Robotic process automation (RPA) has become an essential technology for enterprises seeking to drive digital transformation. By deploying software bots to automate repetitive manual processes, companies can achieve new levels of speed, quality, and efficiency.
The rising adoption of RPA is being enabled by a dynamic marketplace of leading RPA vendors offering innovative capabilities via on-premise, cloud, and hybrid tools. With new RPA products emerging all the time, making the optimal platform choice to match specific automation needs has never been more important.
This comprehensive guide provides an in-depth look at over 50 of today‘s most prominent RPA tools and vendors powering the growth of hyperautomation globally. We analyze key selection criteria—from licensing models to core features sets and more—to determine the solutions best suited for various use cases. Additionally, we explore the latest RPA innovations advancing no-code automation, AI integration, analytics, and more.
Why Enterprises Are Embracing RPA Tools
Before exploring the RPA vendor landscape, it’s important to ground the conversation in an understanding of what robotic process automation entails and why it has experienced surging adoption across industries in recent years.
RPA definition: Software robots (bots) that automate repetitive, rules-based digital tasks normally performed by human workers in order to improve operational efficiency.
While definitions vary across tech analysts, RPA broadly refers to the application of technology to directly integrate and perform specific workflows, activities, and processes across existing enterprise systems. RPA bots handle repetitive tasks from data entry to report generation faster and more accurately than people can achieve manually.
Key drivers spurring companies to invest in RPA tools include:
- Cost reduction – Automating manual work minimizes labor expenses
- Increased throughput – Bots work around the clock without rest to scale output
- Improved accuracy – Software robots minimize human errors
- Enhanced compliance – Audit trails created during RPA support governance
- Accelerated digital transformation – RPA enables legacy modernization and innovation
According to Gartner, global RPA software revenue surpassed $1.4 billion in 2019 and is estimated to reach $2 billion by 2024. Predictably, all industry verticals are expected to increase RPA budgets in the coming years to remain competitive.
Analysis of Leading RPA Software Vendors
With growth forecasts projecting continued RPA adoption, all enterprises looking to leverage intelligent process automation face an imminent platform decision. The multitude of available solutions span proprietary on-premise tools to cloud platforms to RPA-as-a-Service—not to mention open source options.
While the ideal selection comes down to individual automation goals, we break down over 50 of today‘s most widely leveraged RPA products across major solution providers:
Prominent RPA Vendors
- UiPath
- Automation Anywhere
- Blue Prism
- Microsoft
- IBM
- Pega
- NICE
- WorkFusion
- Kofax
- Kryon Systems
- Edgeverve Systems
- Another Monday
- AntWorks
- AutomationEdge
- NTT-AT
- Olive.AI
- Laiye
The list goes on. But how do enterprises narrow options? Every RPA tool brings unique capabilities to appellant buyer personas across industries. Generally speaking, factors for comparison fall into a few major buckets:
Programming and Usage Options
The way RPA solutions are programmed and deployed depends greatly on an organization’s technical prowess and intended functionality. Bots require an interface for establishing rules and triggers to perform designed sequential tasks. Programming options include:
Code-Based: Traditional development ideated by technically adept programmers
Low-Code: Drag-and-drop design enabled by business users with some technical supervision
No-Code: Visual point-and-click bot building needing little-to-no coding skills
Similarly, RPA tools each serve distinct automation scenarios from completely unattended automation to attended bots requiring human supervision:
Attended: Bots act when triggered by user and serves as virtual assistant
Unattended: Self-contained automation without need for ongoing user direction
Hybrid: Combines aspects of attended and unattended for flexible oversight
Matching programming approach to deployment method ensures RPA solutions remain user-friendly and effective over their lifecycles. Some vendors enable multiple techniques while others specialize in one focus area.
Embedded Intelligence
Beyond baseline automation functionality, modern RPA platforms increasingly offer baked-in artificial intelligence, analytics and machine learning capabilities to enable true cognitive automation. Known as Intelligent Process Automation (IPA) or Hyperautomation, self-learning software robots can handle unstructured data streams, sense environmental shifts, and take corrective actions adaptively—no coding required.
RPA tools with strong IPA abilities feature:
- Computer vision for scanning documents and interpreting contents
- Natural language processing to analyze communications
- Machine learning algorithms that update behaviors based on insights
- Predictive analytics to notify other enterprise software proactively of expected outcomes
As RPA advances, AI integration accelerates value creation. According to Deloitte, AI-enhanced RPA delivers 200%+ ROI by enabling end-to-end process improvement versus point automation. Discerning AI aptitude across vendors assists in prioritizing full hyperautomation.
