AI-powered process automation: how SMEs can achieve the same gains as large enterprises
AI-powered process automation is no longer exclusive to large corporations. For years, this perception limited the digital agenda of Brazilian SMEs. However, the latest data shows that this barrier has now been decisively overcome.
An IDC study, commissioned by Microsoft Brazil, surveyed 73 C-level executives from companies with more than 1,000 employees.
The results show average gains of 24.5% among organisations that have adopted AI. The strongest improvements were seen in process efficiency (27.7%), customer satisfaction (28.2%) and risk reduction (26.9%).
What has changed is not simply the cost of the technology. The way companies access it has changed too.
With Business Central, Power Automate and Copilot, SMEs now have access to capabilities that were once restricted to large enterprises. The question has therefore changed. It is no longer whether an SME can use AI, but when it will get started.
51% of Brazilian companies intend to scale AI over the next two years. Those that move first can build an advantage that is difficult to reverse.
— According to the IDC study
What AI-powered process automation means in practice
Before looking at specific use cases, it is worth distinguishing between two concepts that are often confused: process automation and artificial intelligence. Confusing the two creates unrealistic expectations and can ultimately lead to poorly targeted implementations.
Process automation means carrying out repetitive tasks without human intervention. A report generated every day at 8 a.m. An approval automatically routed to the right person. A notification triggered when stock reaches a certain level. This is what Power Automate makes possible in an accessible way.
Artificial intelligence, on the other hand, interprets context and identifies patterns across large volumes of data. It can also learn from a company’s historical data to support decisions in situations where there are no fixed rules.
When these two layers are combined, the result is something tangible: what the IDC research describes as “AI initiatives with a tangible impact on the business”. This is the stage that well-supported SMEs can already reach using the Microsoft ecosystem.
Why large enterprises got ahead with intelligent automation
Large-scale adoption among major organisations has not been driven by budget alone. It has also been enabled by well-established data infrastructure and specialist technical teams. Historically, SMEs have not had access to the same conditions.
The turning point came with a change in the delivery model. The move to the cloud reduced the initial cost of adoption. In addition, integrated platforms such as Microsoft 365 and Dynamics 365 Business Central have reduced the need for multiple integrations.
Finally, low-code and no-code interfaces have reduced reliance on developers. As a result, a company with 80 employees can now implement financial automation in weeks rather than years.
The barrier to entry has fallen. The real challenge is execution: knowing where to start and how to implement automation effectively. That is what separates SMEs that achieve meaningful results from those that remain stuck in experimentation.
AI-powered process automation: 5 practical applications for SMEs
Below are five areas where SMEs can achieve measurable results with automation and AI. Each example covers the problem, the technical approach and the expected outcome.
1. Financial reconciliation and AI-assisted month-end closing
Month-end closing in mid-sized companies is often still entirely manual. Data is exported from different sources, consolidated in spreadsheets and checked line by line. This cycle can consume between three and seven working days of the finance team’s time.
With Business Central integrated with Power Automate, automated workflows can consolidate entries, identify discrepancies and generate alerts for the CFO. AI can also classify accounting entries and detect anomalies, such as duplicates or unusual payments.
Typical result: month-end closing reduced from five–seven days to one–two days, while eliminating rework and improving confidence in financial figures.
2. Approval management and procurement workflow automation
Unstructured approval processes are one of the biggest sources of bottlenecks for SMEs. A request depends on an email, the manager is in a meeting, and the response arrives two days later. Multiply that by dozens of requests each week and the impact becomes measurable.
With Power Automate, a request can be created in the system and automatically routed to the appropriate approver. Notifications are sent via Teams or email, and the transaction is automatically recorded in the ERP.
AI can also add intelligent prioritisation based on urgency and business criticality. It can recommend the most suitable supplier using previous performance and pricing data.
Typical result: a 60–80% reduction in approval time, with full traceability and no more lost or overlooked approvals.
3. Automated management reporting
Managers in SMEs often make decisions using outdated data. Not because the information does not exist, but because consolidating it takes time. Sales reports, margin analyses and expenditure comparisons can all arrive too late to support timely decisions.
The integration of Business Central, Power BI and Copilot addresses this problem. Dashboards connected directly to the ERP can be updated in real time.
Managers can then ask Copilot questions in natural language, such as: “What was the average margin on industrial sales last quarter?” The answer is available without relying on an analyst to manually compile the information.
