Legal management is increasingly no longer operational and assumes a role that is not only strategic, but also indispensable for business. What seemed like a trend a few years ago is now a clear requirement: efficiency, compliance, and innovation have come to define the future of the legal sector. But what will really make a difference in 2025?
According to Daniel Parra, CEO of Intelligenti Stefanini, the legal department is no longer an area separate from the business. "He needs to be connected to organizational goals, acting as a strategic partner. Technology is the factor that makes this transformation possible," he explains.
And in this content, you'll see valuable insights to put into practice in your department this year.
1 – Efficiency: A New Way of Seeing
Automating processes is no longer just a competitive advantage – it's a necessity. With the increasing complexity of demands and the volume of data, traditional methods can no longer keep pace.
"We're seeing a paradigm shift literally. Repetitive tasks, such as contract review and document management, are absorbed by technology. This frees up teams to focus on what really matters: strategic and high-impact decisions," says Parra.
2 – Compliance as a strategic differential
In a scenario where regulations become increasingly stringent, ensuring compliance is not only an obligation, but also an opportunity to stand out in the market.
After all, technological tools not only ensure compliance, but also bring control and predictability, reducing risks and strengthening trust between customers and partners.
3 – Artificial Intelligence: Integrated and Essential Resource
Artificial Intelligence (AI) has already proven its worth in areas such as predictive analytics and flow automation, but by 2025 it will be a key piece of the efficiency puzzle.
According to the executive, AI this year will be a powerful resource, but the big difference will be in how it will be used. "It won't be about putting technology at the center, but about making it part of a strategic ecosystem that connects people, processes, and outcomes."
4 – Business Development: A Pillar of Strategic Legal
Business Development (BD) is no longer exclusive to commercial areas. In 2025, he will take a central role in legal management, helping departments identify opportunities, build relationships, and generate real value.
"Integrating legal into business goals will be more than a trend – it will be the key to generating sustainable results and preparing the organization for the future," explains Parra.
5 – Leading the Transformation
The message for 2025 is clear: it is not enough to keep up with the changes – you will need to lead them. According to Parra, this requires more than technological tools:
"Innovation is as much a matter of culture as it is of technology. It will be necessary to train people, reevaluate processes, and align operations with business strategies. This will be the way to build a legal system that makes a difference", he concludes. Intelligenti, a Stefanini Group company, specializes in technological solutions for the legal sector, focusing on digital transformation. We develop tools that streamline processes, empower teams, and drive strategic results. Discover how our technology can revolutionize your legal department forever.
Face the future of your legal department with Intelligenti and transform the way you work. Take advantage of the full potential of technology to achieve even more efficient and strategic results. We're here to help drive your legal team's success.

Agile and problem-solving service as the key to customer loyalty on Black Friday

Over the past few years, Black Friday has conquered its space as one of the most anticipated events for retail, marking the beginning of the holiday shopping season with sweeping offers. For companies, however, the date also figures as a significant logistical and operational challenge, thanks to the expected strong increase in sales. Therefore, it is essential to prepare for Black Friday and offer a problem-solving and efficient service without suffering from this sudden variation in "temperature" in business.
All of this can be summed up in one goal: quick responses, that is, without generating pending issues or waiting for customers, accumulating unresolved requests after this period. For many consumers, the shopping experience during Black Friday can be marked by delivery delays and difficulties in customer service, which can impact the brand's reputation, which in turn can take months or years to be rescued, generating discontent and complaints both public and dealing with consumer protection agencies.
Companies that manage to avoid backlog and offer agile, high-quality service gain the trust and loyalty of their customers. Therefore, in addition to analyzing sales in previous years, forecasting inventories, and monitoring all stages of the operation, among other planning activities, including customer service in the Black Friday strategy is crucial to ensure business continuity and uniformity, with a properly trained and up-to-date team on promotions, products, and consumer codes. Among the points that should be analyzed are:
1. Reinforcement and training of the service team
2. Automating answers to frequently asked questions
3. Extension of service hours during and after Black Friday
4. Design of special processes for handling critical issues
5. Contingency plan in case of technical problems Necxt, a Stefanini Group company, makes all its CX experience available to the market so that companies can face this period with the solidity and knowledge of a strong and determined partner, offering flexible customer services that can be hired in the size and for the time that the demand requires. More than solving problems, our specialized services add value to organizations acting on several fronts, such as assistance in the billing process, delivery, exchanges and returns, technical assistance, warranty, support for use, among others.
