What Is Intelligent Automation? Impacts on Modern Enterprises

Intelligent automation (IA) is a workflow optimization process that many organizations are implementing to more effectively streamline their operations. IA achieves this improved workflow by combining advanced technologies like artificial intelligence, machine learning, and robotic process automation into one unified offering. If you think your business can benefit from intelligent automation, you need to understand how it works, how it can be most effectively used in common processes and applications, and what the most useful tools to implement it are. Here’s what you need to know.

KEY TAKEAWAYS

Intelligent automation takes the strengths and capabilities of artificial intelligence, machine learning, and robotic process automation (RPA) and combines them to produce new business efficiencies and orchestrated workflows. (Jump to Section)

Intelligent automation can support a wide variety of industries and sectors, but it is most frequently used in highly regulated, complex, and high-tech environments that can benefit from this strategic technology at scale. (Jump to Section)

Several different training programs, certifications, and comprehensive platforms are emerging to meet growing demands for IA. Consider making the investment now to become an early adopter and thought leader in the space. (Jump to Section)

TABLE OF CONTENTS
ToggleHow Does Intelligent Automation Work?Key Components of Intelligent AutomationIntelligent Automation Use Cases by IndustryBest Practices for Using Intelligent AutomationChallenges in Implementing Intelligent AutomationHow to Select an Intelligent Automation Solution3 Key Tools for Intelligent Automation3 Intelligent Automation Courses to ConsiderFrequently Asked Questions (FAQs)Bottom Line: Intelligent Automation Improves Productivity

