Agentic automation for enterprises
We orchestrate AI agents and robots to empower people to accelerate business results
What is agentic automation?
Agentic automation is the next step beyond intelligent process automation and RPA, where AI agents make decisions instead of just following pre-defined rules. Agents operate based on goals set for them and take advantage of AI capabilities that enable them to reason and make auditable actions within given goals, interpret context, run automations and collaborate with employees. Instead of just extracting data, it determines what to do next – and often executes that step automatically. Agentic automation uses software agents empowered by large language models (LLMs), generative AI (GenAI) and large action models (LAMs) that go beyond task execution.
What are the key characteristics of Agentic automation?
Unlike personal AI agents that are used to boost individual productivity, agentic automation delivers enterprise-wide impact. It embeds built-in decision-making into processes, scales seamlessly across thousands of documents and transactions, and integrates with business critical systems like ERP, CRM and HR.
Enterprise-wide impact
Boosts productivity throughout organization
Integrates with ERP, CRM & HR systems
Scalable to business critical processes
Built-in decision making
Agents that don’t just follow rules, but make decisions
Key benefits
What does Agentic automation deliver for your business?
01
Expansion of automation landscape
Agentic automation expands automation into unstructured, dynamic processes that traditional RPA couldn’t handle
02
Increased efficiency and productivity
Automation of end-to-end processes improve accuracy and free people for higher-value tasks through the whole organization
03
Improved decision-making capabilities
AI agents analyze vast data in real time to deliver faster, more accurate, and actionable business insights
04
Employee satisfaction and empowerment
Agents remove repetitive work, boosting job satisfaction and allowing employees to focus on creativity and impact
05
Accelerated innovation and scalability
Agents adapt and scale, empowering employees to focus on innovation and growth
06
Continous performance improvement
AI agents learn continuously, enhancing process performance with every cycle
07
Actionable visibility into processes
Constant self-monitoring gives organizations real-time insight into automation performance, ROI, and opportunities
08
Better AI execution and deployment
Agentic automation ensures the right AI models to run efficiently, maximizing ROI from existing AI investments
What's the difference between RPA, AI-powered automation and agentic automation?
From rule-based task automation to autonomous AI agents – understand the key differences and find the right fit for your processes.
Traditional RPA
Traditional RPA automates rule-based, repetitive tasks by processing structured data with speed and consistency. It is the ideal starting point for routine processes.
- Data entry & retrieval
- ERP integrations
- Reporting
- Processing invoices or applications
- Test automation
AI-Driven Automation
AI-driven automation combines RPA with machine learning, NLP, and generative AI to handle unstructured data and more complex decisions. It enables systems to classify documents, summarize content, understand natural language, and make intelligent recommendations, going beyond rule-based automation.
- Chatbots
- Processing or analyzing documents, emails or customer feedback
Agentic Automation
Agentic automation uses autonomous AI agents that can make decisions, plan multi-step actions, and execute tasks without human supervision. Unlike traditional automation, it handles unpredictable, non-routinized processes – processing and analyzing unstructured data in real time to drive outcomes across the entire organization.
- Service processes
- Self-directed analysis and workflows
- More detailed use cases below
What are the best use cases for Agentic Automation?
Though still emerging, the technology already applies broadly across industries and functions. Below are current examples, but many more will follow as the technology matures.
Finance
AI agents streamline fraud, risk, and customer workflows, enhancing compliance and efficiency
Insurance
Agents accelerate handling claims, policy workflows and customer interactions, cutting manual work and improving CX
Manufacturing
Agents boost manufacturing efficiency through quality control, predictive maintenance and optimized supply chain management
Customer experience
Agentic automation provides 24/7 support, and delivers personalized, and proactive customer experiences at scale
Public sector
Agents help governments deliver faster public services by automating document handling, compliance auditing and more
Retail
Agents optimize inventory, pricing and CX: automated stock management, personalized recommendations, and streamlined order handling
Healthcare
AI agents streamline patient care and data management, accelerate diagnostics, and power faster, data-driven medical drug discovery
Employee experience
AI agents summarize employee feedback, streamline internal communication and email prioritized summaries of required actions to executives
Case stories in AI-driven automation
Which business processes can you automate with agents?
Below are some concrete examples of what kind of processes can be automated with AI agents.