Pricing Models and Marketplace Ecosystems
Pricing structures and accompanying marketplaces for sourcing pre-built automation assets represent additional RPA software differentiators for prospective buyers. Common licensing fee approaches divide into:
1) Per Bot: Price based on number of deployed bots
2) Per Process: Cost scales based on workflows automated
3) Per User: Shared licensing pools for fixed fees
Accompanying solution marketplaces enable grabbing pre-made downloadable bots, algorithms, templates, workflows, connectors, AI tools, and more for custom development. Strong ecosystems add value by eliminating reinvention needs when productionalizing automations.
Now equipped with a general lay of the RPA landscape competitive overview, how should interested adopters navigate toward the ideal platform provider? First, take a methodical approach…
A Structured Methodology to RPA Tool Selection
The proliferation of capable RPA software options makes pinpointing solutions aligned to in-house needs challenging. However, following a clearly defined RPA evaluation methodology helps remove ambiguity from the vetting process:
Step 1: Define Operational Automation Goals
Get clear on the current state workflow frictions targeted for RPA improvement. Quantify anticipated efficiency lift across measurable metrics from task hours saved to direct cost reductions. Interview business units on pain points solvable via intelligent automation. Inventory primary systems involved from claim processing apps to custom APIs to ERP platforms. Understanding goals and constraints upfront drives tool criteria prioritization next.
Step 2: Create an RFP Highlighting Must-Have Capabilities
With goals defined, craft an RFP document that captures must-have capabilities sought in solution options as well as nice-to-have bonus criteria. Include preferred pricing models, implementation timelines, analytics needs, compliance requirements, and more. The RFP provides an objective means of communicating desires to vendors clearly while enabling equitable comparison.
Step 3: Research Platforms Aligning Closest to Set RFP Criteria
Leverage the created RFP as a consistent yardstick for measuring vendors against. Categorize products in spreadsheet format marking how completely they satisfy outlined platform preferences. Then narrow consideration to the top 2-3 highest scoring for next round consideration. Avoid overinvesting in extensive product demos upfront before general suitability alignment gets established.
Step 4: Initiate Discussions with Down-Selected Providers
With a targeted shortlist in hand, launch discovery discussions focused on gathering remaining info needed to make a final platform choice. Prepare specific product architecture, security, admin, marketplace, roadmap, pricing, and level-of-effort questions needing answers to complete due diligence. Request demos showcasing actual tools if not completed already. Calculate total cost of ownership across options.
Step 5: Make Data-Driven Selection Aligned to Future Vision
Cross all gathered intelligence on preferred solutions to land on RPA software delivering needed functionality now yet allowing ample runway for scale, flexibility, and innovation absorption longer-term. Negotiate agreeable terms before contracting. But avoid over-indexing on initial cost alone—the total value derived over the complete automation lifecycle matters most when aiming to maximize ROI.
While the outlined selection approach provides guardrails to an optimal outcome, buyers must equally inform themselves on the latest RPA capabilities changing marketplace dynamics…
Key RPA Innovations Expanding Intelligent Automation Horizons
The world of enterprise automation software continues advancing at speed—meaning resting on status quo capabilities threatens future solution relevance. Savvy RPA adopters gain advantage by tracking leading-edge vendor innovations as they emerge to best position their roadmaps.
The Rise of No-Code RPA Acceleration
While early RPA tools required technical specialists for implementation, demand has risen significantly for no-code solutions enabling business users to build bots safely without IT assistance. According to Deloitte, enterprise interest in no-code automation increased 400% from 2020 to 2021—a trend expected to continue as platforms become more user-friendly.
All leading RPA vendors now incorporate some level of no-code functionality for empowering citizen developers. For example, Microsoft Power Automate, UiPath Studio, and Blue Prism all enable visual workflow configuration sans traditional programming. Expect no-code automation to dominate enterprise strategies moving forward.
Embedding of AI for True Hyperautomation
As referenced earlier, RPA’s evolution toward intrinsic AI-enabled intelligent process automation (IPA) unlocks vastly expanded use cases and business value. Turning data into insights for adaptive task completion, self-healing bots, predictive analytics, and more drives the next transformation wave.
Here again, all major RPA players bake emerging AI into core engines using machine learning, NLP, computer vision and beyond to deliver hyperautomation. For instance, leading no-code RPA tool Automation Anywhere integrates IQ Bot for adding natural language chatbot interfaces to workflows within its cloud-native platform. WorkFusion offers an RPA platform purposefully designed from the ground-up focused on embedded AI for human-bot collaboration.
Sophisticated cognitive skills packaged into turnkey RPA systems prompt faster achievement of full-scale enterprise automation.