How Does Intelligent Automation Work?
Intelligent automation is an advanced automation process that merges artificial intelligence and machine learning with robotic process automation to automate business process workflows and create intelligent, robotic agents that can take over some of an organization’s routine, workflow-based tasks. Robotic process automation (RPA) bots alone can handle a number of automated business tasks. Unlike IA solutions, RPA bots don’t possess the additional human-like capabilities to go beyond routine training and take on new tasks that require cognitive and sensory capabilities.
When supported by RPA, artificial intelligence, and machine learning, intelligent automation bots have the algorithmic toolsets to comprehend and execute automated tasks at a deeper level. Some upper level IA bots are trained with deep learning, neural networks, and natural language processing so they can understand human language and generate unique content on a range of topics. The training data involved in IA is typically a large set of data from various sources and in diverse formats, both structured and unstructured. In essence, this sophisticated AI training gives RPA-powered machines the capacity for decision intelligence, or at least the context to make data-driven decisions that are largely independent from regular human intervention.
To give IA machines the ability to “see” or interact with their surroundings, many of these bots also receive training based on computer vision and optical character recognition (OCR). With this training in particular, intelligently automated machines can take on complex tasks in retail, manufacturing, and other settings that typically require a pair of eyes and sensory skills.
Key Components of Intelligent Automation
The underlying components of AI include workflow orchestration techniques, integration techniques, and real time data processing, all of which are interrelated with machine learning technologies.
Workflow Orchestration
Workflow orchestration effectively acts as the “project coordinator” in intelligent automation. Orchestration management tools within IA platforms are in charge of organizing and managing task and decision sequences within an automated process. This responsibility includes assigning tasks to either humans or robots, deciding on the best order of operations, and identifying and handling exceptions or errors in real time. When done well, workflow orchestration optimizes how your organization uses its resources and helps intelligent automations to be managed more efficiently, quickly, affordably, and with scalability.
Integration Technologies
Intelligent automation can only perform its role effectively if it’s integrated with business applications where data exists and daily operations happen. To achieve optimal levels of integration, most IA platforms directly integrate with common clouds and business applications through integration technologies like APIs and built-in integrations.
Alternatively, some IA vendors offer third-party marketplaces, consultants, and design studios to set up custom niche integrations as needed. The integration step of IA is incredibly important, as it enables end-to-end process automation without the errors inherent with manual data transfers.
Machine Learning and AI
ML and AI provide the complex cognitive capabilities necessary for IA systems to handle upper level assignments that include unstructured data or continuous learning and development. IA’s main sensory skills—including vision, language processing, and image recognition—come from the incorporation of AI technology. In essence, AI’s presence can take a chatbot or other type of RPA bot and enhance it with something resembling human comprehension and decision-making skills.
Real-Time Data Processing and Analytics
In addition to initial training datasets and data uploads, intelligent automation systems require real-time data capture and processing to keep up with system demands. These data tools work to capture, process, and then analyze data as it comes in, using both predictive and prescriptive analytics. From there, the IA system can make recommendations and take actions based on what the latest data says.
Intelligent Automation Use Cases by Industry
Intelligent automation can be incorporated into a range of business use cases and industries. With the right training and monitoring in place, many organizations are beginning to bring IA into their workflows.
Insurance
In complex and tedious insurance workflows like claims and risk management, IA bots can comb through large amounts of data quickly and automate tasks like claim intake and settlement. When these tasks are automated at scale, it can increase insurance company productivity and reduce the chance of risky or erroneous claims. Intelligent automation can also be used to improve fraud detection methodologies in insurance as well as in banking and other finance settings.
Healthcare
IA in healthcare can handle some of the back-office administrative tasks of a healthcare facility, following automated workflows while adhering to cybersecurity and compliance requirements for data processing. For healthcare administration, IA is often used to support the work of medical claims and bills processing. IA has also been used to manage large-scale tasks in public health, like COVID-19 vaccination distribution and tracking. More recently, it has also become part of the AI-driven drug discovery and pharmaceutical product development trend.
Business
Some organizations are using IA tools to create more sophisticated robotic call center agents to handle calls and chats without sounding so scripted. IA tools may also be used to more efficiently manage call logs, score leads, personalize marketing campaigns, and make recommendations based on buyer history or buyer sentiment. Certain key aspects of recruitment and HR can also be automated with IA agents, including onboarding and payroll processing tasks, candidate screening, and general document processing.
Manufacturing
IA-powered robots can take on human tasks—or even chains of tasks—on factory production floors and make adjustments to their performance based on real-time training and feedback. They can also use applied predictive analytics and computer vision/machine vision to manage quality, maintenance, inventory stocking, and order fulfillment schedules for both factory machines and manufactured products. These manufacturing-specific IA solutions do all this while also considering how changes will impact supply chain schedules and logistics.
IT and Cybersecurity
Intelligent automation is particularly effective for automating software testing and recommendations and actions for continuous integration and continuous deployment (CI/CD). It can also be used to manage cybersecurity efforts in DevSecOps scenarios. IA bots can handle the full cybersecurity management lifecycle, not only detecting vulnerabilities and issues on a massive scale but also using predictive analytics and smart recommendations to execute the necessary improvements and handle threat response activities.
Consumer Technology
While technologies like self-driving cars, smart checkout kiosks, and similar self-service technologies are still fairly new, they are becoming more capable with the help of IA. IA technology found in consumer tech is often the most adaptable and dynamic, frequently adjusting to match the sentiments and range of requirements that customers have. To truly understand what customers need, consumer tech’s intelligent automation solutions frequently include biometric identification, computer and machine vision, optical character recognition, and other features that help to identify and understand human preferences.
Adera’s smart kiosk uses intelligent automation to support a variety of customer service use cases.
Best Practices for Using Intelligent Automation
Intelligent automation is a complex and multifaceted automation strategy that requires full management buy-in, dedicated training, change management, thoughtful planning, and ongoing strategic pivots. Incorporating best practices into your intelligent automation initiatives can help you ensure its success.
Involve All Relevant Company Stakeholders
Data scientists, automation engineers, IT staff, and business leaders should be involved from the start in customizing IA to fit the organization. Gathering a multidisciplinary team will ensure the technology meets organization-wide demands and gets ongoing support and input from all departments and project teams.
Set Goals and Consider Important Use Cases
At an early stage, seek out employee feedback on tedious task work that could be automated or otherwise handed off; don’t simply ask managers, but be willing to talk to employees who are in the weeds of the organization’s most tedious tasks. Additionally, consider your budget and any tools or resources you may still need to get started, as well as any measurable goals or outcomes you hope to achieve with intelligent automation. All of the initial goals you set should be documented for future reference.
Invest in Flexible IA Tools You Can Integrate
The market is full of AI software and RPA tools, but not all of them effectively combine the strengths of both technology types to support intelligent automation. Research available options, paying particularly close attention to any advanced technologies and features that meet your needs. Also, take the time to evaluate how—or if—these platforms will integrate with your other business process management tools.
Automation Anywhere is an example of an intelligent automation and RPA platform that gives administrators accessible, hands-on control over bot automations.
Test and Monitor Automations at All Stages of Deployment
At all stages of IA implementation, test how automations are performing and if they are meeting their intended purpose. It’s especially important to quality-test automations that affect customer-facing interactions, such as intelligent customer service agents or autonomous devices. The QA specialists or automation engineers on your team are likely the best fits to test how automations are performing. Be aware that different types of automation testing and monitoring tools can supplement their work; this will likely require some research.
Follow AI Ethics and Ethical Best Practices
Because intelligent automation is so heavily entwined with artificial intelligence, it’s important to consider the AI-focused ethical implications of the data you’re using and where and how you apply artificial intelligence in your workflows. Ensure that all of your most sensitive data—particularly PHI and PII—is stored securely and separately from these technologies, and frequently audit your IA tools and results to ensure data is being used ethically.
If the tools you’re using aren’t transparent enough to give you this kind of visibility, consider switching up your toolset or strategy to create more visibility. Taking this step will help you to protect your consumers’ data as well as any other sensitive business data from unauthorized access and usage.
Read our guide to generative AI ethics for an in-depth look at the challenges and solutions involved with using AI in business.
Challenges in Implementing Intelligent Automation
Intelligent automation is a new and complex automation strategy that can be difficult to implement and maintain. Being aware of the challenges you’re likely to encounter—and their solutions—can prepare you for a successful IA implementation.
Change Management and Employee Adoption
Introducing new, complex types of automation can disrupt existing workflows and lead to frustration or resistance among employees. To overcome this hesitation among employees, business leaders need to effectively communicate, provide role- and task-specific training support, and clearly demonstrate how IA will benefit both employees and the organization.
Data Security and Privacy Concerns
Intelligent automation is only possible with massive amounts of training data and data inputs, some of which may be sensitive or personally identifiable. Especially when you are working with data that may compromise a customer’s privacy, it’s absolutely critical that you follow all data privacy regulations and establish security safeguards within your IA system to protect against breaches and unauthorized data access.
Cost and ROI Assessment
IA can be an expensive implementation process, and even more so if you aren’t clear on your priority projects and how much each component will cost initially and over the long term. It’s a good idea to complete an ROI assessment to determine where IA will be most impactful and cost-efficient for your business.
Automation Bias
Much like with other AI-based solutions, outcomes can be biased, unethical, or otherwise contain errors if the training data you use is biased or incomplete. From the start and on an ongoing basis, you’ll need to identify and mitigate biases both in your datasets and in the systems once they’re up and running. A QA analyst or team is a great way to stay on top of bias and performance issues.
How to Select an Intelligent Automation Solution
When your business has decided to invest in an intelligent automation solution, consider the following features and capabilities to make the best choice:

