Automation has been used to a certain extent for decades across all industries to maximize efficiency, reduce costs and improve services and solutions. However, within the last few years, intelligent automation has grabbed the attention and interest of the business world.
Intelligent automation definition
Intelligent automation (IA) is different from other forms of automation, in that it’s a combination of artificial intelligence and automation and is changing the way organizations function in almost every sector.
This growing technology is making big waves and has the potential to make the most significant impact on the way organizations operate since the internet was first introduced.
Organizations are using IA to produce and process a vast amount of data, automate end-to-end operations and make tasks faster and more efficient.
Most importantly, IA can automatically analyze situations and proactively correct errors in a way that is very similar to how the human workforce functions, but is faster and more precise. This was not possible prior to intelligent automation.
Disruptive technologies bring about paradigm shifts in the way organizations function and how the human workforce carries out various business activities.
The sole purpose behind using these new technologies is not just to enhance efficiency, but to go beyond traditional boundaries of maximizing productivity and profitability. This is exactly what IA is doing in the business world at a global scale.
IA is helping companies infuse three key elements into their operations: agility, responsiveness and frugality.
It is enabling organizations to better adapt to fast-changing situations, especially amidst the current global pandemic. IA is being utilized by businesses of all sizes, primarily because of its low cost of adoption.
Additionally, it allows companies the ability to significantly cut costs, while increasing output at the same time. This is a gamechanger for many businesses in terms of competitive advantage and the ability to remain profitable in an ever-changing economy.
IA is also proving to be a more affordable alternative to leveraging outsourced labor, as keeping processes in-house provides greater security and control.
The most popular IA technologies include robotic process automation (RPA), virtual agents (VA), and artificial intelligence (AI).
- RPA is being used for a host of repetitive and mundane tasks because it not only speeds up processes, but also does so with almost no errors. Furthermore, RPA allows for considerable cost savings as compared to using a manual human resource. The benefits of RPA are making organizations rethink their human resource requirements and business process outsourcing needs.
- Many organizations are turning to VAs, instead of physical support centers, as they offer numerous benefits like 24×7 availability as well as the ability to handle larger call volumes and queries in multiple languages. Organizations no longer need to worry about opening location-specific customer service centers and hiring local talent to manage customers speaking local languages. Using VAs removes concerns around process, geography, time zones and language, not to mention the output and cost-savings are tremendous.
- Similarly, more complex behavioral analytics and other data analytics can be performed using AI easily. Gathering, processing and analyzing data manually would not only be slow and ineffective, but also wouldn’t deliver the same outcomes made possible by using AI, as it can be used from anywhere, anytime.
Using these transforming IA technologies, businesses are experiencing multiple benefits, such as:
- Serving global clients from one location
- One operational model and one point of contact
- Shared technology infrastructure and platforms
- One process owner
Furthermore, it opens up a world of opportunities, where organizations can evolve at an incredible speed and workforces can learn new skills to perform modern-day business operations in more efficient and optimized ways.
Change is never easy and comes with its own uncertainties and challenges.
Some of the most common challenges of IA technology adoption include:
- Lack of a concrete strategy for adopting new technology
It is often difficult to create a strategy for adopting new technology. For the best results, it is imperative to determine the current state of your business and what your starting point is.
There are also certain strategic considerations that need to be discussed early on, like deciding on the scale of automation (small pilot projects or enterprise-wide adoption) and formulating governance structure and the decision-making processes.
- Calculating ROI
Set realistic expectations by mounting your analysis beyond reducing headcount and understanding that initial ROI figures are simply educated estimates.
You will be able to arrive at a much close figure after your first proof-of-concept use case. Post proof-of-concept continue to measure ROI at regular intervals over time to determine whether to scale intelligent automation up or down.
- Lack of Talent
When adopting new technology, finding the right talent can be challenging at times.
This not only includes identifying teams with the technical skills, but overall understanding of your business processes, and change management expertise to guide your company to the future.
- Correct selection of use case
Choosing the right use case and deciding which data set is most critical for developing organizational capacity can be challenging as well. Deciding how best to deploy IA, and which processes will yield the most return, is critical to success.
Start small and build a library of processes to automate as you progress.
- Selecting the right vendor
Choosing the right vendor(s) to begin your process automation journey can be a challenging chore, as all vendors have the same core talking points. It can be difficult to choose a vendor based solely on the differences or benefits of their offerings and is often not enough to base a business decision on.
Work with a consulting partner to help guide the process of selecting vendors to ensure the best fit for your organization’s unique needs.
- Managing change management
In the absence of a change management plan, bringing on such a technology change could cause resistance among the staff. Make sure to explain and highlight the benefits of switching to new advanced technology for everyone in the organization in layman’s terms rather than technical jargon.
IA enables organizations to effectively manage and optimize operational costs. Technologies such as RPA, AI, natural language processing (NLP) and natural language generation (NLG) can automate up to 25–50 percent of business processes.
This helps organizations achieve better outcomes at lower costs, while also freeing up human resources for more strategic and higher value work.
These enhanced capabilities empower organizations to rewrite the rules of the game within their own domain.
It helps them occupy a place of sustainable prominence in the revamped competitive landscape – where processes become more efficient, leaner and more cost effective, while also alleviating dependency on human workforces, addressing the skill gap and allowing customers to feel more engaged.
IA and advanced automation are changing the business landscape at an unprecedented speed.
These shifts are the driving force behind today’s organizational digital transformations and are going to impact how organizations deliver their services and solutions in the future.
Business leaders should assess these opportunities, build use cases and start pilot projects using IA to take advantage of major organization-wide improvements that will propel their business into the future.