Customer experience
- Processing customer feedback
- Making recommendations to customers or service specialists
- Quality review and reporting: AI audits customer service interactions
- AI-guided customer assistance
- Customer event analysis
Efficiency and productivity
- Test automation: automatically create test cases from requirement specifications
- AI-powered purchase invoice processing
- AI-powered sales invoice processing
- AI agent as a legal interpreter
Quality and digitalization
- Real-time reporting from multiple sources
- Bid comparison in procurement
- Cross-checking customer data across systems
- Contract quality review
- EU sanctions compliance
- AI-assisted risk management
Finance and procurement
- Procure-to-Pay
- Accounts Payable
- KYC
- Customer Due Diligence
Manufacturing & supply chain
- Product lifecycle management
- Production line monitoring
- Predictive maintenance
Insurance
- Claims processing
- Pre-authorization
- Multilingual claims validation
Retail
- Demand forecasting & stock management
- Dynamic pricing and promotion
- Returns and reverse logistics processing
- Supplier management
Public sector & compliance
- Document processing
- Services for citizens
- Regulatory compliance auditing
- Integrated government services
HR & workforce management
- Employee onboarding
- Recruitement screening
- Performance management
- Payroll
What challenges you need to consider before implementing AI agents?
Agents can transform how enterprises operate but realizing the potential requires overcoming key implementation challenges.
1. Safeguarding data privacy and security
As agentic automation operates across sensitive systems, strong data protection is essential. A secure automation framework, encryption, access control, and continuous monitoring are key to maintaining compliance and protecting confidential information.
2. Ensuring reliable decision-making
Reliable decision-making depends on rigorous testing, establishing confidence thresholds, validation and auditing decision outcomes, and human oversight to ensure every automated action aligns with enterprise standards and business goals.
3. Managing complexity with expertise
Implementing agents across business systems involves integrating AI, ML, and orchestration tools into existing infrastructure. Partnering with experienced automation experts helps simplify deployment, align with infrastructure, and achieve faster, scalable results.
4. Building ethical and transparent agents
Responsible automation requires transparency and ethical consideration. Designing explainable AI models and addressing potential bias in data and models, builds trust and ensures agentic automation operates ethically and accountably.
Demo video: Processing documents with Document Understanding and Agentic technologies
Watch our free demo on how UiPath’s Document Understanding and Agentic automation transform document handling, for example with purchase orders.
Our tech stack for creating agents
Sisua is a Platinum Partner
UiPath is the world’s leading automation platform and Sisua Digital has been awarded with UiPath’s Platinum Partner status globally. The status signifies top-tier expertise and success in implementing UiPath’s automation solutions and it is the highest level of UiPath partnership. In Chile, Sisua has been certified as UiPath’s USN Partner: there are just a few organizations globally which are certified USN Partners.
Book an AI workshop with us
Tell us if you have potential use cases in mind, or whether you’re interested in AI-powered automation or building agents, and we’ll get back to you soon.
What you will gain from this AI workshop:
- Understanding data: what problem is being solved, technology selection, and data sources and types
- AI capabilities and limitations
- Automation of tasks and processes using AI
- Identification of concrete use cases
- Collaborative classification of best use cases
“The AI workshop facilitated by Sisua’s experts helped us quickly surface new and previously considered ideas for leveraging AI, and prioritize them for further development.”
– Juhana Toivonen, Administrative manager, Maatalousyrittäjien eläkelaitos Mela
Why choose Sisua Digital as your agentic automation partner?
Continuous orchestration, support, and maintenance as a service
Sisua provides a fully managed automation platform combined with continuous service. This includes orchestration management, SLA management, monitoring, reporting, maintenance, and dedicated support. Technology alone doesn’t deliver results – Sisua delivers automation as a service.
Around the clock delivery keeps your automations running reliably 24/7
Sisua operates service centers on three continents, enabling 24/7 development, support, and maintenance. Our certified global team scales flexibly to customer needs, while we also advise on licensing and provide cost-effective managed service and Automation-as-a-Service models.
Enterprise-grade agents with governance and orchestration
Agentic automation requires robust governance, orchestration, and compliance controls – just like RPA, but at a higher level of complexity. We apply our deep automation architecture expertise to ensure agents are deployed, monitored, and scaled with enterprise-grade precision.
Secure integration of AI agents into enterprise systems
As a system integrator, Sisua connects AI agents directly to enterprise systems within a governed and secure framework. This ensures agents operate safely, comply with IT and business policies, and deliver measurable business value — without sacrificing agility.
AI agents embedded in tools your teams already use
We don’t introduce isolated tools. Instead, we build AI agents directly into platforms your teams already use, such as Microsoft Teams. This enables collaboration, automation, and decision-making without platform switching, reducing change resistance and driving adoption.
Identifying agentic opportunities, challenges, and business value
We help customers identify where agentic automation creates real value – and where challenges must be addressed. Our approach balances innovation with practicality, ensuring intelligent and responsible use of agentic technologies.