Process Discovery: The best IA solutions include built-in assistance and features to support process discovery, process mapping, data collection, and risk identification. Look for features like task mining, process mining, document analysis, and other tools that support in-depth research.
Robotic Process Automation (RPA): Robotic process automation capabilities are at the core of what makes IA bots actually operate, so you can’t invest in a tool for IA if it doesn’t include RPA. Look specifically for task automation, process orchestration, process modeling, error handling, system integration, and data transformation capabilities that work for structured and semi-structured data (AI will take care of the unstructured data).
Integrations: IA tools are most effective when they can directly integrate with your most-used data sources and business software solutions. Specifically, look for intelligent automation solutions that will integrate with ERPs, CRMs, and major databases in your tool stack.
Intelligent Document Processing (IDP): Much of the data that helps IA perform its programmed tasks is found in structured and semi-structured documents, so it’s important to select a tool with IDP capabilities. Look for computer/machine vision, document capture and classification, document handling for different document formats, data extraction, data validation, and data enrichment capabilities before making your choice.
Generative AI (GenAI): Generative AI is increasingly becoming a part of the IA tool stack because it helps IA bots generate believable and scalable content in real time. At a minimum, your selected tool should have basic AI/ML capabilities, natural language processing, and natural language understanding, but it’s also worth looking at tools that include or integrate with generative AI models and solutions.
Scale Supported by the Cloud: An IA tool that is compatible with or hosted on a major cloud platform offers more scalability, cost efficiencies, innovation opportunities, security and disaster recovery features, and general accessibility. If you’re not sure if the IA tool you’re evaluating includes cloud-driven scalability, look for keywords and features like elasticity, global reach or localization, scalable and tiered pricing structures, and integrations with popular cloud platforms and services.
Security, Privacy, and Compliance: IA tools can only run effectively and comply with regulations and customer privacy expectations if security, privacy, and compliance features are natively included. Look for admin and access controls, data encryption, data masking and anonymization, compliance certifications, security assessments, data retention policies, and other features that indicate your chosen tool’s commitment to comprehensive data protections.