The ideal scenario is for companies to be ready at least a week in advance, which includes staff training, ensuring that the systems are working and making sure that the infrastructure is prepared to handle the significant increase in sales volume and customer service demand. Black Friday is an opportunity for companies to increase their sales and win new customers. However, dealing with after-sales is even more important because it is the decisive moment for loyalty. So, prepare in advance, be agile, and be ready to offer the best service to your customers during Black Friday with Necxt.

What is BPO? How can we use BPO in the financial sector?

The current corporate scenario is characterized by the increase in the level of business competition, the intense pressure for cost reduction and quality increase, as well as the need for permanent innovation. This has stimulated organizations to seek new ways to generate competitive advantages.
Companies have realized that the reduction in the final price to the consumer is directly related to more agile and efficient processes, which cannot always be achieved with absolute centralization of activities. And this is where BPO comes in the financial sector.
But, first of all, do you know what BPO is?
Business Process Outsourcing refers to the strategic use of external resources for the company's intellectual areas (such as finance, accounting, and marketing). This is something very different from simple outsourcing — which is the transfer of administrative services, such as security and cleaning.
The financial sector is, in fact, among those that benefit the most from external specialized execution, given that a large part of the cases of business mortality in Brazil is due to poor financial and accounting management.
In this post, we will understand how the cost of BPO can actually become a company's most profitable investment.
What are the problems with a lack of specialization in strategic financial planning and management?
One of the capital mistakes of the Brazilian businessman is to cut costs where he should invest, and invest where he should cut. At the first sign of crisis, many organizations deliberately suppress technology expenses, for example. But, in fact, it is in this type of situation that technological resources (such as automation) collaborate the most to reduce corporate costs. The same applies to finances.
Let's be frank: how many Brazilian managers have expertise in strategic management and economics? According to a survey carried out in 2016 by Endeavor (in partnership with Sebrae), it was found that only 28.4% of Brazilian university students attended any discipline directly related to entrepreneurship.
What does this have to do with BPO in the financial sector? Everything. There are not a few entrepreneurs who put a business to work without a minimum of planning, nor professional financial structuring.
Who corroborates this is a survey by Mission Facilitators that, when analyzing 26 startups that went bankrupt, concluded that 67% had no strategic planning, and 86% of executives spent less than 1 hour/month with this type of planning. This culture of improvisation and intuition, when it moves to the financial sector, never brings good results.
An entrepreneur, especially at the beginning, needs to be fully focused on his core business — which, in itself, is already very difficult. In a small organization, when you move a partner to take care of finances, you are giving up a good part of the strength of the business, weakening the point that most needs to be calibrated.
In addition, financial management is the art of allocating scarce resources, which involves experience, a lot of technical knowledge, and a vision of the future.
To have all this in a degree of excellence, either you hire a top-of-the-line professional (who can greatly burden your labor costs), or you do it yourself and give up your own business. The two alternatives don't seem very smart.
What can BPO in the financial sector make a difference in a company?
BPO is the opportunity to delegate important tasks (specialized but bureaucratic) to partners with expertise in the area, in order to improve processes and make the company more agile and accurate in its decisions.
The cost of hiring a company specializing in financial management cannot be disregarded, but its benefits in the medium and long term usually pay for the investment.
This refers to the need to think strategically about what is worth cutting or where it is necessary to invest in order to reduce costs in a company.
BPO in the financial sector means transferring some activities to the most qualified professionals in the market. For example:
· cash flow management;
· preparation of the P&L;
· bank reconciliation;
· accounts payable/receivable;
· revenue projection.
And all this for an average cost lower than what would be had when trying to hire and innovate directly in the organization.
Those who use a BPO place the greatest financial experts in the market within the company. And this without the need to spend time and money on hiring, without the risk of turnover and without worrying about people management.
This also means freeing up staff to focus on the nerve center of your business (selling your software, improving your carrier's services, etc.). This availability of labor, combined with the greater efficiency of the financial sector, usually results in cost reduction and improvement of competitive strength in the market.
What are the advantages of financial BPO?
As you have already noticed, the advantages of BPO in the financial sector, in practice, are diverse. Let's get out of theory and go to the corporate day-to-day?
Cash flow management
Imagine a clothing store that operates in physical and electronic retail (clothing and trade in the women's fashion sector). The store buys its raw material from 3 suppliers, always with a commitment to payment in installments (6 installments).
