and non-traditional business functions.

Generative AI: The Engine Driving Strategic Growth in Asia

As Generative AI (GenAI) evolves from a technological novelty to a core business driver, organisations across Asia are ramping up investments to capitalise on its transformative potential. A recent survey by Dataiku and Databricks, summarised in the report “AI, Today: Insights From 400 Senior AI Professionals on Generative AI, ROI, Use Cases, and More”, sheds light on how leaders are leveraging GenAI to navigate challenges, unlock new use cases, and drive measurable returns. Read the full report here.

A Strategic Commitment

Investment in GenAI is skyrocketing, with nearly half of the surveyed organisations planning to spend over $1 million on GenAI initiatives in the next year. This financial commitment signals a decisive move beyond experimentation toward strategic integration. With 90% of respondents already allocating funds—either from dedicated budgets (33%) or integrated into broader IT and data science allocations (57%)—GenAI is becoming an indispensable part of enterprise strategy.

However, only 38% of organisations have a dedicated GenAI budget. This indicates that while enthusiasm for GenAI is high, it often competes with other priorities within broader operational budgets.

Realising ROI Amidst Persistent Barriers

While 65% of organisations with GenAI in production report positive ROI, others struggle to achieve or quantify value effectively. Key challenges include:

• Resource Shortages: 44% lack internal or external resources to deploy advanced GenAI models.
• Knowledge Gaps: 28% of employees lack understanding of how to effectively utilise GenAI.
• IT Constraints: 22% face policy or infrastructure limitations, impeding GenAI adoption.

Cost remains a consistent concern, with unclear business cases ranking as a major barrier. For organisations aiming to justify investments, robust ROI measurement frameworks and employee upskilling programs are essential.

Expanding Use Cases: GenAI’s Versatility

One of GenAI’s defining strengths is its adaptability across business functions:

• Traditional Use Cases: Finance and operations lead in leveraging predictive analytics and automation.
• Non-Traditional Departments: HR and legal are exploring GenAI for recruitment, compliance automation, and contract management.
• Emerging Applications: Marketing teams use GenAI for personalised content creation, while R&D integrates it for simulation and prototyping.

The flexibility of GenAI is especially relevant in Asia, where diverse industries face unique challenges that GenAI can address.

AI Techniques Powering Transformation

The survey highlights key AI techniques that organisations are actively using:

• Predictive Analytics (90%) and Forecasting (83%) dominate in deployment.
• Large Language Models (LLMs) and Natural Language Processing (NLP) are widely adopted for understanding and generating human-like text.
• Reinforcement Learning and Federated Machine Learning are gaining traction, enabling advanced decision-making and secure data collaboration.

AI Pioneers: Setting the Standard

The survey identifies “AI Pioneers”—organisations that excel in AI adoption by combining advanced frameworks, ROI measurement, and significant investments:

• 54% of pioneers plan to spend over $1 million on GenAI, compared to 35% of their peers.
• Pioneers report higher confidence in leadership understanding of AI risks and benefits, with 69% achieving positive ROI from GenAI use cases.

These organisations often operate under mature models, such as the “Hub & Spoke” or “Embedded” structures, which facilitate cross-department collaboration and innovation.

Shifting Sentiments Around AI

Fears surrounding AI have become less polarised:

• Only 4% of respondents are “more worried than excited” about AI, down from 10% last year.
• Confidence in leadership understanding of AI risks and benefits rose by 12% year-over-year, reaching 56%.

This shift suggests that organisations are adopting balanced and pragmatic approaches to integrating AI into their operations.

The Path Forward for Asia-Pacific

Asia-Pacific businesses, known for their tech-forward mindset, are uniquely positioned to harness GenAI. However, success will depend on addressing key challenges:

1. Building Knowledge: Invest in employee training to bridge knowledge gaps and empower teams.
2. Strengthening IT Infrastructure: Simplify systems to align with GenAI’s demands.
3. Quantifying ROI: Implement frameworks to measure returns, ensuring GenAI investments deliver clear business value.

Conclusion

The Dataiku and Databricks report demonstrates that GenAI is not only reshaping industries but also redefining organisational priorities. For Asia-Pacific, the opportunity is clear: lead the charge by embedding GenAI into core strategies, leveraging it across diverse functions, and overcoming barriers with strategic investments in talent and technology.

By doing so, organisations can unlock measurable returns and maintain a competitive edge in the global AI landscape. For an in-depth dive into the findings, access the full report here.

Join the Conversation

Interested in how Generative AI can drive strategic growth for your organisation? Share your thoughts and experiences with GenAI integration, challenges, and successes.

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