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Why it matters: IT leaders seeking to democratize technology with low code citizen developer projects may not realize low code platforms still require application development skills.
The big picture: Regardless of required development effort, building more apps for workers to contend with increases complexity and builds technical debt.
Hyper Intelligent Automation (HIA) was verily the flavor of 2021 and going ahead into 2022 and beyond it’s set to stamp its importance in more ways than one. The growing clout of “Intelligent Automation” is buttressed by the fact that a recent Zinnov Zones report on Hyper Intelligent Automation (HIA) shows the segment will grow at a rate of 50-55% year-on-year to cross USD 18Bn by 2026 from the existing USD 2.4 Bn. The deal ecosystem has seen a steady rise in demand for HIA and 30-35% of the overall HIA deals are over USD 500K in size.
This trend underlines a fundamental shift of large enterprises who are no longer looking at automation focusing only on efficiency and cost savings but at outcomes around enhanced stakeholder experience and business resilience.
Natural Language Processing (NLP) or Natural Language Understanding (NLU) is a subset of Artificial Intelligence (AI). There are many benefits when using the technology, and I am surprised at the pushback from technical people when talking about deploying it. I guess there is a difference between learning about technology in academia and the complexity of actually deploying it.
So, how do we get past all the pushback when chatbots are having conversations and intelligent automation promises to be better than old-school EAI and SOA?
The year 2020 was a watershed moment for automation. The challenges posed by the global pandemic – in which many businesses had to move operations remotely, nearly overnight – forced CIOs to turbocharge digital transformation and start executing on their 2025 digital transformation strategies – five years earlier than many had planned.
A May 2020 report from Forrester Research asserted that the pandemic resulted in a shift in "automation psychology" that will spark an 18- to-24-month period of rapidly accelerating automation.
The technology that enables us to extract information from scanned images of printed or handwritten documents is called Optical Character Recognition or OCR. It has applications for the processing of business contracts, receipts, utility bills, passports, product sheets, handwritten forms, bank statements, and a variety of PDF documents generated by businesses.
Accurate and reliable data extraction plays an important role in finance, accounting, electronic health record updates, insurance claims processing, personal and national security, logistics documentation, and legal documentation. The extraction accuracy is extremely important because OCR is often used to convert documents such as passports, invoices, or receipts, where every bit of information is vital and errors can prove costly.
The amount of data is increasing rapidly. More and more devices can produce and transmit data. We live in a world that threatens to drown in the flood of data. The merger of 5G, IoT, and AI could help us and be of great importance when it comes to profiting from the rapid increase in available data.
The Fusion of 5G, AI, and IoT will play a significant role in critical areas like:
2019 marked the year we crossed the tipping point for robotic process automation (RPA) adoption. A recent report from Futurum Research — commissioned by Automation Anywhere — discovered that more than half of North American businesses today have adopted intelligent automation.
These findings show that RPA is no longer an emerging technology but rather a mission-critical component for businesses, driving immense value due to its ability to automate labor-intensive tasks so that humans can refocus their efforts to work that drives impact and satisfaction.
Fuzzy logic has quietly arrived in our day-to-day lives. Take, for example, rice cookers.
Unlike regular rice cookers, which are either on or off, a fuzzy logic enabled rice cooker can consider the type of rice, room temperature, and other factors to determine the optimal temperature and time for cooking.
The global workforce has transitioned to a mobile workforce. The number of mobile workers will grow to 1.9 billion by 2022, which will make up 43 percent of the total workforce [1]. This mobile workforce growth influences enterprise mobility needs.
As far as office automation is concerned, business users need the ability to orchestrate and supervise their digital workforce from anywhere. At Automation Anywhere, we offer a Robotic Process Automation (RPA) mobile app to access your live RPA dashboard securely. Users now can start, pause, and stop attended RPA bots from the app, monitor ROI and performance data, or receive automation alerts.
Artificial intelligence isn’t just for driving the cars of the future, trading stocks in nanoseconds, or pushing the bounds of scientific discovery. It’s also ready for the office.
But the office hasn’t realized that yet. About 80 to 90 percent of organizations still manually extract data from documents and emails.
It could be said that the technological developments in all industries contribute to compounding developments in the future.
That is to say, better technology today makes it a little easier to harness better technologies tomorrow. Smarter algorithms, more robust hardware, and more capable programs all make it easier to find technologies of the future, effectively quickening technological growth with each discovery. Each and every discovery can work with others to offer new possibilities. 
Over the past few years, we have seen tremendous advances in machine learning (ML) and artificial intelligence (AI). Rooted in these inspiring technologies is the idea of robotic process automation (RPA), the possibility of automating routine and mundane tasks with software robots capable of interacting with traditional software systems in the same way as human operators would.
Enterprise executives are attracted by the numerous benefits of RPA, which include significant cost savings and productivity improvements, but they are often left wondering how to best adopt RPA to drive long-term growth.