The factory takes 30 days to produce the pieces, and the average sales time, after display in the window, involves another 30 days. The problem is that, after 2 months, those who buy the units pay in installments (in an average of 5 installments, for example).
Notice that there is a profound mismatch in this "cost – revenue" flow. But we are talking about only one type of product. Consider that this store works with 10 different products in addition to clothes (belts, shoes, bags): how to organize this confusing cash flow?
Without BPO, improvisation is what usually takes its turn in managing this schedule. Financial BPO is synonymous with excellent cash flow management (global and activity-based), which supports more correct strategic decisions, avoiding miscalculations that can compromise the health of the organization.
Bank reconciliation
According to a survey by SPC Brasil, 79% of Brazilians make purchases in installments. Clothing (32%), electronics (28%) and smartphones (25%) top the list of products with this payment model.
In e-commerce, purchases in installments on credit cards are even more popular. Imagine an online store that sells 150 units per month, with 100 items paid in installments on the card.
Who has time to check all the card machine files in order to find out if the receivables are falling into their account correctly? How to verify that the rates agreed upon by the payment intermediaries are in fact being met?
The mathematician William Deming wisely said that "what is not measured, is not controlled". BPO in the financial sector represents the close confrontation between sales and receivables. Everything is controlled: auditing of fees and floats, provision for receiving installments, management of chargebacks, etc.
Document control and processing
Electronic invoices, DREs, trade bills, promissory notes, payment receipts, service contracts. There are hundreds of financial and accounting documents in the corporate environment. And the loss of a single file is enough for the organization to be at the mercy of immense losses (from fines by the Federal Revenue Service to irreversible default).
Financial documents are a source of valuable information for important decisions, as well as legal certainty to support the organization's actions. The problem is that controlling all this data flow is complicated when you don't have full energy concentration in this sector.
BPO is a way to give due attention to this document management, without compromising your core business. Find out in this link how BPO can impact not only the financial sector of your company, but also the area of People Management, Legal, Procurement, critical points for business success! Success and see you next time!
Banking BPO

Agentic AI: The autonomy of Artificial Intelligence in focus

In recent years, artificial intelligence has evolved impressively. Initially restricted to simple predictive algorithms, it now encompasses highly sophisticated systems capable of learning, reasoning, and making decisions autonomously. In this context, Agentic AI engines emerge as a key player in the automation of complex tasks.
To illustrate the importance of this technology, according to Gartner, by 2028, about 15% of daily decisions, whether they are made directly or assisted by assistants, will be guided by autonomous agents.
This growth marks a paradigm shift in the way we interact with technology and optimize business and personal processes. To better understand this scenario, read on.
What is Agentic AI?
Agentic AI refers to artificial intelligence engines with the ability to not only process information but also plan and execute tasks with a high degree of autonomy.
In other words, these agents use machine learning, natural language processing, and generative models to analyze scenarios, set goals, and act independently to achieve them.
In contrast to traditional rules-based AI systems or supervised learning, Agentic AI engines possess the ability to dynamically adapt to new information and change their action strategies as needed.
Consequently, this makes them ideal for applications where variability and real-time decision-making are essential.
Difference Between Agentic AI and AI Agents
While the terms Agentic AI and AI Agents are often used interchangeably, they represent distinct concepts:
Agentic AI: Focuses on autonomy, with the ability to make decisions, learn, and adapt without human intervention. It's like a virtual assistant that thinks and acts on its own.
AI Agents: These are systems designed for specific tasks, such as chatbots or personal assistants. They follow predefined commands and do not have the same autonomy or capacity for continuous learning.
While AI Agents are excellent for automating repetitive and simple tasks, Agentic AI goes the extra mile by solving complex problems and making strategic decisions.
How Does an Agentic AI Engine Work?
The structure of an Agentic AI engine is based on four fundamental pillars:
· Perception: The agent collects and processes data from the environment, using sensors, APIs, or databases to obtain up-to-date and contextual information.
· Reasoning: Based on the data collected, the agent processes and interprets the information to understand the current scenario.
· Action: After analyzing the data, the agent decides what to do and takes the necessary actions to achieve their goals.
· Learning: The agent learns from the results of their actions, refining their strategies and improving their performance over time.
These four pillars operate in a continuous and interactive way, allowing the agent to become increasingly efficient and adaptable.
