As AI has become commonplace in many organizations, the number of tasks that can be automated has increased. It is no longer just simple macros or scripts. Instead, you often see “classic” automation being supplemented with AI-based capabilities within the framework of modern platforms, so that more steps in the process can be handled, even when there is variation in data and data.
IT automation is not a technology – it's a spectrum
A common mistake is to look for an automation tool that will solve everything. In reality, there are different types of tools for different problems:
- Some automate clicks and button presses in existing interfaces (RPA).
- Others build stable integrations via APIs and events.
- Some orchestrate flows with rules, attestation, and traceability.
- And now there are tools that use AI to interpret text, suggest actions, and manage variation.
However, some automation tools (Softadmin®) can combine solutions to your problems in a common platform. Think about which processes are important to improve in order to achieve your goals and think about which systems and departments the processes affect. Getting a business perspective is at least as important as getting an IT perspective.
The International Labour Organization highlights that AI often enhances jobs by automating certain tasks rather than taking over an entire role. In practice, the impact often occurs in many small moments in everyday life, and you therefore need tools that can handle different parts of the process, from integrations and workflow to AI support where appropriate.
Without predicting the future of employees, it is definitely possible to prove that automation is a path that many organizations are choosing to save time, increase control, and reduce costs or risks.
Common types of automation tools for businesses
This is a practical division that usually makes the choice easier. Think “what kind of problem should we solve”, not “what brand should we buy”.
- RPA : Software robots that mimic user steps in systems and automate repetitive, rule-driven tasks. Suitable when API is missing or when you need to quickly relieve manual labor.
- Workflow and Business Process Management : Tools that model a flow with steps, rules, roles, SLAs and attestations. Good when the process needs control and traceability, not just “doing the job”. Automation within BPM is often called Business Process Automation or process automation.
- iPaaS and integration : Platforms for connecting systems via APIs, message queues and events. The right choice when robustness, monitoring and data quality are more important than the fastest shortcut. The integrations that you want to get out of an "Integration Platform as a Service" can also be made available via a platform that is not a pure integration platform.
- Process mining and task mining : Are analysis and insight methods that help you find where work actually happens, where variation occurs, and where automation has an effect before you build.
- Low-code platform : When you want to build process-oriented applications and automation logic that is more than “a script”, but still faster than traditional development. Here Softadmin® is a Swedish proven example that definitely covers most of the “automation spectrum”.
- AI support in processes : Everything from classification and information extraction to suggestions for the next best action. Important to combine with governance, logging and quality assurance.
- Test and operation automation : CI/CD (Continuous Integration/Continuous Deployment is about how code is delivered), Infrastructure as Code (how the servers and systems your app needs to function are built and configured), scheduled jobs, policy-as-code. Often “invisible”, but can have a big impact in IT delivery.
How to match tools to needs and avoid buying the wrong ones
Deloitte describes Intelligent Process Automation as a combination of AI-related technologies and Robotic Process Automation, where techniques like machine learning and computer vision (when AI can interpret images and videos) can be used to automate more than just strictly rule-driven tasks. However, you don't necessarily need to use RPA as the automation technology when combining with AI.
RPA, at least historically, has been more about automating a specific manual task. Today, the challenges associated with automation are often about digitizing and automating the right processes in the right way, and the right adaptations for your business, your everyday life, and your IT environment.
Consider whether you have the capacity in your organization to build and manage a solution, the costs and risks associated with purchasing a system, or whether you need a customized solution.
When RPA is the right choice
RPA is best suited when:
- You have clear, repetitive steps.
- Systems lack APIs or are difficult to integrate.
- You can accept that the automation needs maintenance if the UI changes.
RPA is often a good start to cut overhead in administration, but rarely becomes a sustainable foundation for the entire process landscape when it needs to grow or when systems change. RPA is often used as a complement rather than a foundational architecture.
When integration is the right choice
Integration via API or event is suitable when:
- Data needs to be accurate, traceable and reusable.
- Multiple systems should share the same truth.
- You want to build a capability that lasts even when interfaces change.
If RPA “imitates a user,” then integration builds a more stable engine under the hood.
When workflow and BPM are needed
Choose workflow/BPM when you have:
- Many roles and handovers.
- Requirements for certification, logs and regulatory compliance.
- Need to measure lead times and bottlenecks.
This is often where you get real scale, as you standardize the way you work and reduce variation. Conceptually, this is usually referred to as BPA (process automation) or DPA (Digital Process Automation) in combination with BPM (management discipline).
When low-code or customized system support is right
If the process is strategic, varies a lot, or requires special logic and UX for internal users, a customized system support can be more effective than “patching” together a chain of point tools.
It is also a common situation that a standard system does not quite match how you actually work. Here you have the opportunity to also weave in integrations with the right platform.
Multisoft's focus is precisely to build customized system support that automates information management and administrative processes, based on the low-code platform Softadmin®, where requirements gathering and ongoing further development are a central part of the delivery.
How do you know you need more than a standard tool?
A good litmus test is to ask: “If we change tools, is the problem solved?” If the answer is no, it is often the process, system map and/or data model that is the real issue.
Signs that you need to think bigger:
- Several systems contain the same data but with different versions.
- The process requires many manual checks and exceptions.
- You need traceability and control that are not available in today's system.
- The work is done in Excel, emails and chats between “real systems”. You have a hole in the system map.
Then the next step is often to combine technologies such as process automation, AI support and integrations (SOAP, REST, GraphQL, Webhooks, XML, JSON, CSV, file transfer via FTP/SFTP, etc.)
Common pitfalls when implementing automation tools
Automation often provides quick results, but some patterns recur when it becomes expensive in the long run.
- You are automating a bad way of working.
If the process is unclear, the tool will only make the problems go faster. Start by simplifying. - “Shadow automation” without ownership
When employees or teams build their own automation flows without common standards, you incur technical debt, often without the IT department or organization knowing or approving the automations. - Overconfidence in AI without control
AI can be powerful in classification, text interpretation, and decision support, but you need traceability, quality metrics, and human control at the right steps. - You are measuring the wrong thing.
The number of automations says little. Instead, measure throughput time, error rate, rework, and actual time released.
The European Commission highlights in the State of the Digital Decade that Europe's digital transformation is linked to both technology and skills. The report tracks developments in areas such as the digitalisation of businesses and digital skills, and points out that there are gaps that need to be closed to reach the 2030 goals.
In practice, this means: Automation is as much about changed working methods and skills as it is about tools.
Speaking of technology and expertise: Multisoft has 94% in NKI and has been named Sweden's best workplace nine years in a row.