3 Key Tools for Intelligent Automation
Among the large and growing group of solutions that serve the intelligent automation market, we recommend considering three leading solutions: Automation Success Platform, UiPath Business Automation Platform, and SS&C Blue Prism Enterprise.
Automation Success Platform

Automation Anywhere’s Automation Success Platform is a large IA platform that includes dedicated, integrated systems for automation and AI that are open, trusted, flexible, and capable of operating on-premises or in the cloud. Its automation system includes RPA bots, API tasks, a center of excellence (CoE) manager, and several relevant enterprise integrations. Its AI system includes an AI agent studio, document automation, process discovery, and several different generative AI models, process models, and specialized AI solutions. Many users also appreciate the built-in automation co-pilot that offers use-case-specific support in healthcare and life sciences, banking and finance, service ops and supply chain, IT, and HR.
Automation Anywhere’s entry level solution starts at $750 per month. This includes one control room, one unattended bot, and one bot creator. Additional bots cost $125 per month for attended, or $500 per month for unattended.

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UiPath Business Automation Platform

The UiPath Business Automation Platform is an IA and RPA solution that offers dedicated solutions for discovery, automation, and operations management. For discovery, the platform includes dedicated tools for process, task, and communications mining, as well as a dedicated automation hub for brainstorming and planning. Its automation solutions include a range of prebuilt apps, studios, robots, assistants, autopilots, and marketplaces to help users build the exact solutions they need. To reach and maintain enterprise-level standards, the platform also includes a dedicated test manager, orchestrator, AI center, insights, and automation ops.
UiPath’s Pro solution starts at $420 per month and includes robots to enable on-demand execution, advanced automation tools with user governance, and basic support.

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SS&C | Blue Prism Enterprise

SS&C | Blue Prism Enterprise is an enterprise-level automation solution that focuses on helping businesses build highly capable digital workforces. The platform is divided into three main sections: the Digital Workforce section, the Design Studio section, and the Control Room section. With Digital Workforce, users can set up RPA and autonomous software robots for their applications and specific use cases. In Design Studio, businesses can access user-friendly, no-code tools for process automation design and access the Digital Exchange (DX) marketplace for third-party integrations. Through the Control Room, business leaders can assign digital workers and scale their task requirements, set up SLA-based orchestration, and monitor results with centralized analytics.
Blue Prism does not publicly disclose its pricing; contact the vendor.