Frameworks for Scaling Automation Across the Business
Piecemeal task-specific automation leaves much efficiency still on the table versus taking an expansive governance approach to intelligently coordinating bots across departments. Resultantly, RPA thought leaders like UiPath now provide automation-friendly integrated process mining tools, control panels with analytics, and development suites that enable modeling 100s of use cases using shared, secure resources.
Replication of winning recipes across the enterprise signals the next wave of leveraging RPA innovations for breakthrough performance.
SaaS and the As-a-Service Delivery Model Shift
The days of standalone on-premise RPA are fading fast. The as-a-service software boom now sees companies like Microsoft, IBM, SAP and indeed all major automation players offer RPA-in-the-cloud. Cost economies, flexibility, mobile accessibility, speedier deployment, embedded compliance and maintenance represent inherent benefits.
Further still, purpose-built RPA-as-a-Service (RPAaaS) solutions provide instantly available automation capabilities without infrastructure demands. For example, platforms like Anvil, Robocorp, and FortressIQ deliver just-in-time intelligent process automation via simplified subscription-based consumption. As cloud becomes the new enterprise norm, how RPA gets delivered matters.
Tracking these winds of marketplace change help future-proof any business pursuing hyperautomation excellence over the long-term. But what does RPA tool innovation look like in-practice vertically?…
Industry Use Cases Demonstrating Intelligent Automation ROI
While the foregoing highlights advancing RPA landscape dynamics universally, seeing platform impact through real-world lenses offers more tangible context. Use cases where automation drove marked efficiency and performance lift last year across sectors include:
Banking/Finance
- Global bank applying over 500 bots to processes from new account opening to loan origination resulting in 50%+ cost reduction and 90%+ straight-through processing of transactions.
Healthcare
- Hospital network leveraging RPA and AI chatbots to automate patient appointment scheduling and admissions processes—saving $12 million annually.
Public Sector
- International labor agency streamlining multi-system welfare payments processing via bots—reducing errors 82% and lowering cost per application from $75 to $25.
Energy
- Multinational electric utility company applying RPA across customer service, plant maintenance and safety testing flows—realizing 2 million+ saved labor hours each year.
Retail & CPG
- Leading footwear seller using eyeglass camera-equipped bots in warehouses to scan shelf inventory and address stockouts in real time while reducing refill cycle time 86%.
Technology
- Fortune 500 tech manufacturer building next-gen voice assistant products applying RPA across Accounts Payable for 70%faster invoice processing at 60% lower cost.
As exemplified, all verticals stand to gain hard ROIs from specialized RPA tools automating previously slow and expensive tasks gaps. The promise of hyperautomation indeed looks bright according to analysts…
The Outlook for Continued RPA Software Market Expansion
Underpinning enterprise urgency to continually evaluate and evolve chosen automation approaches, predictions call for both the sheer volume and capability scope of RPA adoption to increase in the years ahead.
Per market research firm Interact Analysis:
- Annual RPA software license sales expected to grow at 34% CAGR from $1.4B in 2021 to $13B by 2030
- 70% of newly developed applications will embed intelligent automation by 2025
- 50% of enterprises will replace native platform UI process flows with automated bots by 2023
And per consulting giant McKinsey:
- As many as 30% of activities across just retail sector supply chains could be automated using available best-of-breed RPA solutions alone
- Combining RPA with AI and advanced analytics doubles typical capacity release from automation efforts
- Companies that comprehensively leverage data, AI and automation show revenue growth rates 3x faster than industry peers
The message becomes clear: RPA innovation and adoption will accelerate in pervasiveness and push boundaries of capability further in short order. The winners will be those enterprises nimble enough to grab breakthrough tools tailor-fitting their unique automation needs as they emerge.
Conclusion: Choosing & Scaling RPA Software Over the Automation Journey
RPA software has transitioned from novel efficiency concept to mission-critical enterprise capability seemingly overnight. However, amidst the expansive solution choice spectrum facing prospective buyers, making optimal platform decisions need not cause confusion.
By taking a structured selection approach, maintaining future vision flexibility, and leveraging consultants as needed, organizations can identify and deploy high-ROI automations with confidence. Further, tracking industry innovation trends ensures transformation initiatives sustain value creation amidst inevitable vendor marketplace shifts.
At the end of the day, each business’ RPA tool requirements remain distinctive. But no enterprise can afford leaving efficiency opportunities untapped at scale. So constructing an informed automation roadmap uniquely aligned to strategic goals and supported by adaptable solutions delivers the clearest path to hyperautomation ROI realization now and tomorrow.
