Intelligent Automation
INTELLIGENT
AUTOMATION
For the Future
Intelligent Automation
INTELLIGENT
AUTOMATION
For the Future
AUTOMATE COMPLEX BUSINESS OPERATIONS—AT SCALE
WHAT IS INTELLIGENT AUTOMATION?
Intelligent automation is a combination of artificial intelligence (AI) and machine learning (ML) technologies which together solve multi-dimensional, complex business problems and accelerate digital transformation through end-to-end process automation.
Bonus fact:
ARE YOU FAMILIAR WITH HYPERAUTOMATION?
Hyperautomation refers to the sophistication of automation and the application of multiple advanced technologies and tools to deliver increased AI-driven decision making. (Gartner)
THE CURRENT STATE OF INTELLIGENT AUTOMATION
$214 Billion worldwide will be generated by the automation industry in 2021
(Statista)
More than 30% of enterprises currently invest more than $50M in IA technologies
(KPMG)
84% of company representatives believe AI can bring competitive advantages in their industry
(Statista)
Nearly 133 million new jobs will be created by 2022, replacing over 75 million existing ones
(World Economic Forum)
CIOs will automate 10% of their IT tasks and look to upskill employees
(Forrester)
AUTOMATION
AI
(Artificial intelligence)
RPA
(Robotic Process
Automation)
INTELLIGENT AUTOMATION
(RPA software enhanced by AI algorithms and services)
Intelligent automation is changing the way businesses look at how they can make improvements and overcome business challenges. It is the intersection of multiple advanced technologies coming together, which allows organizations to layer tools to reach the pinnacle of operational efficiency, workforce productivity, and cost savings.
Reduce manual error to improve quality and accuracy
Automating quality testing using machine learning increases defect detection rates up to 90%.
(Forbes)
Prevent downtime and
maintenance
A single hour of downtime can cost manufacturers over $100,000.
Predictive maintenance can reduce rework and downtime, potentially saving up to $630 billion per year by 2025.
(McKinsey)
Increase business agility and velocity
Organizations piloting intelligent automation expect an average payback period of 15 months; those in the scaling phase report an average payback after just nine months.
(Deloitte)
Automate complex business operations—at scale
By 2024, organizations will lower operational costs by 30% by combining hyperautomation technologies with redesigned operational processes
(Gartner)
24% of businesses will deploy job process automation in order to reduce operating costs
(Willis Tower Watson)
By 2035, AI has the potential to boost labor productivity by 40%
(Gartner)
Business and/
or IT strategy
Integration with existing
IT systems
Data preparation, integration and/or cleansing
The ability to identify business opportunities for IA, estimate ROI, and bridge the gap between business and technology via an innovative consulting practice
State-of-the-art AI and ML expertise
The ability to validate innovative ideas in predictable and time efficient manner
A user-centric approach via design thinking methodology
SoftServe addresses challenges around intelligent automation
through:
Bottom-line benefit:
Banks can expect up to 25% of potential savings across IT operations, including infrastructure, maintenance, and development costs.
(Accenture)
Bottom-line benefit:
Intelligent automation is revolutionizing demand forecasting, supply chain planning and customer engagements.
(IBM)
Bottom-line benefit:
AI could enable a cut in global greenhouse gas emissions of between 1.5% and 4% by 2030, with its impact greatest in transport (up to 1.7%) and in energy (up to 2.2%)
(PWC)
Bottom-line benefit:
Studies show that unplanned downtime costs manufacturers $50 Billion annually, and asset failure is the cause of 42% of this unplanned downtime.
Bottom-line benefit:
The AI recommendation system that Netflix uses, for example, saves the company about $1 Billion each year. Additionally, 75% of what users watch on Netflix come from those recommendations.
(Netflix)
Bottom-line benefit:
Increase crop yields by 30% and predict weekly and seasonal crop yields with more than 90% accuracy using AI-powered equipment based on the computer vision.
The future is bright for enterprises that leverage AI and ML, and other advanced technologies, to reach the pinnacle of intelligent automation. Imagine your organization tackling multi-dimensional problems to operate quickly, efficiently and with higher impact—all at scale.
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For the Future