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3 Intelligent Automation Courses to Consider
As the intelligent automation sector expands rapidly, creating job openings for qualified individuals, those interested in a career in the field will need to seek out training to boost their skills. We’ve identified three online courses that provide a solid mix of skills and hands-on knowledge to help you get started or advance your career in IA.
Automation Anywhere Essentials RPA Certification
Automation Anywhere is one of the leading IA solutions providers in the market today, so it’s strategic to pursue one of their certifications. The Essentials RPA Certification is specifically designed for university students who want to pursue a career in this field and is one of the only options available for individuals who are new to a technology career. The certification includes a handful of prerequisites; from there, you’ll take a 60-minute online certification test and complete an automation development assessment to earn your certificate. More advanced certification paths are also available from Automation Anywhere.
There’s no cost for this Essentials program; more advanced Automation Anywhere certification costs $50-$80 per program.

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Certified Intelligent Automation Professional (CIAP) Program
The Certified Intelligent Automation Professional (CIAP) Program is a six-week certification opportunity that focuses on teaching procurement professionals and other backoffice leaders how to apply intelligent automation, best practices, and tools to their line of work. Each week of the program, students will have approximately two to five hours of coursework, discussions, and quizzes to complete. At the end of the program, a final essay is assigned to assess skills from across the program. This program is intended more for business leaders who need to understand IA from a strategic standpoint rather than for technical team members who need to grasp IA on a tactical basis.
This course costs $1,795.

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Intelligent Automation Foundations (LinkedIn)
Intelligent Automations Foundations is a LinkedIn Learning certification program that focuses on the basics behind intelligent automation, how it works, and how it can be applied through strategic methodologies and frameworks. Many past students have complimented the program’s focus on explaining how the sensory technology works within IA systems. The program consists of six chapter quizzes, with one at the end of each section. Upon completion of this program, students earn a LinkedIn Learning certificate of completion and are eligible to earn CPE credits from the National Association of State Boards of Accountancy (NASBA).
This course can be taken at no cost during a one-month free trial of LinkedIn Premium.

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Frequently Asked Questions (FAQs)
What Are Examples of Intelligent Automation?
Examples of intelligent automation include automated claims processing in both healthcare and insurance, automated onboarding workflows and recruitment screenings in human resources, automated predictive and prescriptive analytics across industries, and intelligent chatbots for customer service. New examples and use cases are launching regularly, typically to reduce manual labor and human error in routine or complex taskwork.
What Is the Difference between AI and Intelligent Automation?
Artificial intelligence (AI) is one component of what makes intelligent automation work. While AI primarily consists of algorithms, big-data training sets, and machine learning components, intelligent automation takes all of these strengths and combines them with robotic process automation (RPA) to achieve intelligent automation workflows at scale.
What Is the Role of Intelligent Automation?
Intelligent automation plays an important role in optimizing existing business workflows and transforming operations to improve outcomes for both employees and customers. Intelligent automation is frequently used to supplement or replace manual human labor, a step that can automate repetitive tasks and improve processes, support complex data analytics taskwork, improve customer experience, enhance risk mitigation strategies, and create new efficiencies that may ultimately reduce business expenses.
Bottom Line: Intelligent Automation Improves Productivity
Intelligent automation has gained steam in recent years, not only because it incorporates today’s most sophisticated AI technologies but also because it offers a significant improvement in business productivity. This is a dynamic time for intelligent automation and a great time to get started with the technology. For optimal results, follow the best practices listed above and don’t lose sight of the people who need to be involved. Especially as this technology and its capabilities evolve, you’ll want to ensure that all relevant stakeholders in your business receive the upskilling training they need to support the major productivity boost enabled by intelligent automation.
Read our guide to the best machine learning platforms available in 2024 to find out more about the marketplace of tools, what they can do, how much they cost, and which might be a good fit for your business.

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