Despite the huge promise surrounding AI, many organizations are finding their implementations are not delivering as hoped. Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs.[1]
The limits of siloed AI implementations
According to SS&C Blue Prism, an expert on AI and automation, the chief issue is that enterprises often implement AI in siloes. When AI solutions are designed to address isolated problems without integrating broader organizational data and insights, they miss opportunities to drive transformative outcomes.
These narrow approaches also exacerbate data quality issues, as discrepancies in data format, consistency, and storage arise across disconnected teams, reducing the accuracy and reliability of AI outputs. Reliability and security is paramount. Without the necessary guardrails and governance, AI can be harmful. Automation takes care of end-to-end processes while also providing a detailed audit trail. With AI now incorporated into this trail, automation can ensure compliance, trust and accuracy – critical factors in any industry, but especially those working with highly sensitive data.
Moreover, siloed initiatives can lead to duplicated efforts, with different departments independently developing overlapping AI capabilities, resulting in wasted time, inflated costs, and diminished efficiency.
Taking a holistic approach to enterprise AI
However, when AI is implemented effectively it can dramatically enhance productivity and innovation while keeping costs under control. According to PwC, organizations can experience incremental value at scale through AI, with 20% to 30% gains in productivity, speed to market, and revenue, on top of “big leaps” such as new business models.[2]
For SS&C Blue Prism, the key to success in AI lies in deploying the technology holistically across the enterprise and integrating AI technologies alongside comprehensive business automation and orchestration capabilities.
SS&C Blue Prism argues that combining AI tools with automation is essential to transforming operations and redefining how work is performed. By leveraging AI technologies such as generative AI, machine learning (ML), natural language processing (NLP), and computer vision in combination with robotic process automation (RPA), process and task mining, low/no-code development, and process orchestration, organizations can create smarter and more efficient workflows.
Transforming the enterprise with AI
In this approach, businesses are able to move beyond isolated implementations, aligning AI-driven insights and automation capabilities with enterprise-wide objectives. For example, process and task mining can uncover inefficiencies and identify opportunities for optimization, while RPA and low/no-code platforms can empower teams to automate repetitive tasks and develop solutions rapidly.
Meanwhile, AI-powered tools like NLP and computer vision can enhance these workflows by enabling greater understanding and interaction with unstructured data. When orchestrated effectively, these technologies drive scalable transformation, allowing businesses to innovate, respond to changing demands, and enhance productivity seamlessly across functions.
AI in action
The benefits of this approach are clear to see. One insurance company, for instance, automated its mailroom with SS&C Blue Prism, using pre-programmed templates to quickly identify and reorder forms and extract typed and handwritten data, SS&C Blue Prism helped the company replace manual tasks with up to 98% accuracy.[3]
Meanwhile, ABANCA, a Spanish retail bank, has used SS&C Blue Prism’s intelligent automation, generative AI, and NLP to automate over a thousand tasks, which improved customer and employee experience and allowed it to respond to customer inquiries 60% faster.[4]
On their own AI and GenAI can deliver value. However, it’s only when combined with automation and orchestration that the technologies’ full potential can be unlocked. Clearly, organizations that think strategically about AI and deploy it as an integrated, holistic system stand to unlock the full benefits of the technology, control costs, and outpace their peers.
[1] Gartner, Gartner Predicts 30% of Generative AI Projects Will Be Abandoned After Proof of Concept By End of 2025, July 2024 https://www.gartner.com/en/newsroom/press-releases/2024-07-29-gartner-predicts-30-percent-of-generative-ai-projects-will-be-abandoned-after-proof-of-concept-by-end-of-2025
[2] PwC, PwC’s October 2024 Pulse Survey, October 2024, https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.html
[3] SS&C Blue Prism, Mailroom Automation: AI Replaces Manual Tasks with Up to 98% Accuracy, https://www.blueprism.com/resources/case-studies/digitizing-the-mailroom-ai-system-eliminates-manual-tasks-with-up-to-98-accuracy/
[4] SS&C Blue Prism, IA and Generative AI Help ABANCA Respond 60% Faster to Customer Inquiries, https://www.blueprism.com/resources/case-studies/abanca-customer-experience-cx-generative-ai/
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Source: News