How Enterprises Can Prevent AI Project Production Failure
Enterprise organisations are facing a substantial implementation gap in AI projects, with more than two-thirds failing to reach production environments, according to research recently released by SS&C Blue Prism.
The automation company’s 2025 Global Enterprise AI survey gathered insights from 1,650 CEOs, CTOs and IT leaders across financial services and healthcare enterprises in the Americas, Europe and Asia-Pacific, highlighting some of the main challenges that prevent organisations from realising returns on their AI investments.
The findings come at a time when 92% of organisations report using AI to transform operations, yet 55% acknowledge they have seen limited benefits from these initiatives.
SS&C Blue Prism identifies process orchestration as enterprise AI adoption prerequisite
Process orchestration emerges as a fundamental requirement for successful AI implementations, with nearly 94% of respondents identifying it as an essential component of their technology stack to enable effective end-to-end AI management.
“AI adoption is advancing rapidly. Success depends on careful strategic planning, ethical governance, and workforce readiness,” said Rob Stone, Senior Vice President and General Manager of SS&C’s Intelligent Automation and Analytics business. “Organisations realise these foundations are critical to minimising risk inefficiencies and security vulnerabilities.”
The research indicates that organisations face persistent data challenges, with 44% reporting insufficient systems to effectively move large data sets, while 41% struggle with inaccurate and inconsistent data.
Trust remains a significant concern among enterprise decision-makers. Despite growing interest in autonomous automation — with 29% of respondents already implementing such systems and another 44% planning deployments within the next year — the report found that 78% of organisations express a lack of full confidence in AI tools.
SS&C research reveals security and skills shortages constrain enterprise AI scaling efforts
Security and compliance concerns represent the most significant barriers to AI adoption, cited by 37% of respondents. These issues reflect the complex regulatory landscape surrounding AI implementation and the potential risks associated with deploying these technologies in regulated industries.
The skills gap presents another substantial challenge, with 35% of respondents identifying shortages of specialised expertise as a limiting factor in their AI initiatives. This shortage occurs despite 84% of business leaders recognising AI's potential to transform traditional work practices.
“Striking the right balance between speed, governance and strategic alignment is crucial,” Rob adds.
Integration complexities rank equally with skills shortages (35%) as organisations attempt to incorporate AI systems into established technical infrastructures without disrupting operations.
SS&C Blue Prism survey highlights workforce transformation in enterprise AI implementation
The research reveals a workforce in transition, with organisations actively preparing employees for an AI-augmented work environment. Approximately 40% of businesses report upskilling employees for new or expanded roles related to AI implementation and management.
- More than two-thirds of advanced AI projects fail to reach live business operations
- 55% of organisations report seeing limited benefits from AI implementations despite 92% using AI to transform operations
- 78% of organisations lack full confidence in AI tools, limiting adoption and effective utilisation
- Security concerns (37%), skills shortages (35%), and integration complexities (35%) represent the primary barriers to enterprise AI adoption
Employees appear to recognise potential opportunities in this transformation, with 40% anticipating the creation of new AI-specific job functions. Additionally, 34% expect to focus on supporting AI adoption, while 31% foresee transitions to more creative and strategic work as AI assumes routine tasks.
Despite widespread implementation efforts, measurements of AI’s business impact reveal inconsistent results. While 88% of organisations monitor the value derived from AI investments, only 36% report consistent, recognisable returns, highlighting the need for refined implementation strategies.
The autonomous capabilities of AI systems continue to attract significant interest, with nearly three-quarters of organisations either implementing or planning to implement autonomous automation within the next year. However, the trust deficit remains a challenge that organisations must address through appropriate governance frameworks.
“Investing in upskilling, building ethical frameworks and adopting enabling technologies such as process orchestration helps ensure long-term success and maximise opportunities,” says Rob. “The enterprise AI revolution is here. Unlocking its full potential depends on holistic, sustainable adoption strategies.”
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