Amidst the inescapable AI hype, many business leaders are understandably skeptical about the potential for AI and intelligent automation to truly transform their business.
Other organizations, however, have already achieved tremendous success with purpose-built AI technology. Hear from innovation leaders at ING and Reveal Group to learn how AI is already being used to generate real value and accelerate operational excellence.
Key drivers for AI adoption
Our studies indicate that 65% of IT leaders adopt AI primarily due to the fear of missing out (FOMO). For the remaining 35%, what drives their investment in AI technologies?
ING's transition to a fully digital bank model aligns with their customers' preference for digital banking. Their goal of improving customer experience facilitated their journey from AI-enhanced robotics and rule-based automation to more sophisticated fintech and data analytics for better business outcomes.
Reveal Group's clients are sometimes driven by the fear of looming obsolescence (FOLO) to adapt to AI, even if it isn't always the perfect solution. Reveal Group's suggestion is not to use AI as a panacea; instead, they propose more practical and efficient solutions. A primary consideration for adopting AI is to revisit stalled automation initiatives and incorporate intelligent document processing (IDP) enhancements for better understanding of unstructured texts.
Businesses also have apprehensions about AI’s inherent risk and vulnerability to inaccuracy. They’re attentive to the sensitivity of information being extracted, and the likelihood of grossly incorrect information being communicated. Thus, hesitations around wholly end-to-end automation continue, making both human-in-the-loop considerations and narrower, specialized applications increasingly integral to businesses’ desired AI tools.
Progress of generative AI initiatives
Regarding the growth of generative AI, the ABBYY State of Intelligent Automation Report indicates that 65% of businesses use third-party generative AI tools, contradicting previous inclinations towards creating custom language models. While the failure rate of generative AI projects decreased from 90% to 75% between 2023 and 2024, companies still grapple with setting unrealistic goals and ensuring the accuracy of data extracted through automation.
While deploying generative AI, businesses focus on identifying areas that will deliver value and experiment with a mix of technologies for comprehensive automation. Generative AI is best employed in complex processes where precision isn't the initial priority.
A case study of ING in Belgium reveals how IDP was used to process complex documents, like salary slips, with 50% straight-through processing (STP) in mortgage applications. This significantly reduced human involvement without compromising the service quality, speeding up the process, and improving customer experience.
From exciting concepts to real value
AI is beginning to round the corner from “this is cool technology, but how will we use it?” to investing in practical, value-enabling applications.
For example, Reveal Group helped a large company accelerate the extraction of over 100 fields from lease-related documents. Facing eight different document types consisting of 80 to 100 pages, Reveal Group devised a pairing of ABBYY’s purpose-built AI OCR with an Azure OpenAI model to streamline the workflow. ABBYY would classify documents, identify key segments and extract data, while the LLM would contextualize and format the information. This strategy exceeded 80% accuracy, drastically reducing the need for over 20 employees to manually comb through these lease documents and extract the relevant data.
This serves as another testament to AI’s greatest potential existing within the combination of several solutions.
Firsthand innovation lessons
The innovation leaders at ING and Reveal Group described the following as the most valuable lessons they learned when implementing AI and intelligent automation:
- Find the right place to start. Analyze where there’s room for AI, where it can expand existing processes, and where it can best augment employees to boost efficiency.
- Set appropriate goals. Unattended end-to-end processes shouldn’t always be the determining factor for success. Start with the mindset of improving employees’ experience.
- Weave contextual business knowledge into innovation strategy. With an understanding of both your business and the new technology, you can leverage both more effectively.
ABBYY recently hosted four webinars for our yearly Intelligent Automation Month. This panel of innovation leaders featured insights from ABBYY Senior Director of AI Strategy Maxime Vermeir, ING Product Area Lead – Intelligent Automation Jeroen van Genuchten, and Reveal Group Automation Insider & Partner Josh Noble. To explore this topic in greater detail, request access to a recording.
Interested in intelligent automation solutions, but not sure where to start? Tell us about your business process challenges and we can find a solution together. We look forward to learning about your digital transformation journey.