Typical result: four–six hours of manual reporting work eliminated each week, with decisions based on up-to-date data.
4. Internal support and request triage
Internal support teams handle a high volume of repetitive requests: password resets, access requests and questions about internal processes. Combined, these tasks consume hours every day from professionals who could otherwise focus on more strategic activities.
Implementing AI agents through Copilot Studio makes it possible to create assistants that automatically resolve the most common requests while escalating only those cases that genuinely require human judgement.
According to the IDC research, 56% of organisations are already using AI agents either in production or in experimental environments. Adoption is particularly concentrated in customer service and internal operations.
Typical result: 40–60% of internal requests resolved automatically, reducing operational workload and improving response times.
5. Demand forecasting and intelligent inventory management
For SMEs in manufacturing and distribution, intuition-based inventory management can be a major source of waste. Excess stock of slow-moving items ties up working capital, while shortages of critical items can disrupt production.
With AI integrated into Business Central, predictive models can analyse historical sales, seasonality and supplier lead times. The system therefore does more than report current stock levels: it can recommend when to buy, how much to buy and which supplier to use.
Typical result: a 15–25% reduction in capital tied up in inventory, alongside fewer stockouts and a direct positive impact on financial health.
The human factor: AI reorganises work, it does not replace managers
One of the biggest barriers to AI adoption among SMEs is neither technical nor financial: it is cultural. The perception that automation means replacing people creates resistance. In many cases, that resistance comes from the very managers who need to lead the change.
Data from the IDC research puts this concern into perspective. 70% of companies are reviewing internal responsibilities as a result of AI-driven productivity gains. In addition, 63% have already created new roles dedicated to the technology. This is not simply about removing jobs. It is about redistributing work.
What disappears is repetitive work with low cognitive value. What emerges requires interpretation, judgement and human interaction. Automation therefore frees teams to focus on the work that genuinely matters.
For managers, this has an important practical implication. Implementation should be accompanied by an open and transparent conversation with the team about what will change. Without that context, teams can develop passive resistance that undermines results.
AI is not an IT project. It changes the way a company operates, and leadership needs to treat it accordingly.
How to implement AI-powered process automation successfully
Most automation projects do not fail because of technical issues. They fail because of choosing the wrong process to automate first. Automating a poorly designed process does not fix it. It simply makes the problem happen faster.
That is why the first step should be process mapping. This means identifying where manual workload is highest, where rework is most common and where visibility is lacking. This analysis then determines which processes should be prioritised for automation.
Some practical criteria for deciding where to start include:
- High volume, clear rules: repetitive processes with well-defined rules can deliver quick results and help build internal confidence.
- Available and reliable data: AI needs data. Processes with structured records tend to involve less implementation friction.
- A recognised pain point within the team: when a process creates visible frustration, people are more likely to support automation. The problem already has a clear name and owner.
- Measurable financial impact: prioritise automation initiatives where the return can be quantified financially. This makes the investment easier to justify.
Once the process has been mapped, implementation can be incremental. It may begin with basic workflows in Power Automate, progress to integration with Business Central and, as maturity increases, incorporate generative AI and agents through Copilot.
The time to act is now — and the data supports it
The IDC research shows that 52% of executives believe companies without AI will lose competitiveness. In addition, 28% of corporate budgets are already associated with AI initiatives, with this figure expected to reach 45% by 2028.
For SMEs, the window of opportunity is still open. Large enterprises have already begun scaling their initiatives. Well-positioned SMEs therefore have an opportunity to build a competitive advantage before AI adoption becomes widespread across their industries.
The good news is that the point of entry has never been more accessible. The Microsoft ecosystem allows businesses to start with a single process, measure the result and then expand. There is no need for a two-year transformation programme before seeing tangible results.
The distance between where your company is today and where it could be with automation and AI is not measured in years or investment alone. It is measured in decisions.
The journey can be simple with the right clarity
AI-powered process automation is no longer something for the future. The data shows that organisations already implementing these initiatives are achieving tangible gains. Efficiency, decision quality and service capabilities can all improve in measurable ways.
For SMEs, this does not require a complete reinvention of the business. It requires clarity about where the biggest bottlenecks are and a partner that understands the operational realities of the organisation. Nexer works precisely at this intersection, helping mid-sized businesses implement solutions that deliver meaningful results.
Want to understand which processes offer the greatest potential? Talk to a Nexer specialist. A diagnostic assessment is the first step — and it often reveals more opportunities than expected.