Recent analyses from various industry experts indicate that the implementation of artificial intelligence (AI) within organisations is frequently falling short of expectations. Research conducted by Gartner reveals that approximately 30% of generative AI (GenAI) initiatives are likely to remain in the proof-of-concept stage until the end of 2025. The reasons for this stagnation include challenges related to data quality, insufficient risk management measures, and increasing deployment costs.
One significant issue identified is the siloed nature of many AI implementations. According to SS&C Blue Prism, a company specialised in AI and automation, organisations often deploy AI solutions to tackle isolated problems without integrating them into their broader operational frameworks. This approach can lead to missed opportunities for transformative growth and enhanced efficiencies. Furthermore, siloed developments may cause data quality problems, introducing inconsistencies in data formats and storage methods across different teams. As a result, the accuracy and reliability of AI outputs are compromised. In contexts where data security and compliance are critical, establishing comprehensive governance and control measures becomes a necessity.
SS&C Blue Prism posits that a more holistic approach to AI implementation can significantly bolster productivity and innovation while maintaining cost efficiency. According to findings from PwC, companies employing AI methodologies strategically can observe productivity gains of 20% to 30%, alongside rapid market responsiveness and revenue growth. More critically, successful AI initiatives often do not function in isolation; they require integration with comprehensive business automation and orchestration capabilities.
An effective synthesis of AI and automation tools can reshape business operations and redefine workflows. SS&C Blue Prism emphasises the importance of merging various technologies, such as generative AI, machine learning (ML), natural language processing (NLP), and robotic process automation (RPA), with methods like process and task mining and low/no-code development. By employing these technologies concurrently, organisations can develop smarter, more efficient workflows that seamlessly align with their overarching business objectives.
Case studies illustrate the substantive impact of this integrated approach. For instance, an insurance company utilised SS&C Blue Prism to automate its mailroom operations, successfully employing pre-programmed templates to expedite form identification and data extraction. This implementation achieved up to 98% accuracy, effectively replacing manual tasks. Similarly, ABANCA, a retail bank located in Spain, adopted SS&C Blue Prism's intelligent automation along with generative AI and NLP, successfully automating over a thousand tasks. This move enhanced both customer and employee experiences, allowing the bank to respond to customer inquiries 60% faster.
Ultimately, while AI and GenAI can provide standalone value, their maximum potential often lies in conjunction with robust automation and orchestration practices. Thus, organisations that adopt a strategic perspective on AI deployment, viewing it as part of an integrated system, are better positioned to harness the full range of benefits offered by these technologies while effectively managing costs and maintaining a competitive edge.
Source: Noah Wire Services