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DIGITISATION OF CONTENTAI in business process automation | Practical applications - Lukardi
- Workflow
Artificial intelligence is increasingly appearing in corporate strategies, board presentations and digital transformation plans. At the same time, many organizations are still asking themselves: How to realistically use AI in everyday business processes?
The greatest value AI brings today is not in experimental projects, but in automation of repetitive operations - Such as workflow, reporting and workflow management. In this article, we show concrete examples of AI application in companies, real business benefits, and how to move from theory to working solutions.
Why do companies struggle to implement AI in their business processes?
Despite appearances, the barrier is not a lack of technology. AI tools are widely available today. Rather, the problem is a lack of clearly defined processes and uncertainty, Where AI will actually bring the most operational value.
Companies often:
They start with the tool, not the business problem,
are trying to implement AI "everywhere at once."
do not combine AI with existing ERP, ECM or workflow systems.
Meanwhile, a successful AI implementation should start with processes that are time-consuming, repetitive and generate large amounts of data.
Where does AI provide the most value in process automation?
AI in workflow - automation that works right away
Document circulation is one area where AI is producing measurable results very quickly. Artificial intelligence can:
automatically recognize the content of documents (invoices, contracts, applications),
classify documents and assign them to appropriate processes,
Extract key data such as dates, amounts or contractors,
detect deficiencies, discrepancies or duplicates.
As a result, organizations reduce document handling time, reduce errors, and ease the burden on operational teams.
Automate workflow and business decisions with AI
AI not only processes data, but also supports decision-making in business processes.
When combined with workflow systems, it enables:
Recommending next steps in the process,
Prioritization of tasks and requests,
Analysis of exceptions and non-standard situations,
Intelligent support for acceptance and approval processes.
This approach works especially well in multi-step processes, where there are different decision paths and a large number of exceptions.
AI in reporting and data analysis
Traditional reporting often means manual preparation of statements, delayed data and inconsistent information.
AI is changing this model, making it possible:
Automatic generation of reports and summaries,
Trend analysis and anomaly detection,
Creating dashboards based on real-time data,
Asking questions in natural language and quickly accessing information.
For business, this means faster and better reasoned decisions, based on up-to-date data.
AI as support for operations and back-office teams
Increasingly, AI is acting as a digital assistant to support HR, finance, administration or IT teams.
Artificial intelligence can:
Answer repetitive questions from employees,
Support onboarding and access to knowledge,
Analyze requests and tickets,
ease the burden on teams in day-to-day operational work.
This is especially important in organizations that want to scale operations without proportionally increasing teams.
What are the business benefits of AI in process automation?
Companies implementing AI in business processes are most likely to observe:
saving time and reducing manual labor,
lower operating costs,
greater predictability and consistency of processes,
better quality of data and decisions,
The ability to scale without increasing resources.
AI does not replace workers - strengthens their competence, allowing you to focus on tasks with greater business value.
Where to start in implementing AI in process automation?
Implementing AI does not have to mean a large and expensive project.
A phased approach yields the best results:
Identification of processes with the greatest potential for automation.
Linking AI to existing ERP, ECM and workflow systems.
Using low-code/no-code platforms for rapid prototyping.
Gradual scaling of solutions based on real business needs.
At Lukardi, we combine AI with process automation, enterprise-class systems and low-code/no-code platforms, so that solutions are embedded in real business operations.
AI as real business support, not a fashion accessory
Artificial intelligence is becoming A practical tool to streamline daily business operations. The key to success is its smart, process-oriented use and integration with the existing IT environment.
If you want to check it out, Where AI can bring the most value to your organization, it makes sense to start by talking about processes - not algorithms.
📩 Contact us, to move from theory to working AI solutions.
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- Workflow
Joanna Komsa
Digital Transformation & Business Development |Marketing Manager at Lukardi.
She has been involved in online marketing, strategy building and communications for 15 years. She is passionate about new technologies, AI and neuropsychology. She supports organizations in digital transformation and generating new business opportunities, combining experience in dordzdz, sales and marketing.
The most common questions about AI
1. will AI replace employees in business processes?
No. AI automates repetitive tasks and supports data analysis, but decisions and responsibility remain with humans.
2. what processes are best to automate with AI?
The best candidates are processes that are large in scale, repetitive and have clearly defined rules, such as workflows, reporting and ticket handling.
3. Can AI be combined with existing ERP and ECM systems?
Yes. AI works most effectively as an extension of existing ERP, ECM and workflow systems, rather than as a separate tool.
4. where to start implementing AI in a company?
It is best to start by analyzing business processes and identifying areas where automation will bring the fastest return. Only then should you select AI tools tailored to your real needs.
5 Does AI implementation require a large investment?
Not always. Many AI projects can be implemented in stages, starting with a pilot or a single process. Using low-code/no-code platforms significantly reduces costs and implementation time.
6. What business benefits do companies see most quickly after implementing AI?
The most common are:
Reduction of process execution time,
limitation of manual labor,
fewer errors,
Better quality of data and reports,
Greater transparency in processes.
7.Is AI in process automation safe?
Yes, provided the solution is properly designed. AI can work within existing security, access control and regulatory compliance policies (e.g., RODO, NIS2).
8. will AI also work for medium and smaller companies?
Definitely yes. With off-the-shelf AI models and low-code/no-code platforms, smaller organizations too can automate processes without extensive IT teams.
9. How long does it take to implement AI in process automation?
Implementation time depends on the scale of the project. The first effects can often be seen after just a few weeks, especially in the case of workflow or reporting automation.
10. can AI "learn" the specifics of our organization?
Yes. AI models can be trained and customized to fit the data and processes of a specific organization, making them work more and more effectively and better support the business over time.
