The Power of Intent: AI Deployment Drives Business Growth

In today’s competitive landscape, business success hinges on implementing a deliberate strategy. From product development to market expansion, every decision needs a well-defined roadmap to success because even the most ingenious concepts can fizzle out and gather dust without a clear purpose and goals understood at every level across the business. This principle becomes even more crucial when businesses grapple with the complexities of rapidly developing technologies like Generative AI (GenAI).

According to a 2024 survey by Gartner Report, in the last 10 months, 50% of the organisations globally have increased investment in GenAI, 44% are piloting towards it, and 10% have put it into production. Similarly, IBM Data shows that China (85%), India (74%), and the UAE (72%) are the markets most likely to be accelerating AI rollout. In comparison, businesses in the UK (40%), Australia (38%), and Canada (35%) were the least likely to accelerate the rollout. While it is clear that companies are aware of how Gen AI presents a unique opportunity to drive innovation and productivity at scale, acting with intent is key to unlocking true value for businesses.

Align business goals and AI strategy

While the potential of Gen AI tools is established, just deploying them doesn't ensure success. Without clear goals and alignment between AI strategies and business objectives, enterprises risk wasting resources and missing opportunities. Business leaders need to take decisive action to accelerate AI adoption. Being intentional is key to achieving a positive return on investment.

The first step is establishing a clear data strategy to treat data as a strategic asset. By aligning its use with business priorities, companies will be able to harness the power of Gen AI to streamline workflows and garner business critical insights.

Next, cultivating a learning culture that starts from the top is key. Leaders should clearly communicate their organisation’s AI strategy and goals to pave the way for the workforce to trust and work alongside this evolving technology. Lastly, equipping the workforce with essential resources, skills, and knowledge through training programs will ensure employees have the capabilities and expertise to keep pace with the constantly changing applications of AI.

Backing your AI strategy with modern infrastructure

Legacy infrastructure's decentralized nature often traps valuable data in outdated, siloed systems, leading to data sprawl that hinders extracting actionable insights for AI models. Cloudera’s recent “State of Enterprise AI and Modern Data Architecture” survey showed that common challenges organisations face in accessing all their data include contradictory datasets (49%), an inability to govern data across platforms (36%), and too much data (35%).

Organisations with access to high-quality, diverse data can leverage it to streamline AI operations, maximise the return of IT investments, and unlock new business opportunities. However, companies that do not modernise their stack risk fall behind.

To move away from legacy systems, businesses need to invest in a scalable, secure, and resilient data architecture to support increasing data workloads generated from AI models. Real-time data processing, storage, and integration, allow organisations to fully leverage AI for task automation and budget optimization.

For instance, Bank Negara Indonesia is using GenAI to improve productivity in regional and commercial banking, enhance its credit mechanisms, and offer a more personalized customer experience. This latest deployment will help the bank quickly scale its AI operations to better serve a global customer base and deliver more value to stakeholders.

Furthermore, modern data platforms encourage a data-driven culture, enabling AI-driven insights to guide product development, marketing, and customer service. The platform provides universal data access, ensuring consistent security and governance to make all data AI-ready, accelerating decisions and offering a competitive edge.

One such company taking these steps to augment their customer experience is PT Bank OCBC NISP - they see technology and customer experience as intertwined and have implemented a hybrid data strategy that integrates with their data lake. Implementing such modern data technology paves the way for the bank to launch GenAI projects to remain at the forefront of the banking industry.

Using trusted data to create lasting impact from AI

Since AI systems hinge on having large volumes of data, the real challenge is ensuring that data is trustworthy. This should form the foundation of any organisation looking to deploy an AI solution. A secure and agile platform enables reliable insights, speeding up decision-making and supporting business critical data-driven strategies to drive success.

Strategic implementation of Generative AI involves setting clear objectives, fostering transparency, and building a strong data foundation. This journey requires collaboration among leaders, technical teams, and employees to address ethical considerations and ensure AI serves as a tool for lasting impact, not just novelty.

By Mayank Baid, Regional Vice President, India, Cloudera