Integration and automation: Key pillars of every IT strategy

As businesses transform for the AI era, the demand for AI and automation tools is growing, intensifying pressure on IT teams to deliver. To stay ahead in an AI-powered future, integration and automation will be essential.

However, across Asia-Pacific (APAC), IT leaders grapple with establishing the governance and processes required to master the basics, with skills gaps, disconnected systems, and compliance concerns among their top issues.

According to MuleSoft’s 2024 Connectivity Benchmark Report, 98% of IT teams in APAC face challenges regarding digital transformation.

The role of the CIO and other IT leaders is more critical than ever. The savviest business leaders turn to their IT leaders to help drive their businesses’ AI strategy forward.

While 87% of IT leaders in APAC expect AI to boost developer productivity, they flag that both security and trust remain barriers to adoption.

Additionally, 64% of IT leaders are concerned with ethical AI usage and adoption, including establishing and communicating a clear strategy for execution that addresses both compliance and skills gap concerns.

Integration is the foundation to connected customer experiences

With the rapid adoption of AI tools among the general public, demand for AI-first customer experiences will follow. Today’s customers expect exceptional experiences supported by well-connected data through integrated systems.

Nearly three-quarters (71%) of customer experiences are now entirely digital in Singapore, but only 26% of organisations report providing a completely connected user experience across all channels.

This is why a single, unified, and real-time view of every customer, at scale, is the intelligent heart of customer engagement. Across all industries, there is a greater need for better integration to unify all structured and unstructured business data to power and deploy trusted, relevant AI across business functions.

By unifying structured and unstructured data, IT teams can discover problems and anomalies in product telemetry. Combining data into one unified platform means AI can identify and flag unusual data points through semantic similarity, alerting teams to any problems with equipment.

While AI has the power to drive efficiency, it is dependent on integrated data, which creates more complexity for integration strategies. Organisations must balance nearly 1,000 applications to create a cohesive experience for end users.

IT leaders acknowledge that data silos and system fragility are holding their companies back from AI adoption. A significant minority of organisations are architected for AI success, with only 2% of organisations in APAC reporting no significant barriers to utilising their data for AI use cases.

Concerns around integration are twofold: the difficulty of integrating generative AI features with other software systems and the need for integration between existing systems.

Organisations that have adopted an integration strategy have reported a vast array of benefits. From customer experience to greater ROI and automation implementation, integration positively impacts the organisation. Failure to close the gap between integrated/connected applications will prevent AI from meaningfully improving employee or customer experiences for most organisations in the foreseeable future.

Democratising automation and establishing data governance will unlock greater productivity

Automation remains a source of contention for IT leaders. IT relies on automation solutions to drive efficiency and provide business users with autonomy. According to McKinsey, current generative AI and other technologies have the potential to automate work activities that absorb 60% to 70% of employees’ time today.

Yet, IT teams are still largely responsible for governing and maintaining the automation process, and the workload required to implement solutions can counter the intended benefits. Around 70% of IT developers in APAC implement and govern automations for business users.

To scale, automation solutions highlight an opportunity for business teams to self-serve and ease the burden on IT.

As businesses increasingly look to automation to drive efficiency, APIs can become a powerhouse for productivity and revenue. IT leaders in APAC report that APIs allow them to increase productivity (50%), drive agility across teams to self-serve IT (48%), and even increase employee engagement and collaboration (45%).

Currently, only 25% of IT leaders in APAC feel their strategy to enable non-technical business users to integrate apps and data sources powered by APIs easily is up-to-date.

Managing and securing the data that underpins these APIs at scale has become increasingly complex. By establishing data governance — setting the rules or policies by which information is collected, managed, stored, measured, and communicated — companies can set the foundations for success.

With the right governance parameters in place, automation can be democratised, freeing up IT teams to tackle technology challenges with increased complexity.

Through the support of the wider business, they can unlock the benefits of AI applications and data integration and governance, paving the way for a more productive, efficient, AI-powered future.