Agentic Workflow: How to unite AI, data, and processes

In recent decades, digital transformation in companies has followed a clear pattern: for every operational bottleneck, a new specialized software was acquired. The result of this race for technology was the creation of extremely fragmented corporate ecosystems, in which marketing, sales, finance, and logistics operate in isolated silos.

With the recent rise of Generative Artificial Intelligence (GenAI), a new challenge has emerged in executive boardrooms. While leadership demands the immediate implementation of AI to reduce costs and accelerate deliveries, IT and operations teams find themselves trapped in the daily routine of "putting out fires.".

The great corporate truth of the modern era is straightforward: Artificial Intelligence does not work without structured processes and centralized data. To move beyond the superficial layer of technological "hype," organizations need to evolve from using isolated tools to building intelligent workflows, the so-called Agentic Workflows.

The real bottleneck for businesses: the island of fragmented systems and data

It's common to find companies using up to 15 different platforms to manage their operations. While each software fulfills a specific role, the lack of a seamless connection between them leads to serious distortions in decision-making.

In a recent episode of the Trend Off, hosted by Felipe Wasserman, Marketing Director at Skyone, this reality was brought to light during an in-depth discussion about the impact of AI on the business ecosystem. Lucas Andrade, CEO of MIA and professor at ESPM, specializing in process optimization and AI implementation, participated in the conversation.

Lucas highlighted how a lack of integration creates chronic metric discrepancies within organizations:

When each department analyzes the business using an isolated metric (cash flow, accrual basis, gross revenue), leadership loses true visibility into the income statement. Without a "single source of truth,"anyattempt to implement AI results in inaccurate answers, misleading information, and a loss of governance.

The end of the manual process: the impact of autonomous agents in practice

Historically, business automation relied on rigid Python scripts, Excel macros, or inflexible conditional flows (“if X happens, do Y”). Today, pure conversational AI and LLM (Large Language Model)-based architecture enable the creation of autonomous agents capable of interpreting complex commands, making contextualized decisions, and executing end-to-end tasks.

During the podcast, Lucas Andrade illustrated this evolutionary leap by citing the restructuring case that MIA carried out in a large labor law firm.

Success story: operational restructuring in a law firm

• The traditional scenario: receiving leads required senior lawyers to manually screen them, calculate the potential of each case, negotiate fees, collect contract signatures, and gather documents. The process took weeks and consumed the technical time of highly qualified professionals.
• The AI ​​solution: a pure conversational AI was implemented via WhatsApp and audio. The automated agent now operates from start to finish: it asks qualifying questions, analyzes the potential of the case, negotiates fees based on predefined premises, sends the contract to the signing platform, and follows up with the lead until completion.
• The result: the initial processing time dropped from 3 months to 5 days. The human lawyer now only works at the final stage of the workflow, the strategic drafting of the petition, scaling the firm's service capacity without sacrificing quality.

Another striking example of previously unfeasible automation is the processing of medical certificates. Companies that receive thousands of certificates per month often lack the human capacity to analyze the veracity of the documents. With AI agents connected to external data, the system can validate the doctor's CRM in real time, cross-reference data, and identify fraudulent edits, generating immediate savings and avoiding labor liabilities.

Integrated structure: how Skyone Studio enables Agentic Workflow

For AI agents to operate autonomously and securely within the corporate environment, the technological infrastructure needs to support four fundamental pillars: integration, centralization, orchestration, and governance. It is precisely this unified ecosystem that comprises Skyone Studio.

With a comprehensive approach that combines iPaaS, Lakehouse, AI Agents, and Conversational BI, Skyone Studio enables you to transform scattered data into real strategic value.

Main layers of Skyone Studio:

• Unified Integration (iPaaS): Connects over 400 market systems (such as SAP, TOTVS, Salesforce, HubSpot, and ZOHO CRM) without the need for slow or costly manual development.
• Data management (Lakehouse): organizes structured and unstructured data into a single source of truth, enabling real-time analysis, enrichment, and continuous governance.
• Agent Orchestration (Agentic Workflow): enables the building and training of virtual agents capable of planning actions, querying corporate databases, and autonomously executing operational tasks.
• Multichannel publishing: makes AI insights and interfaces available on the channels where teams already work, such as WhatsApp, Google Chat, Microsoft Teams, and BI dashboards (Power BI and Metabase).

As highlighted in the official Skyone Studio document: “The ability to reason lies in the uniqueness of your data, allowing models to take autonomous actions and complete complex tasks in workflows.

The profile of the professional of the future: logical reasoning and the ability to question

Given the rapid advancement of AI, a common concern arises in organizations: will automation replace the human workforce?

Historically, every technological revolution eliminates repetitive tasks and opens up space for the creation of new, more complex demands. As AI takes over the operational base of the organizational pyramid, the value of the human professional shifts from manual execution to critical thinking.

During the Trend Off debate , Lucas Andrade highlighted the two essential skills that will define the success of professionals in the age of Artificial Intelligence:

1. Logical reasoning: understanding the structure behind data and processes. Knowing how to think in terms of information architecture and organization is vital for instructing and managing automation tools.
2. The ability to ask good questions: in an era where answers have been democratized by AI, the competitive edge lies in how you formulate the problems.

Strategic comparison: traditional approach vs. unified platform

To clearly visualize the efficiency gains from adopting an integrated solution like Skyone Studio compared to the traditional IT model, analyze the chart below:

The next step: break free from inertia and execute the transformation

The biggest risk for companies today is not testing a technology and failing, but remaining stagnant due to over-planning. The current market forgives manageable errors, but does not tolerate hesitation.

Data consolidation and process automation no longer require multi-million dollar investments or years of development from scratch. With the support of robust platforms like Skyone Studio and strategic direction focused on solving real business pain points, your company can move beyond the superficial layer of AI and lead the digital transformation in your industry.

Want to delve even deeper into this enriching discussion about AI, data, and the future of business? Listen to the full episode of the Trend Off on Spotify and check out the entire conversation between Felipe Wasserman and Lucas Andrade!

Written by Skyone