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Applied AI: Real-World Solutions for Business Transformation

Applied AI delivers targeted, industry-specific solutions that enhance efficiency and collaboration. AnalystAccelerator.ai exemplifies this by modernizing payments for banks, integrating seamlessly with existing tools and delivering gold standard business, system and QA analyst documentation. 

8 min read

Artificial intelligence (AI) has rapidly moved from a niche interest to a transformative force driving change across industries globally. 

Among its many branches, Applied AI is generating particular interest for its capacity to deliver in a practical, real-world, and tailored manner, addressing specific needs and challenges faced by businesses.   

Unlike General AI, which focuses on creating systems that mimic broad human capabilities, Applied AI focuses on targeted solutions, delivering tangible value in complex environments. 

How do we define Applied AI?

Put simply, Applied AI is the implementation and targeting of AI areas, such as machine learning, natural language processing (NLP), Large Language Models (LLMs) and data analytics, in specific, practical applications that directly address business problems.   

By targeting defined existing use cases, Applied AI ensures businesses can maximize efficiency, optimize workflows, move faster as they modernize and gain a competitive edge. It turns theoretical capabilities into usable tools that integrate into existing operations and help humans work much smarter and faster. 

What are its key components?

  • Domain-Specific Knowledge: Applied AI systems are trained on data and rules specific to a particular industry, enabling high accuracy and relevance in outputs. Unlike general AI, which aims to mimic human intelligence broadly, Applied AI narrows its scope to focus on precision and expertise. 
  • Integration with Existing Workflows: Applied AI doesn’t exist in a vacuum; it integrates smoothly with existing systems and tools, augmenting what teams already rely upon rather than overhauling entire systems. 
  • Human-AI Collaboration: Applied AI enhances, rather than replaces, human intelligence. It partners with human experts, providing them with enhanced insights and automating mundane tasks, so humans can focus on higher-value activities.  

The main differences between Applied AI and General AI

  General AI Applied AI
 

Training

   

  • Trained on everything: low quality in = low quality out.
  • Trained on relevant industry or project-specific data only.
Optimisation 
  • Optimised for speed: best answer = the quickest.
  • Optimised for accuracy: best answer = the most reviewed, supported by evidence.
Implementation   
  • Broad / non-specific – needs careful integration and controls across systems.
  • Leverages existing technologies and tools – easier to implement and maintain.
Decision-making 
  • Can operate outside of its remit to autonomously make decisions in an unpredictable way.
  • Designed to assist humans.Final decisions made by experts who understand context and potential implications. 
ROI 
  • Broad applications with unknown impact on current processes.
  • Quantifiable impact in automating specific tasks. Easily calculate human time saved. 

AnalystAccelerator.ai: A Best-Practice Example of Applied AI

AnalystAccelerator.ai from RedCompass Labs is an illustration of how Applied AI drives meaningful impact in the financial sector. 

The solution focuses on accelerating payments modernization for banks—a complex challenge involving regulatory compliance, intricate workflows that require extremely detailed design and documentation, and high security standards.  

By taking an AppliedAI approach, we are able to ensure our solution delivers tangible and measurable efficiencies for our clients whilst reducing the risk of go live incidents. 

How AnalystAccelerator.ai Harnesses the Principles of Applied AI

Industry-Specific Optimization: AnalystAccelerator.ai draws on 20 years of RedCompass Labs’ world leading payments expertise and knowledge from over 300 successful payments projects from around the globe. It is trained using payments-specific data, regulations, and industry insights, ensuring it delivers precise and highly relevant outputs tailored to banks’ modernization efforts. 

Seamless Integration: AnalystAccelerator.ai works with widely used tools such as JIRA, Confluence, MS Teams, and SharePoint, embedding AI capabilities within the existing workspace of payments teams. By integrating with these tools, AnalystAccelerator.ai can significantly accelerate project timelines without disrupting established processes. 

Enhanced Collaboration and Knowledge Management: Applied AI enables banks to build institutional knowledge. AnalystAccelerator.ai captures institutional expertise, transforms it into actionable insights, and provides detailed documentation, creating a hub for collaboration and learning across payments teams. This empowers teams to produce high-quality business requirements, test scenarios, and more at a fraction of the typical time and cost. 

Proactive Risk Management: AnalystAccelerator.ai harnesses AI agents to handle complex tasks and analysis while maintaining a high degree of human oversight, ensuring compliance and minimizing risks. With up-to-date regulatory data and the ability to process nuanced requirements, it de-risks modernization programs, delivering safer, faster project outcomes. 

More than a tool… a whole new way of working  

The evolution of Applied AI is reshaping industries by addressing sector-specific challenges head-on. In banking, where precision, compliance, and speed are paramount, AnalystAccelerator.ai demonstrates how Applied AI transforms ambitious goals into achievable realities. 

By optimizing workflows, informing decision-making, and empowering human talent, Applied AI is more than a tool—it is a catalyst for the next wave of business innovation.  

Applied AI transforms theoretical potential into business-changing results. AnalystAccelerator.ai demonstrates how harnessing this power within a specialized context, such as payments modernization, create gold standard documentation that can drive efficiency, reduce costs, and help ensure project success.  

As organizations continue their digital transformations, embracing Applied AI is key to improving outcomes and staying ahead in a competitive market.

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Written by

Raquel Payments Expert AI

AnalystAccelerator.ai

Payments Expert AI, RedCompassLabs


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