Lessons Learned: Focus on YOUR High-Value Use Cases
Small and medium-sized companies (fewer than 500 people) are finding that purpose-built artificial intelligence (AI) applications – those aimed at specific problems – generate more immediate value than open initiatives and experiments. Practical AI applications such as automatic bank reconciliations, accounts receivable/payable automation, and internal decision support are enabling businesses to realize quick and tangible benefits.
For example, platforms that are highly specialized in performing reconciliations (in sales, banking, accounting, credit card vouchers and others) are managing – in a consistent and stable way – to automate up to 93% of the items to be reconciled that were previously carried out manually. In practical terms, this means that a complex reconciliation that took 5 days for a single person can today become an effort of only 4 hours, thanks to multiple AI algorithms, specialized in reconciliation only, which provide a fast recovery time and an ROI that makes sense for the investment.
The old phrase “show me the money first”, as an analogy to the tendency in decision-makers not to invest in expectations without a solid business case, but only in use-cases applicable to concrete problems and with an immediate return on investment is reflected in the latest customer surveys of 2025 by both Source Global, the “Gartner of the consulting world” as well as by studies by Gartner itself.
Source Global indicates that companies want to see in their advisors the ability to execute on new technologies, not just ideas.
From experimentation to execution
The key to success in the implementation of AI in companies lies in focusing on specific problems, identifying clear and high-value use cases in terms of the problems or situations they solve and measuring concrete results. Most failures or stalling behavior in AI projects are due to a lack of clear focus and measurable goals. It also seems not to have a good investment-to-return ratio the practice of training personnel in artificial intelligence without having a clear mandate, a problem to solve and assuming they will figure out how to use their new skills. Even if there is a culture prone to innovation, without a clear mandate, enterprises and other types of organizations do not seem to achieve traction in terms of business results derived from their “blank-check” initiative.
Examples of high-value use cases that you can start using for generating ideas for your business
Banking, Finance & Accounting
AI-powered reconciliations (purpose-built algorithms): Reconciliations go far beyond just accounting. Today’s technology is able to resolve “one-to-one,” “one-to-many,” and “many-to-many” reconciliations in 93% of cases. The use of this technology has applications in multi-acquiring contracts, event tickets, card processor settlements, bank collection and collection, cards, e-commerce gateways like Stripe and other payments (AFAQ, Aani or IPI in the GCC, ECACH in the Caribbean or others in Latin America depending on the different countries), travel agencies, invoicing and taxes and contract accrual. At EXYGE.COM we address all of these use cases with our technology partner DaMap.
Financial Statement Analysis and Complex Reporting from multiple data sources: Although the common generative artificial intelligence that we have today, such as ChatGPT, Qwen, Mistral or Deepseek can do a lot for the analysis of financial statements from data in an MS Excel file or in a PDF, when reporting or the required analysis uses multiple data sources, some from ERP, others from pheripheral systems or even from unstructured manual sources (Excel lists filled out by hand or extracted exports from old systems, this task is quite complicated for a general-purpose AI and can generate inconsistent results through several runs, since the same “prompt” can generate different results. Creating and deploying a custom AI model can process the different data sources consistently in every run, resolve common discrepancies based on the business rules provided during model training with your internal data, combine the different data sources and analyze the results, compare trends and with historical data, as well as suggest variations and alert on new patterns that may be of interest. A personalized, secure, and private model can consistently analyze your data, regardless of who runs it, lowering the impact of specialized staff turnover or an unforeseen event that makes difficult to access specialized personnel who does the data transformation. At EXYGE.COM we can approach all these cases in various ways depending on several factors, applying AI in data transformation and visualization tools or generating all the processing and analysis encapsulated within a single AI model with our partner DiscoveryAI.
Granting of credit in companies, banking institutions and savings and loans cooperatives: AI models specialized in credit scoring address two high-value uses: the predictive determination of the credit potential of a requestor and the prediction of payment delays or delinquent loans within those already granted. This type of use case leverages ML (Machine Learning) in models trained in a secure and private way with your company’s historical data. They are internally trained models where the same AI engine can be hosted on-premise, if company policies or regulation require it. Although the accuracy of these models depends on the quality and availability of the data within the organization, results obtained from prior cases do have an assertiveness of 76% for credit analysis and 88% in the prediction of delinquencies and defaults. At EXYGE.COM we approach these cases with our technology partner DiscoveryAI. Click here to learn more about tailored AI models with complete privacy of your data.
Retail (supermarkets, convenience stores, department stores)
Demand Analysis: which allows identifying patterns in consumer preferences, segmentation, personalization and challenges associated with the growth and expansion of new branches. These models study historical data from sales, inventories, transfers between warehouses and other information to discover patterns of consumer behavior, incipient trends in purchasing and obtain alerts, conclusions and recommendations on the evolution of day-to-day sales and inventories at a level of detail that is impossible for a human being. Using this technology, a chain of mini-markets in Brazil, with more than 250 stores and a portfolio of more than 2000 SKUs was able to:
- Optimize the product mix for each store, based on consumer preferences.
