Major hurdles remain in the artificial intelligence journey from pilot projects to enterprise-wide deployment, even as businesses grapple with ambitious AI predictions, according to a new report released by Boomi.
Produced in collaboration with MIT Technology Review Insights, the study includes a global survey of 204 C-suite and senior data executives, of whom 26% is based in the Asia-Pacific region.
Key findings from the report highlight the following trends and challenges.
AI ambitions are substantial, but few have scaled beyond pilots. Fully 95% of companies surveyed are already using AI and 99% expect to in the future. However, few organisations have graduated beyond pilot projects — 76% have deployed AI in just one to three use cases.
As half of companies expect to fully deploy AI across all business functions within two years, this year is key to establishing foundations for enterprise-wide AI.
Also, AI-readiness spending is slated to rise significantly. Overall, AI spending in 2022 and 2023 was modest or flat for most companies, with only one in four increasing their spending by more than a quarter.
Boomi said this is set to change in 2024, with nine in 10 respondents expecting to increase AI spending on data readiness (including platform modernisation, cloud migration, and data quality) and in adjacent areas like strategy, cultural change, and business models.
Two in every five expect to increase spending by 10 to 24%, and one-third expect to increase spending by 25 to 49%.
Further, data liquidity is one of the most important attributes for AI deployment.
The ability to seamlessly access, combine, and analyse data from various sources enables firms to extract relevant information and apply it effectively to specific business scenarios. It also eliminates the need to sift through vast data repositories, as the data is already curated and tailored to the task at hand.
In addition, data quality is a major limitation for AI deployment. Half of respondents cite data quality as the most limiting data issue in deployment. This is especially true for larger firms with more data and substantial investments in legacy IT infrastructure.
Companies with revenues of over $10 billion are the most likely to cite both data quality and data infrastructure as limiters, suggesting that organisations presiding over larger data repositories find the problem substantially harder.
Moreover, companies are not rushing into AI. Nearly all (98%) organisations say they are willing to forgo being the first to use AI if that ensures they can deliver it safely and securely.
Governance, security, and privacy are the biggest brake on the speed of AI deployment, cited by 45% of respondents (and a full 65% of respondents from the largest companies).
“Over the last year, organisations have come to understand the power and potential of AI,” said Matt McLarty, CTO at Boomi.
“This year, those organisations are seeking to shift from small pilots to enterprise-wide deployment of AI at scale,” said McLarty.
