What is intelligent automation? A definition

Intelligent automation benefits

Properly implemented, intelligent automation brings a wealth of benefits to any organization. Intelligent automation benefits include:

Save time

“Software developers can code twice as fast with automation via generative AI.” (McKinsey)

Intelligent automation reduces or eliminates manual tasks, freeing your people to spend their time on higher-value work that only humans can complete. They will also be able to complete these tasks faster, accelerating your business processes, decisions, and growth.

Cut costs

“Organizations project a 31% cost reduction over three years by adopting intelligent automation.” (Deloitte)

Intelligent automation lowers the man-hours needed to complete many tasks, reducing their costs and letting you trim your overhead. Most important, with intelligent automation, you can cut these costs while improving the quality of the work.

Reduce errors

“88% of respondents say poor-quality customer data negatively impacts their operations and efficiencies.” (Experian)

Intelligent automation performs tasks more consistently than humans while reducing their associated risks, errors, and costs. With intelligent automation, you can bring this accuracy to complex cognitive activities and decision-making, not just simple tasks.

Unify data

“61% of IT leaders say managing unstructured data is a problem for their organization.” (CIO)

Intelligent automation performs many of the routine tasks needed to centralize, normalize, and integrate myriad data sources. With intelligent automation, you can also automate data analysis, including high-level cognitive tasks like sentiment analysis.

Maintain compliance

“92% of manufacturers state robotic process automation improved compliance.” (Deloitte)

Intelligent automation can search for incidents of non-compliance and either alert on—or outright remediate—any issues it finds. Further, intelligent automation streamlines the process of auditing and reporting to prove good standing with regulations.

Improve customer experience

“84% of respondents say chatbots and AI improve customer service.” (HubSpot)

Intelligent process automation gives your customers automated support, recommendations, and the experience of chatting with a real human—24x7x365. With intelligent automation, you can also offer consistent digital services and experiences at any scale.

Enhance processes

“AI can automate up to 70% of business activities by 2030.” (McKinsey)

Intelligent automation provides data-driven insights and recommendations to improve business processes at every level. With intelligent automation, you can continuously refine your performance, surface new opportunities, and rapidly fix inefficiencies.

Intelligent automation (IA) vs robotic process automation (RPA)

What is intelligent automation (IA), and how does it differ from robotic process automation (RPA)? While IA and RPA are sometimes used interchangeably, these are two distinct practice areas.

RPA is a technology that automates simple, digital tasks like completing forms, organizing documents, or performing simple searches and queries.

Intelligent automation is the process of integrating AI with systems in order to automate more complex tasks, generate insights, and learn from experience.

This creates some fundamental differences between IA and RPA and what they can do.

Simple vs complex

RPA can only complete simple tasks, like organizing, moving, and storing data or files. Most of these tasks are manual, time-consuming, and highly repetitive—and worth automating—but do not require cognition, interpretation, or analysis of content.

IA can complete complex work that requires higher-order thinking. For example, it can “read” the text within a file and categorize it based on intent, or analyze website usage data to find patterns and suggest improvements that would increase conversion rates.

Programmed vs self-learning

RPA can only work within a set of rules. Either an RPA system is programmed to complete a few specific steps, or a user records a task and the RPA solution copies their behavior. Either way, RPA can only repeat what it’s told or shown to do.

IA can teach itself how to complete tasks, and can improve its performance the more it repeats a task. While RPA will always repeat a task the same way every time, IA can identify more efficient steps to reach the same outcome at higher accuracy rates.

Siloed vs integrated

RPA technology largely works in isolation. An RPA system is typically self-contained and has everything it needs to complete its tasks. Each bot is programmed to complete one simple task that does not connect directly with anything other bots are doing.

IA is an integrated solution. Different elements of the solution can learn from each other, and the solution can combine a wide range of cognitive capabilities like computer vision, business process management, and character recognition from external tools.

In sum: Intelligent automation (IA) vs. robotic process automation (RPA) is a false debate. Intelligent automation is a modern process that layers over robotic process automation and lets you automate more complex workflows, and robotic process automation is a component of intelligent automation. Overall, intelligent automation and robotic process automation are two components of a single system for automating modern, complex, digital workflows.

