81% of IT Leaders report the persistence of data silos, and 72% cite the fragility of tightly coupled and highly dependent systems as top challenges holding them back from AI adoption.]
For businesses looking to stay ahead in an AI-powered future, integration and automation will be essential. The role of the CIO and other IT leaders is becoming more critical than ever. The savviest business leaders are turning to their IT leaders to help drive their businesses’ AI strategy forward. While 85% of IT leaders expect AI to boost developer productivity, they flag that both security and trust remain as barriers to adoption. An additional 64% of IT leaders are concerned with ethical AI usage and adoption.
This includes 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 adoption of AI tools rising rapidly among the general public, demand for AI-first customer experiences will follow. Today’s customers have come to expect exceptional experiences supported by well-connected data through integrated systems.
Nearly three-quarters (70%) of customer experiences are now entirely digital, but only 26% of organizations 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’s a greater need for better integration to unify all structured and unstructured business data to power and deploy trusted, relevant AI across business functions.
While AI has the power to drive efficiency, it is dependent on integrated data, and it’s creating more complexity for integration strategies. Organisations having to balance nearly 1000 applications to create a cohesive experience for end users.
IT Leaders acknowledge that data silos and systems fragility are holding their companies back from AI adoption. Over 90% of IT leaders are experiencing integration issues.
A significant minority of organisations are architected for AI success, where only 2% report no significant barriers to utilising their data for AI use cases. Concerns around integration are twofold: the difficulty 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, more significant 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 for 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 percent of employees’ time today.
Yet IT teams are still largely responsible for governing and maintaining the automation process, and the workload that is required to implement solutions can counter the intended benefits.
With the right governance parameters in place, automation can be democratized, which would free up IT teams to tackle technology challenges with increased complexity.
With 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.
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