Intelligent automation is revolutionizing how work gets done across industries from banking to healthcare. Powered by cutting-edge technologies like robotic process automation (RPA), artificial intelligence (AI) and machine learning, intelligent automation enables the digitization and automation of complex business processes.
The result? Enterprises that implement intelligent automation report major improvements across key metrics including:
- 50-80% reductions in processing time and cost
- Near 100% increases in throughput, productivity and accuracy
- Rapid ROI typically within 6-12 months
To better understand the real-world impact of intelligent automation, let‘s examine case studies and examples from leading global companies across sectors that have successfully deployed these solutions.
The Real Results of Intelligent Automation Adoption
First, let‘s set the broader context around intelligent automation (IA) adoption and results across regions and industries. This will help frame the transformational potential being realized globally today.
Intelligent Automation Market Size
The global intelligent automation market is projected to grow at a rapid 29% CAGR from $18.2 billion in 2022 to reach $42.5 billion by 2024 according to recent Meta4 estimates.
North America leads adoption with a 43% regional share, but Europe and APAC are also seeing surges in IA spending.
The graph below summarizes the rapid growth:
Source: Meta4 2022 Global Intelligent Automation Survey
This exponential growth underscores how enterprises globally and across sectors are still in early stages of tapping automation‘s potential.
Industry Adoption Rates
Currently financial services leads intelligent automation adoption with over 50% of applicable processes automated on average.
But other industries are quickly following suit. The chart below summarizes adoption rates across sectors:
Source: Everest Group 2021 Process Automation Benchmarking Study
As highlighted, leading industries like banking, insurance, telcos and healthcare are automating 35-50%+ of key processes already. Still, even the most aggressive sectors have significant runway to penetrate the estimated 60% to 80% ceiling of automatable processes per enterprise.
Now let‘s explore real-world examples of IA transformations happening today across sectors and leading firms.
Intelligent Automation in Banking & Financial Services
Financial services has emerged as one of the leading adopters of intelligent automation technology…
Additional Major IA Case Studies
Beyond the Bankcolombia and Swiss Re examples, numerous financial leaders are using IA to drive major benefits:
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Petroleum giant BP leveraged RPA leader Automation Anywhere to automate high volume, repetitive AP processes including invoice receipt and payment. This freed up thousands of hours for the finance team to focus on value-add analysis. By eliminating invoice errors using bots, BP also saved an estimated $50 million annually.
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Global bank Standard Chartered deployed RPA, AI and analytics solutions from EdgeVerve to enhance straight through processing, compliance and customer experience. By processing over 160 million account transactions with software bots, the bank increased STP rates 15%+ while also improving regulatory rigor.
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Leading investment bank JPMorgan Chase built an "AI factory" to drive automation use cases at scale leveraging IPsoft‘s Amelia cognitive platform. In early testing, virtual agents handled thousands of help desk queries, yielding $3 million+ in savings. With expanded use, JPMorgan estimates it may save $300 million+ annually using AI.
Intelligent Automation Use Cases in Healthcare
Healthcare has emerged as a surprise leader in intelligent automation adoption thanks to numerous processes prime for digitization and ongoing margin pressures…
In Depth: Pharmaceutical IA Success
A closer look at the pharmaceutical sector highlights the incredible operational efficiencies and cost savings intelligent automation is enabling:
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Leading biopharma firm AstraZeneca automated over 175 processes with RPA and boosted straight through processing (STP) by 15%. This yielded $42 million in savings annually from eliminating manual work.
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Amgen leveraged RPA for automating adverse events case intake and processing. Bots now handle over 80% of cases autonomously, leading to $14 million in projected bottom line savings.
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Johnson & Johnson Consumer Health deployed RPA across quality assurance, finance and regulatory processes, achieving 50-70% improvements in cycle times, data quality and compliance.
The examples underscore why pharma has emerged as an automation pioneer. As firms face pricing pressures amid patent cliffs, using IA to boost throughput and cut costs unlocks major competitive upside.