Practical Applications of Agentic AI
Agentic AI engines are already being used in various industries with the aim of increasing efficiency and reducing the need for human supervision. To illustrate the versatility of this technology, some of the key applications include:
Business Process Automation
Companies are using autonomous agents to optimize workflows, from customer service to inventory management and logistics. For example, these systems can predict demands, allocate resources, and even negotiate contracts with suppliers without human intervention.
Health and Medical Diagnosis
In healthcare, AI agents are employed to analyze medical tests, suggest diagnoses, and recommend personalized treatments. In addition, they can continuously monitor patients with chronic diseases and alert doctors to potential complications before they occur.
Finance and Investments
Independent agents are revolutionizing the financial industry by conducting trading operations, assessing credit risks, and offering personalized advice to clients. In this sense, these systems are able to analyze large volumes of data and make instant decisions based on market trends.
Intelligent Personal Assistants
Agentic AI-based virtual assistants are becoming increasingly sophisticated. In the near future, they will not only respond to simple commands, but they will be able to schedule appointments, plan travel itineraries, and even manage users' personal finances with full autonomy.
Cybersecurity and Threat Detection
Finally, with the increasing sophistication of cyber threats, AI agents are essential for detecting suspicious activity, identifying vulnerabilities, and automatically responding to attacks in real-time, ensuring greater protection for businesses and users.
Autonomous Vehicles
One of the most iconic examples of Agentic AI is self-driving cars, such as Tesla's. These vehicles perceive their surroundings, make driving decisions, and learn from each trip, continuously improving their efficiency and safety.
Supply Chain Management
Companies like Amazon use Agentic AI to manage inventory, predict demand, and optimize delivery routes in real-time, ensuring more agile and efficient operations.
Benefits and Challenges of Agentic AI
· Efficiency and Productivity: Automating repetitive tasks frees up time for humans to focus on strategic and creative activities.
· Fast and Accurate Decision Making: The ability to process large amounts of data and act instantly reduces errors and improves the effectiveness of decisions.
· Continuous Adaptation: Agentic AI engines learn from experience, becoming more efficient over time.
Challenges
· Ethics and Transparency: The autonomy of agents raises questions about accountability and transparency in decisions made by AI.
· Security and Control: How to ensure that AI agents do not make harmful decisions or be exploited by hackers?
· Market Acceptance: Large-scale adoption depends on user trust and government regulation on the use of these technologies.
The Future of Agentic AI Engines
Companies that adopt Agentic AI engines early will undoubtedly have a significant competitive advantage by automating processes, reducing costs, and boosting user experience.
However, responsible and ethical implementation of these solutions will be crucial to ensure that the benefits are widely enjoyed without compromising users' security and privacy.
As we move into this new era of AI, the question is no longer whether autonomous agents will become a part of our daily lives, but rather how we can ensure that they act ethically, safely, and efficiently to benefit society as a whole.
Ready to lead the transformation with Agentic AI? Scala offers innovative, customized solutions to accelerate your digital journey. Find out how we can boost your bottom line and position your business at the forefront of artificial intelligence.
Schedule a free consultation right now and get ready for the future! Agentic AI Data Artificial Intelligence

What is Responsible AI?

Responsible AI is not another type of artificial intelligence, like generative AI. Rather, it is an approach to developing and implementing artificial intelligence systems in a way that is ethical, fair, and beneficial to society. This approach considers the broader societal impact of AI and seeks to mitigate potential risks and negative consequences.
There are six principles that guide the responsible development of AI. By following these principles, developers and organizations can ensure that artificial intelligence is a positive force in society.
What are the six principles of Responsible AI?
The six principles of Responsible AI are:
· Fairness: AI systems must treat all people fairly and avoid discrimination based on factors such as race, gender, or age.
· Transparency: The decision-making processes of AI systems must be understandable and explainable to humans.
· Accountability: There should be a clear chain of responsibility for the actions of AI systems, including who is responsible for any negative consequences.
· Privacy: AI systems must respect people's privacy and protect their personal data.
· Security: AI systems must be secure and resistant to attacks that could compromise their integrity or lead to the misuse of their capabilities.
· Benefit to society: AI should be developed and used in a way that benefits society and improves people's lives.
Responsible AI development vs. responsible use
The concepts of responsible development and responsible use of AI are intertwined, but they focus on different aspects to ensure that AI is beneficial and ethical.
· Responsible use ensures that AI is applied in an ethical and beneficial manner.
· Responsible development ensures that AI is created ethically and responsibly.