Intelligent automation upgrades robotic process automation–giving you even greater speed, cost savings, and performance boosts across more processes.

Intelligent automation business use cases

You can realize intelligent automation benefits by automating, simplifying, and improving a wide range of workflows. These include, but are not limited to:

• Collecting, correlating, and analyzing data
• Sending and responding to security, operational, or regulatory alerts
• Powering chatbots, resource sharing, and support ticket routing
• Writing personalized content including emails and SMS texts
• Automating and scaling business processes

This makes intelligent automation a flexible practice that can assist with any use case that involves digital tasks—which means every use case in the modern business landscape. A few common intelligent automation business use cases include:

Onboarding and offboarding

IA can assist with onboarding and offboarding employees. It can accelerate the completion of HR paperwork, equipment provisioning or reclamation, training modules, and other tasks. It can also onboard new customers and clients by personalizing initial communications and capturing, tagging, and sorting all necessary information.

Customer service

IA can automate nearly every touchpoint between your business and your customer. It can run and improve chatbots, email and SMS sequences, and other communications—while also adding data to your backend systems, tracking each customer’s progress through their lifecycle, and sending alerts when manual human intervention is needed.

Product management

IA can assist with most points in a product’s lifecycle. It can accelerate product development by automating routine tasks, and even help determine what new products and features to build in the first place. It can also help manage inventory, fulfillment, and shipping, and predict supply and demand cycles to avoid potential shortages.

Sales and marketing

IA can A/B test marketing materials to quickly identify the most effective and efficient assets and campaigns. From there, it can analyze and score leads, automate and enhance many functions within customer relationship management (CRM) software, and help forecast sales based on industry trends and past performance.

Strategy and planning

IA can collect, analyze, and pull insights from vast quantities of data. Doing so, it can identify market opportunities, forecast demand for new products and services, and predict future revenue based on different actions—while freeing employees at every level of the organization to spend less time on routine tasks and more on big-picture thinking.

Vulnerability management

IA can identify both known and unknown vulnerabilities within the IT stack that could lead to security or operational incidents. From there, it can automate many routine tasks of vulnerability management like applying patches and updates, configuring assets and applications, and prioritizing remediation actions to resolve highest-risk areas first.

Industry-specific use cases

Finally, intelligent automation business use cases can support many industry-specific needs. These include:

• Automating product review and quality assurance for manufacturing
• Running simulations of potential compounds for pharmaceuticals
• Calculating risk, rate, and payment combinations for insurance
• Analyzing, diagnosing, and treating conditions consistently for healthcare
• Predicting and responding to supply and demand trends in retail

Why intelligent automation matters in AIOps

Intelligent process automation goes hand-in-hand with the field of AIOps.

AIOps leverages AI to better manage IT infrastructure. It uses data pulled from a mature observability practice to rapidly detect operational and security problems, to investigate them thoroughly, and to better understand what happened and how to remediate it. In turn, this helps teams solve IT problems faster, easier, and more completely.

AIOps also gives security and operations teams the visibility, control, and insights they need to proactively find and fix vulnerabilities within their IT estate, and to overall improve and maintain the performance of their technology infrastructure.

Intelligent automation is a core component of AIOps. It automates many of the complex tasks and analyses involved in AIOps, and provides a fast, accurate, and scalable way to resolve any issues that AIOps brings to light.

In sum: Intelligent automation is powerful on its own, but it becomes even more effective when combined with AIOps and a mature observability practice. Together, they let you automate many of the most important elements of keeping your IT infrastructure up and performant.

Combining AIOps with Intelligent Automation

BMC offers a simple, powerful, unified solution that makes it easy to integrate intelligent process automation with AIOps and observability—all within one platform, out of the box.

BMC Helix for Observability and AIOps is a full stack solution and is a recognized leader in its category that provides every essential capability to establish both observability and AIOps within your IT stack. These core capabilities include:

Helpful resources about intelligent automation

• What Makes Automation Intelligent?
• Unifying Automation with an Intelligent Automation Broker
• Smar AIOps: Service Prediction and Intelligent Automation