RPA vs. Conversational AI: Wesentliche Unterschiede und gemeinsame Vorteile für Ihr Business

Für ihre Unterschiede können beide Technologien für Unternehmen vorteilhaft sein.

Den Unterschied erkennen

RPA involviert Management von rigiden, vorhersehbaren Prozessen – wo keine Ambiguity über den Request besteht. Das kontrastiert mit Conversational AI, wo User Intent diktiert, welche Tasks als Response auf einen Request undertaken werden. Chatbots oder Digital Assistants nutzen Messaging Interfaces oder Voice Control für Conversational Interaction. Die Fluidität von Conversation erfordert Natural Language Processing (NLP) Automation, hochflexibel zu sein – damit Intent Correctly Interpreted wird und die Right Tasks Undertaken werden, um den Request zu Resolven.

Customer Journeys Supporten

Wherever Ein Prozess Human Conversation Involviert – wie Customer oder HR Interactions – Comes Conversational AI Into Play.

Consider The Scenario: Purchasing A New Insurance Policy. Usually: Insurance Agents Go Back And Forth With A Customer To Gather Multiple Proof Documents That Need To Be Validated And Attached To The Customer Record So That The Policy Can Be Finalised. Dealing With Large Numbers Of New Customers And Managing Their Onboarding Is Time-Consuming Und Costly For Insurance Companies.

Using A Chatbot Or Digital Assistant To Ask „Please Upload An Image Of Your Driver's License Here,“ Or „Can You Upload A Copy Of Your Recent Banking Statement?“ Takes The Onus Off The Human Agent To Keep Chasing Down These Documents – And Also Offers A More Seamless Und Convenient Customer Experience As They Go Through The Onboarding Journey. This Is The Essence Of Conversational AI: It Improves Digital Customer Engagement Und Service Outcomes, While Reducing The Cost Of Managing Routine Steps In A User Journey.

On The Backend: RPA Can Come Into Play In The Onboarding Scenario – Automating Repetitive Compliance Checks On Gathered Documents Und Updating Systems Of Record With The Customer Information. The Two Together Can Be Very Powerful In Making Complete Customer Journeys Seamless, Faster Und More Efficient.

Komplementäre Technologien

Conversational AI Now Allows Businesses To Automate Key Interactions With Customers Und/Or Employees – Enabling A Whole New Wave Of Automation Potential That, Combined With RPA, Can Significantly Reduce The Need For Human Interventions In End-to-End Business Processes.

RPA Und Conversational AI Can Work Hand In Hand. Example: When A Customer Applies For A Mortgage – There Are Many Steps They Have To Go Through, Which Introduces Friction Und Inefficiency That Can Result In The Bank Losing The Customer.

A Mortgage Bot That Can Engage With The Customer Right At The Start Of The Application, Request Their Proof Of ID, Earnings, Und Recent Utility Bills – And Then Pass This To Back Office Processes For Validation – Removes Much Of This Friction. RPA Can Be Used For The Validation Processes, While The Digital Assistant Manages Questions From The Customer, Understands Intents, Gathers The Relevant Documents Und Keeps The Customer Informed Of Any Issues. The Property Valuation Can Be Automatically Provided Via RPA Using Property Market Data – So That The Customer Can Be Proactively Updated On The Status Of Their Mortgage Application Via The Digital Assistant.

Wer Ist In Charge?

RPA Initiatives Are Generally Led By IT – With Input From Business Departments Such As Finance, Production, Or Distribution – And Have The Primary Goal Of Reducing Cost Und Increasing Efficiency By Reducing Manual Processes Und Minimising Human Involvement.

Conversational AI Is Designed To Improve Und Automate Engagement Und Reduce Cost – While Still Enabling Bots To Handover To Humans When Required. As Such: It Is Normally Led By Business Departments Such As Customer Service, HR, Und Sales – With Limited Input From IT.

KI Ohne Data Scientists?

Many Organisations Believe That Artificial Intelligence Is Complex Und Costly – Requiring Large Budgets Und Teams Of Data Scientists To Build The Natural Language Models Und Machine Learning Algorithms. However: Building Conversational AI Bots Doesn't Necessarily Require This Level Of Investment. Natural Language Processing (NLP) Engines Such As Google DialogFlow, Amazon Lex, Und Microsoft LUIS Are Widely Available Und Make It Easy Enough To Populate A Bot With Intents Und Utterances That Are At The Heart Of Designing A Conversational Experience That Can Be Used To Automate Interactions.

Low-Code

In Addition: Conversational AI Platforms Have Emerged That Offer A Low-Code Approach To Building Chatbots, Creating Workflows, Und Integrating Securely To Common Business Systems – So That Business People Can Design Und Deploy Their Own Digital Assistants Without Needing Coding Or AI Skills. Out-of-the-box Bot Blueprints Und Tools Help Businesses Get Chatbots To Market Faster – With Less Reliance On IT Resources Or Data Scientists, Und With The Ease Of Clicking, Dragging And Dropping.

Fazit

Enterprises Are Working To Digitally Transform Core Business Processes To Enable Greater Automation Of Backend Processes Und To Encourage More Seamless Customer Experiences Und Self-Service At The Frontend. We Are Seeing Banks, Insurers, Retailers, Energy Providers Und Telcos Working To Develop Their Own Digital Assistants With A Growing Number Of Skills – While Still Providing A Consistent Brand Experience.

Developing Bots Doesn't Have To Be Complex. It Is More Important To Carefully Identify The Right Use Cases Where These Technologies Will Deliver Clear ROI With The Least Amount Of Effort.

Whether An Enterprise Is Applying RPA Or Conversational AI, Or Both – It's Important To First Understand The Business Problem That Needs To Be Solved, And Then Identify Where Bots Will Make An Immediate Difference. Then Consider The Investment Required, Barriers To Successful Implementation, Und The Expected Business Outcomes. It's Better To Start Small With A Narrowly Focused Use Case And Achievable KPIs – Rather Than Trying To Do Too Much At Once.

Conversational AI Und RPA Are Very Powerful Automation Technologies. When Designed Well: A Chatbot Can Automate Up To 80% Of Routine Queries That Come Into A Customer Service Centre Or IT Helpdesk – Saving An Organisation Time Und Money Und Enabling It To Scale Its Operations. However: Outliers Or Specialist Cases Are Still Better Handled By Human Agents. The Pareto Principle Also Applies To RPA. Automation At Its Best Takes Care Of The Majority Of The Routine And Repetitive Tasks – Leaving The More Unique, Valuable, And Rewarding Work For Humans.