This article deals with the responsible development of artificial intelligence. The focus is on the process of creating AI systems that follow ethical principles, ensuring transparency, accountability, and addressing potential biases in algorithms and data.
Some practices for responsible AI development include using unbiased data, making AI models interpretable, and establishing clear governance structures.
The responsible use of AI, on the other hand, looks at how AI is applied in the real world. This involves ensuring that AI systems are not used for discriminatory purposes, that users' privacy is protected, and that job replacement risks are mitigated.
For AI to be truly beneficial, both responsible development and responsible use are required. A well-developed AI system can still be misused if it is not applied ethically, and an ethically developed system can have unintended consequences if not used responsibly.
Why is Responsible AI important?
Without responsible AI development, there is a high potential for negative consequences. Uncontrolled AI can perpetuate biases, leading to discriminatory outcomes in areas such as hiring, lending, and criminal justice. A lack of transparency in AI decisions can undermine trust in institutions and weaken democratic processes.
The misuse of AI for malicious purposes, such as the creation of deepfakes or autonomous weapons, can have serious implications for society. Deepfakes can compromise trust in information and fuel disinformation campaigns, influencing elections or causing social instability. Autonomous weapons raise ethical concerns about the use of lethal force without human intervention.
Additionally, the advancement of AI can cause mass unemployment and increase economic inequality if not managed carefully.
By prioritizing fairness, transparency, and accountability, we can mitigate bias and discrimination in AI systems. Responsible AI helps protect the privacy and security of people's data, ensuring that technologies are used ethically and responsibly. It is essential for building trust in AI and ensuring that it is used for the good of society.
Responsible AI Practices
Responsible AI practices are a set of guidelines and principles that ensure the ethical and beneficial development and implementation of AI systems. They aim to mitigate risks and biases, promoting transparency, accountability, and fairness.
Here are some fundamental practices of Responsible AI:
1. Fairness and Bias Mitigation
Data quality: Ensure that the data used to train AI models is representative and free of bias.
Bias detection: Utilizing techniques to identify and correct biases in AI systems.
Fairness metrics: Applying metrics to measure and enhance the fairness of AI outcomes.
2. Transparency and Explainability
Interpretability of models: Making AI models more understandable to humans, promoting trust and accountability.
Explainable AI techniques: Utilizing methods such as variable importance, decision trees, and rule-based systems to make AI decisions more transparent.
Documentation: Maintain clear records about AI models, their training data, and decision-making processes.
3. Accountability and Governance
Accountability structure: Clearly define who is responsible for the actions and results of AI systems.
Ethical oversight: Implementing ethics committees or councils to keep track of the development and use of AI.
Audits and monitoring: Conduct regular audits to identify and fix potential issues in AI systems.
4. Privacy and Data Protection
Data privacy: Comply with privacy regulations such as GDPR and CCPA.
Data minimization: Collecting and storing only the data necessary for the purposes of AI.
Data security: Implement robust security measures to prevent unauthorized access or data leaks.
5. Safety and Robustness
Adversarial attacks: Test AI systems against attacks that may compromise their functionality.
Robustness metrics: Use metrics to assess the resilience of AI models.
Continuous monitoring: Follow up on AI systems for anomalies or unexpected behaviors.
6. Human-Centered Design
User-oriented design: Involving users in the AI development process to meet their needs and preferences.
Augmented intelligence: Designing AI systems that complement human capabilities rather than replace them.
Ethical considerations: Assess the ethical implications of AI applications and their impact on society.
What can Responsible AI mitigate?
Responsible AI can mitigate several risks and negative consequences associated with AI technologies. Key areas of impact include:
Biases and discrimination: Prevent AI systems from perpetuating social inequalities.
Privacy breaches: Protect users' personal data with security and privacy measures.
Unemployment: Creating opportunities and jobs instead of just replacing workers.
Autonomous weapons: Ensuring that the use of AI in weaponry is ethical and controlled.
Disinformation: Utilizing AI to detect and combat the spread of fake news.
Algorithmic accountability: Establish AI frameworks that ensure transparency and accountability.
Responsible AI and the future of technology
Responsible AI considers the broader societal impact of artificial intelligence and seeks to reduce risks and negative consequences. Without appropriate guidelines and ethical safeguards, AI technologies can generate unpredictable side effects.
Stefanini has been a pioneer in AI development by co-creating solutions with customers for over 13 years. From steel giants to multinationals in the automotive sector, many leading companies have found Stefanini the ideal partner for the application of artificial intelligence.