The Top 5 Trends That Will Shape the Future of RPA in 2024 and Beyond

ByPaul Christiano Last Update on

Robotic Process Automation (RPA) has exploded in popularity in recent years as businesses seek new ways to automate repetitive, rules-based tasks. RPA adoption grew over 60% in 2021 alone according to Gartner. The global RPA market is projected to reach $13.74 billion by 2028.

With growth accelerating so rapidly, what trends will shape RPA‘s future over the next 3-5 years? As an experienced data analyst and AI consultant, I‘ve been closely tracking developments in the RPA space. In this article, I‘ll provide my insights on the top 5 trends that will transform RPA in 2024 and beyond. Let‘s dive in!

Trend 1: No-Code RPA Will Become Mainstream

One of the biggest barriers holding back many companies from adopting RPA has been the need for technical skills to program and deploy bots. Traditional RPA platforms require coding expertise, making it hard for non-technical business users to implement automation.

But that‘s changing fast. No-code RPA solutions with intuitive drag-and-drop interfaces are emerging so anyone can build bots without coding. By 2024, Gartner predicts 75% of large enterprises will use at least one no-code RPA tool.

No-code RPA democratizes automation by empowering citizen developers across the business. A 2021 survey found that when RPA projects fail, lack of internal skills is a top reason. No-code solutions solve this adoption bottleneck.

For example, Automation Anywhere‘s new Bot Store provides over 200 pre-built no-code smart bots. User reviews show an average bot deployment time of just 2-3 days. Automation Anywhere also acquired FortressIQ‘s no-code process discovery tool in 2021 to further expand no-code capabilities.

Rival UiPath launched UiPath StudioX in 2020 to enable programming-free RPA. It provides record and replay features to easily capture processes for automation using intuitive dragging, dropping, and configuration instead of code.

According to customer Heaven Hill Distillery, UiPath StudioX reduced their automation development time by 50%. The company automated 13 processes in just 3 months to free up employees for more strategic work.

Microsoft Power Automate also offers a no-code approach to RPA within its Power Platform. Its desktop flows feature lets users turn manual processes into automated workflows through recording and graphically mapping steps.

No-code startups like Electra, Robocorp, and WorkFusion are also gaining attention. In 2021, Electra raised $30 million in funding to further develop its visual automation platform.

As no-code RPA matures, it will empower entire organizations to build bots without IT bottlenecks. Employees closest to pain points will be able to automate their own workflows. This self-service automation experience will help scale RPA rapidly across the enterprise.

Trend 2: Hyperautomation Will Connect Multiple Technologies

While RPA provides value in automating repetitive digital tasks, it has limitations when processes require decision making, content analysis, or handling exceptions. This has fueled the rise of hyperautomation – combining RPA with other AI-driven technologies like machine learning, natural language processing (NLP), and computer vision.

According to Gartner, hyperautomation enables organizations to quickly identify, vet, and automate as many processes as possible. It provides sophisticated end-to-end automation seamlessly connecting front, middle and back-office functions.

The global hyperautomation market is projected to grow at a CAGR of 18% to reach $596 billion by 2022. RPA will be the gateway into hyperautomation. Leading RPA vendors are enhancing offerings with embedded AI capabilities:

  • Automation Anywhere – Launched IQ Bot in 2020 which leverages NLP and computer vision for document understanding
  • UiPath – Announced an Immersion Lab in 2021 to research using AI and neuroscience to advance hyperautomation
  • Blue Prism – Partners with Intel and worldwide AI research labs to expand the AI capabilities of its Digital Workforce

As RPA interconnects with more adjacent technologies, it will be able to automate increasingly unstructured and complex processes beyond just screen scraping.

Let‘s look at some examples:

  • Chatbots – RPA can integrate with AI chatbots to provide end-to-end automated customer service across platforms.
  • Computer Vision – Bots can extract info from images like documents, forms, invoices to process unstructured data.
  • NLP – Unstructured text in emails, messages, notes can be analyzed to automate processes.
  • Predictive Analytics – Data patterns identified by RPA can feed decision algorithms to trigger automated actions.

Hyperautomation dramatically expands the scope of RPA by enabling end-to-end intelligent process automation.

Trend 3: Cloud-Native RPA Will Become Standard

Traditionally, RPA has required on-premise bot deployment across user desktops. But there is a growing shift towards cloud-native RPA delivered through SaaS platforms.

According to Mordor Intelligence, the cloud RPA market will reach $7.7 billion by 2026, growing at over 24% annually. SaaS centralizes bot deployment, monitoring, and maintenance without hardware requirements.

UiPath already has over 8,000 enterprise customers on its UiPath Cloud Platform. In 2021, 75% of its new product bookings were cloud-based as companies accelerate cloud migration.

