Boomi Releases Strategic Playbook for Effective AI Adoption
Boomi, the intelligent integration and automation leader,
announced the release of a new report, “A Playbook for
Crafting AI Strategy,” produced in collaboration with MIT Technology
Review Insights. This comprehensive study — which includes a global survey of
C-suite and senior data executives, including in-depth interviews conducted
with business leaders on data and AI — sheds light on the current state of
enterprise AI adoption, and offers actionable strategies for navigating the
transformative landscape of artificial intelligence.
As businesses grapple with ambitious AI predictions — such as PwC's
forecast that AI could contribute an astounding $15.7 trillion to global GDP by
20301 — major hurdles remain in the journey from pilot projects to
enterprise-wide deployment. As an example, just 5.4% of US businesses utilized
AI to produce a product or service in 2024,2 signifying a
pressing need for strategic and organizational shifts to leverage AI
effectively.
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. But
few organizations 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.
· 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. That is set to change in
2024, with nine in ten respondents expecting to increase AI spending on data
readiness (including platform modernization, cloud migration, and data quality)
and in adjacent areas like strategy, cultural change, and business models. Four
in ten expect to increase spending by 10 to 24%, and one-third expect to
increase spending by 25 to 49%.
· Data liquidity is
one of the most important attributes for AI deployment. The ability to seamlessly
access, combine, and analyze 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.
· 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
organizations presiding over larger data repositories find the problem substantially
harder.
· Companies are not
rushing into AI. Nearly all organizations (98%) 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, organizations have come to understand the power and
potential of AI,” said Matt McLarty, CTO at Boomi. “This year, those
organizations are seeking to shift from small pilots to enterprise-wide
deployment of AI at scale.”
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