- Predict mini-market demand for “Top 100” SKUs with 85% to 95% reliability depending on the product line.
- Save on SKU management, transfers between warehouses, reduce obsolescence and shelf-life expiration.
Profitability optimization through better management of the product mix: AI models customized with sales and inventory data. Superior analysis of custom and trained models can:
- Analyze and answer complex questions that require analyzing large volumes of data.
- Track patterns that maximize profitability with a focus on sustainability.
- Constantly monitor consumer trends in order to take early action and react quickly to variations in consumption.
- Consolidate resources and avoid duplication.
In a wine manufacturer, the use of this technology achieved reductions in distribution costs (5% to 25%), increased profitability due to dynamic price management (5% to 20%), reduction of average inventory (10% to 20%) and minimization of stock-outs, producing an increase in income of up to 15%. Similar results have been obtained in breweries and dairy manufacturers. At EXYGE.COM we approach these cases with our technology partner Discovery AI.
Customer Service
Personalized interactions and customer support: Models trained on CRM data on customers and cross-referenced with customer consumption (sales) patterns can increase customer retention (10% to 20%) and customer value throughout the entire customer lifetime by 5% to 15%, through:
- Personalized interactions based on customer behavior and preferences.
- Increased customer loyalty through targeted marketing campaigns and personalized experiences.
- Provision of instant response – based on AI – to customer queries (both B2C and B2B).
Predictive Maintenance (Buildings, Equipment, Manufacturing Plants, Fleets)
Cost Reduction and Reliability Improvement: Through the historical analysis of information regarding repairs, supplies, repair costs and cross-referencing this information with that of equipment, trucks, real estate locations, and other type of operational records, downtime and costs associated with maintenance can be reduced:
- Monitoring the equipment health and its metrics, predicting some failures before they occur.
- Proactively planning maintenance, reducing downtime and extending equipment life.
- Lower maintenance costs and disruptions to manufacturing runs.
- Ensure greater consistency in product quality and operational reliability of the plant, fleet, or facility.
The role of consultants: strategy and execution
Companies, regardless of their size, often require outside help to maximize the value of AI. It’s prudent while choosing your consulting provider to look not only for strategic guidance, but also for technical execution capabilities within the same provider (integration with existing systems, training, and hands-on support), ensuring that the AI initiative delivers real results.
It is also important that your digital transformation project, whether with artificial intelligence or any other innovative technology, has clear objectives for knowledge transfer and training of your staff. The consultant’s specialist knowledge can be crucial for the quick progress of the project, but the sustainability of the initiative will depend solely on how well you can assimilate the knowledge and become autonomous in the technology in the long term.
Practical takeaways for CEOs and CFOs
- AI has a real impact when it is clearly geared towards solving specific problems whose resolution provide high value to the business.
- Managed staged implementations with clear metrics will facilitate the effective adoption of AI.
- Collaboration with external experts is key to accelerating results and to ensure assimilation and knowledge transfer to internal staff for long-term sustainability.
Specialized AIs are already a successful reality in companies of all sizes, enabling faster, more accurate and more profitable operations. Adopting this hands-on mindset turns AI into a real business enhancer, achieving efficiencies typical of large enterprises, while maintaining mid-market agility.
Finally, while we’ve focused this article on purpose-built AIs, commonly used generative AI (the one we see with ChatGPT, Gemini, Perplexity, Qwen, DeepSeek, Claude, and others) can also benefit from some of the lessons outlined here:
- Identify use cases where there’s a problem to solve or a task to accelerate that represent high value for the business.
- Make a simple and practical business case, or a simple project charter that establishes:
- the problem or situation to be improved
- the current state in numerical terms (how much it costs today, how long it lasts, how many errors are generated, etc.)
- the expected goal or expectation that defines what a successful results look like
- Document the results (time saved, reduced errors, lower cost, better decisions, or any other)
- Manage your learning and acquired knowledge:
- Document your lessons learned
- Identify your developed skills and record them in some form (nowadays making mini-videos with Loom or another application is very simple)
- If you have acquired any specific knowledge, structure it in a way that someone new or who does not have the context of the project can understand it.
- Categorize and store your acquired knowledge in the new technologies in an orderly manner. Something as simple as a repository on a network disk where charters or initiatives are saved and a master table that helps you navigate each initiative can do wonders with your AI knowledge management.
Final Thoughts
Specific artificial intelligence is no longer a distant promise, but a tangible reality that generates immediate and significant results for small, medium, and large companies. As a CEO or CFO, you know that every strategic decision must be clearly justified in terms of profitability, efficiency, and operational improvement.
That’s where EXYGE.COM can be your decisive ally: our approach combines deep strategic and operational expertise with practical technology execution capabilities, ensuring your AI investment generates measurable and accelerated impact from day one. We invite you to take a step forward, to transform the promise of AI into concrete benefits for your company. Contact us at EXYGE.COM and together let’s take your business to the next level of practical application and demonstrable success.
