What does the democratization of data and AI spell for organizations and their CIOs in Asia Pacific?

Data and AI are powering progress in organizations looking to thrive in the digital economy – with intelligent automation and business insights.

With agility and adaptability keys to business survival and success in the era of data and AI, Asia Pacific CIOs’ priorities and roles are also evolving with the times.

DigiconAsia taps into the expertise of David Irecki, Director of Solutions Consulting, APJ, Boomi, for a deeper understanding of the impact of data and AI democratization on organizations in the region, and on the roles of CIOs now and in the future.

What are the key priorities for Asia Pacific organizations in the era of data and AI?

David Irecki: Customers today have a wealth of options, so businesses will need to be more agile and adaptable. A top priority is to elevate the customer experience. Businesses will need to recognize key touchpoints or moments that matter, if you will, in the overall experience to ensure the strategic priority of extended customer lifetime value.

But there isn’t just stiff competition for customers, it is equally fierce for talent, too. Standing out hinges on giving employees opportunities to do meaningful and fulfilling work. AI and data are both significant enablers here, as they hold the key to making workflows more efficient – which ultimately empowers productivity and employee impact.

David Irecki, Director of Solutions Consulting, APJ, Boomi

Meanwhile, growing competition requires enterprises to find ways to increase distribution leverage, as it significantly amplifies market reach. Businesses will also need to explore ways to diversify and unlock fresh revenue streams. It is imperative that businesses work to build stronger partner ecosystems. This is because they enable collaboration for innovation and growth.

How do you see the CIO role evolving in this new landscape?

Irecki: There is a heightened focus on the CIO’s role – not just on prioritizing technology, but on steering the business itself. Indeed, more than 80% of business executives are accelerating work process digitization by deploying new technologies. The new CIO needs to be a creator, innovator, and disruptor, leading initiatives that extend beyond traditional IT boundaries.

In this brave new world, there is no distinction between IT projects and business ones. Simply put, driving changes cannot come at the expense of business efficiency.

However, it isn’t just about connecting systems or simply using a machine to run a task. No, it’s about intelligent integration and automation acting as a digital nervous system for the digital backbone of the business. By making workflows more intelligent, and optimizing resources, data flows become seamless and deliver comprehensive insights.

In the digital economy, what is the importance of data and AI democratization?

Irecki: As highlighted in a recent ADAPT market analysis, data culture and literacy were significant factors in digital readiness – especially vis-a-vis AI. In other words, because democratization broadens access, it enables both technical and non-technical staff to harness AI tools to drive business value. This is especially important amid the skills gap facing many organizations globally.

Likewise, with regards to data, democratization allows non-specialists to easily access data. Free from requiring specialized tools or skill sets, this enhances decision-making through faster access to business insights.

Both data and AI democratization can provide impetus to promote enhanced organizational success, competitiveness and creativity, particularly in the long run.

How critical is the role of prompt engineers in this age of AI? Is it a transient role or is it one that transforms the tech landscape, fueling business growth?

Irecki: Prompt engineering is intriguing because it cuts across AI and data management, especially because the role of prompt engineers is expanding. Whether it’s a finance department employee using an LLM to provide a summary of financial data or a software engineer using a copilot to write code, the skills that underpin the role are now found throughout organizations.

However, the imperative remains in the breaking down of data silos.

More specifically, as data ecosystems transition from traditional deployments to those augmented with AI, there will be a need to ensure data can be interpreted and understood by AI. This is why the role of prompt engineers will be pivotal to structuring data, supported by integration and automation: prompts that are crafted more effectively, data from the business being used to provide deeper context, and also additional data sources – like real-time analytics – being integrated to enrich AI outputs.

Prompt engineers, too, are leveraging integration and automation tools in more advanced use cases to enhance AI responses, while using the same tools to automate subsequent actions based on AI insights.

How should businesses become AI-ready?

Irecki: Fostering a culture of AI-readiness begins with mindsets. We have to remember that this is a systemic shift for most – if not all – organizations. That means it encompasses people, processes, and platforms. Organizations may have skilled people and a wealth of tools, but they need to assess if they have leveraged intelligent automation and integration for a single-pane view of their data.

Further to that, do they have a culture that is steeped in curiosity, openness, and learning, with strong partners and vendors able and available to provide additional support? Despite swift and cutting-edge progress, it is critical for businesses to approach the implementation of AI deliberately to ensure longevity.

While it’s tempting to see things that way, not all progress is good progress. Businesses need to have practical frameworks in place to promote steady, effective engagement that ensures sustainable and achievable AI strategies. This includes:

      1. Solving current pain points via intelligent integration and automation. Ultimately, each solution to a current problem advances the development of both context and action pipelines.

      2. Breaking down problems into smaller increments to speed up value actualization. This limits impact and raises flexibility.

      3. Relentlessly enforcing a composable approach to solution architectures, enabling digital building blocks to be harvested at every opportunity.