Blue Prism also reported 80% growth in its cloud-hosted Digital Workforce in 2021. Cloud RPA enables faster scaling of automation across the enterprise.

Here are some of the benefits driving adoption of cloud RPA:

  • Faster deployment – Cloud bots can be rolled out in days without on-premise infrastructure delays
  • Centralized control – Cloud dashboards make it easy to orchestrate and manage bots enterprise-wide
  • Scalability – Cloud RPA allows bots to be quickly spun up or down to meet business needs
  • Security – Data and credentials are secured through cloud provider protections
  • Resiliency – Bots stay operational with built-in redundancy and failover

As more companies embrace cloud strategies, cloud-native RPA will emerge as the deployment model of choice for achieving resilient, scalable automation.

Trend 4: RPA Will Become Embedded Into Business Apps

To date, standalone RPA tools have helped prove automation‘s value. But businesses still face challenges integrating bots with existing systems. Siloed automation creates governance and maintenance burdens.

That‘s why RPA will become increasingly embedded directly into business applications – both on front-end UIs and back-end processes. Front-end integration assists employees as they work. Back-end integration automates cross-application data flows.

Microsoft, SAP, Oracle, Salesforce, and ServiceNow are now actively embedding RPA capabilities natively into their popular business apps to drive hyperautomation.

For example:

  • Microsoft – Launched Power Automate Desktop in 2021 to embed RPA into Office 365 and Windows 10 to automate legacy apps.
  • SAP – Introduced SAP Intelligent RPA integrated with SAP Leonardo Machine Learning capabilities.
  • Salesforce – EinsteinBot allows RPA and AI to be embedded directly within Salesforce CRM.

Rather than rip-and-replace systems, embedded RPA supercharges legacy platforms with automation. IDC predicts embedded RPA will represent 60% of RPA adoption by 2024.

Native integration removes the need to deploy standalone bots that must be connected separately into ecosystems. This simplifies tech stacks.

Embedded RPA also enables creating "digital workers" – front-end smart assistants that provide users procedural guidance, answer questions, and handle tasks automatically.

Trend 5: Intelligent Process Automation Will Emerge as the End Goal

While RPA provides the technology to automate tasks, choosing which processes to automate remains a challenge. There is also lack of visibility into automation effectiveness after deployment.

Intelligent Process Automation (IPA) brings together RPA with tools like process mining, machine learning, and analytics for smarter automation. Gartner forecasts a $14 billion IPA market by 2025.

According to their research, IPA adds these capabilities:

  • Hyperautomation discovery – Tools like process mining analyze system logs and activities to uncover automation opportunities and optimize processes.
  • Automation lifecycle governance – Centralized control over RPA bots and models across environments and business units provides standards and risk management.
  • Automation analytics – Dashboards track RPA metrics like bot utilization, human hand-offs, SLA adherence to maximize ROI.

As RPA matures, it will be part of an overarching IPA strategy enabling transparent, ROI-driven automation across the enterprise. IPA provides the missing intelligence layer to align bots with business goals.

Leading RPA platforms are already advancing IPA capabilities:

  • UiPath Process Mining tool tracks end-to-end processes to identify automation potential.
  • Automation Anywhere Bot Insight collects data across bots and systems to monitor performance.
  • Blue Prism Decisions as a Service platform applies intelligent document processing and machine learning algorithms to RPA.

IDC predicts over 50% of RPA customers will use process mining capabilities by 2023. IPA powered by AI will become integral to scaling automation.

RPA adoption is still early-stage with tremendous innovation underway. No-code solutions, hyperautomation, cloud delivery, embedded capabilities, and intelligent process automation will transform RPA over the coming 5 years.

RPA will get smarter, more user-friendly, and integrated into business processes. It will evolve from isolated bots into an enterprise-wide digital workforce capability.

The future of RPA is a fully automated organization – with flexible, intelligent software robots augmenting human employees to enable maximum efficiency. RPA will be the foundation for cross-functional automation that revolutionizes how companies operate.

As an RPA advisor, I‘m excited to see these trends unfold to reshape enterprises. RPA‘s full potential is still untapped. As the technology matures, it will penetrate deeper across industries to become a core business productivity engine and a key driver of digital transformation.

I am Paul Christiano, a fervent explorer at the intersection of artificial intelligence, machine learning, and their broader implications for society. Renowned as a leading figure in AI safety research, my passion lies in ensuring that the exponential powers of AI are harnessed for the greater good. Throughout my career, I've grappled with the challenges of aligning machine learning systems with human ethics and values. My work is driven by a belief that as AI becomes an even more integral part of our world, it's imperative to build systems that are transparent, trustworthy, and beneficial. I'm honored to be a part of the global effort to guide AI towards a future that prioritizes safety and the betterment of humanity.

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