The above image from Workfusion’s Combining RPA + AI webinar, nicely summarizes both RPA and cognitive automation. While RPA is the doer, cognitive is the decision engine.
Cognitive automation or also called intelligent / smart / hyper- automation or AI process automation is the hottest field in automation. Talk to any RPA company CEO and they will start talking about cognitive automation, at least Max from WorkFusion was most excited about cognitive automation in our podcast.
While automation is old as the industrial revolution, digitization greatly increased activities that could be automated. However, as you can read more on our guide on RPA tools, initial tools for automation, which includes scripts, macros and robotic process automation (RPA) bots, focus on automating simple, repetitive processes. This makes sense because most core corporate processes are quite repetitive but not repetitive enough to completely take human out of the loop with simple programming. However, as those processes are automated with the help of more programming and better RPA tools, processes that require higher level cognitive functions are next in the line for automation.
Key capabilities for cognitive automation
Natural language processing (NLP): Even basic language understanding makes it much easier to automate most customer service processes or processes involving contracts.
Optical Character Recognition (OCR): Despite increased digitization, a mind-boggling amount of paper is still used, especially in heavily regulated industries like healthcare or banking. Processing these papers are required to automate any process end-to-end.
Machine learning: Processes require decisions. If those decisions can not be formulated as a set of rules, machine learning solutions are required to replace human judgement with machine judgement and automate processes.
Let’s look at what bots will do with these capabilities.
Cognitive Automation Solution Providers
Cognitive RPA solutions by RPA companies
- Automation Anywhere is marketing IQ Bot as a cognitive RPA solution that incorporates AI capabilities.
- Blue Prism calls their bots advanced capabilities intelligent automation skills.
- UiPath promotes cognitive automation under intelligent process automation. Its solutions suite includes bots to manage other bots which UiPath calls unattended automation. According to UiPath: “Automated bot managers reduce automation costs & meet service levels by synchronizing queued work and robot deployments with scheduled workflows and events; monitoring & triggering failover procedures, as needed”
- WorkFusion promotes their bots cognitive capabilities under Smart Process Automation.
Cognitive RPA solutions by RPA ecosystem
While these are efforts by major RPA vendors to augment their bots, RPA companies can not build custom AI solutions for each process. Therefore, companies rely on AI focused companies like IBM and niche tech consultancy firms to build more sophisticated automation services.
Cognitive plugins/bots in RPA marketplaces
Additionally, large RPA providers have built marketplaces so developers can submit their cognitive solutions which can easily be plugged into RPA bots. Read our article on RPA marketplaces to learn more.
Discovering mismatches between contracts and invoices: Deloitte explains how their team used bots with natural language processing capabilities to solve this issue.
Offering end-to-end customer service with chatbots: While chatbots are gaining popularity, their impact is limited by how deeply integrated they are into your company’s systems. For example, if they are not integrated into the legacy billing system, a customer will not be able to change her billing period through the chatbot. Cognitive automation allows building chatbots that can make changes in other systems with ease.
Banking – Fulfilling KYC requirements: Leverage public records, handwritten customer input and scanned documents to perform required KYC checks.
Banking – Processing trade finance transactions: Banks finance international trade. Processing these transactions require paperwork processing and completing regulatory checks including sanctions checks and proper buyer and seller apportioning.
Insurance – Servicing policies: Data mining and NLP techniques are used to extract policy data and impacts of policy changes to make automated decisions regarding policy changes.
Insurance – Claims processing: Make automated decisions about claims based on policy and claim data and notify payment systems.
Though cognitive automation is a relatively recent phenomenon, most solutions are offered by Robotic Process Automation (RPA) companies. Check out our RPA guide or our guide on RPA vendor comparison for more info. You can also learn about other innovations in RPA such as no code RPA from our future of RPA article.
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