Cuts Across Sectors: Retail, Energy and Beyond
Beyond banking, insurance and healthcare, IA drives results across today‘s leading companies globally and industries from CPG to media and entertainment…
Retail
Global retailer Target revamped order reconciliation by combining RPA with machine learning algorithms. Bots now handle manual matching tasks previously done by staff. This yielded $6 million in direct labor savings annually and improved accuracy by 20%.
UK supermarket giant Tesco automated critical supplier rebate management processes using RPA. Tesco reduced processing times from 4 weeks to 4 days while also improving compliance.
Energy
EDF Energy leveraged RPA and machine learning for customer service operations including billing calls. Virtual agents now handle 43% of all call volume with 50%+ faster resolution times. EDF realized $3.5 million in savings the first year from automating calls, and projects 20%+ gains ongoing enabled by no longer needing to hire seasonal staff.
Duke Energy built an automation center of excellence with Blue Prism RPA to optimize key processes from customer onboarding to payroll. By 2021, Duke automated 60 processes executing over 1 million transactions annually. Duke also realized $14 million in benefits as increased productivity from bots offset pending headcount adds.
Media & Entertainment
ViacomCBS (now Paramount) deployed software robots to automate metadata tagging for video assets and chapters. RPA radically decreased processing times from 3 days manually to 3 hours automatically. This enabled faster content publishing to Paramount+ amid the streaming wars.
ESPN automated sports broadcast captioning leveraging AI speech-to-text models rather than outsourced labor typing captions in real time. The natural language platform boosted caption accuracymaterially while also saving millions in annual transcription fees.
The above are just a sample of IA leaders and results across today‘s enterprises. But for companies just getting started, what‘s the best path to drive ROI?
Getting Started With Intelligent Automation
The proven real-world case studies clearly showcase the transformative potential of intelligent automation. However, to successfully drive ROI, companies must follow structured best practices when evaluating and deploying automation solutions.
Here is a high-level guide to getting started:
1. Assess automation potential – Profile and prioritize processes based on suitability for automation quick wins as well as long-term ROI
2. Define the business case – Build the business, functional and technical cases backing automation with clear ROI projections
3. Start small, scale fast – Prove automation value via pilots before expanding across the enterprise. Lessons from initial deployments can help maximize benefits of wider rollouts.
4. Focus on change management – Successful automation requires new ways of organizing teams and work – plan extensively for the people transition
5. Continually optimize – Apply analytics and intelligence to guide the automation journey, identify emerging use cases and drive continuous improvement
For detailed guides on intelligent automation strategies, best practices, tool selection and more, see:
- The Complete Guide to Implementing Intelligent Automation
- 10 Steps to Build an Enterprise Intelligent Automation Strategy
- Intelligent Automation Tools – Comprehensive Guide
Cutting Edge Innovations Further Expand Potential
As highlighted throughout this analysis, leading enterprises are already leveraging intelligent automation to drive tremendous efficiency gains today. However there are also exciting innovations emerging that will expand automation possibilities exponentially in coming years:
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Process Intelligence solutions from leaders like Celonis can automatically analyze desktop activity logs and enterprise systems to identify automation opportunities organizations didn‘t even realize existed. This "automated process discovery" flips traditional manual assessments to realize 10X+ more use cases.
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Integrating IA with cloud data platforms and lakes will allow coordinating and syncing automation flows across previously siloed legacy systems. This will power true enterprise-grade, scalable automation.
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AutoML advancements will ease non-technical users training machine learning models to handle more unstructured data like Computer Vision analysis of documents. This democratization promises to boost automation rates for previously human-dependent tasks.
Real Results Show the Power of Intelligent Automation
As highlighted by the cross-section of case studies and examples detailed above, leading global enterprises across banking, insurance, manufacturing, retail and more are using intelligent automation today to drive tremendous efficiency improvements, cost savings and competitive advantages.
We are only in the early innings of the automation revolution powered by cutting-edge technologies like RPA, AI and machine learning. As the case studies and market data proves, first movers in leveraging automation will secure significant advantages in their industries.
Now is the time to assess if and how intelligent automation can reshape your operations for the better. The examples and results showcase what is possible – and prove automation delivers the future today for forward-looking enterprises.