“Successful digital transformation is like a caterpillar turning into a butterfly. It’s still the same organism, but it now has superpowers.”

George Westerman, principal research scientist at the MIT Initiative on the Digital Economy, first used the now popular analogy two years ago to explain the changes businesses were going through. But, over the last few years we haven’t seen many butterflies and that is because companies still have the mindset of caterpillars. “It’s hard to keep up with your competitors if you’re crawling ahead while they can fly,” according to Westerman’s analogy. 

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Digital transformation is just another means to compete in the marketplace. It can be viewed as an overhaul to how the business operates, but the perceived outcomes of a digital transformation is what makes it desirable. According to a recent report from SnapLogic, 98 percent of IT decision-makers are committed to digital transformation because they want to increase revenue, market share, and business speed; reduce operating costs and development time; and improve customer satisfaction. 

However, the expectations may be too high. The report goes on to reveal that 40 percent of enterprises are behind schedule when it comes to meeting their expectations. Additionally, 69 percent are re-evaluating their digital transformation strategy and 59 percent would do it differently if they had the chance. 

This unexpected slowdown is causing enterprises to find new ways to get back on track. The report also found 68 percent of respondents are turning to artificial intelligence or machine learning to help speed up digital transformation. 

“Digital transformation doesn’t happen overnight, and there’s no silver bullet for success. To succeed with digital transformation, organizations must first take the time to get the right strategy and plans in place, appoint senior-level leadership and ensure the whole of the organization is on-board and understands their respective roles, and embrace smart technology. In particular, enterprises must identify where they can put new AI or machine learning technologies to work; if done right, this will be a powerful accelerant to their digital transformation success,” said Gaurav Dhillon, CEO of iPaaS enterprise solution provider SnapLogic, an integration platform-as-a-service provider.

One way AI is being used to drive the digital transformation is to sort through the mounds of data coming in from all areas of the business and provide insights into that data in real time. 

“The sheer amount of data collected every day isn’t usable as an effective tool unless it’s in real-time,” said John McDonald, CEO of digital transformation company ClearObject.

“There is simply too much data to ingest and analyze. So, training machine learning models to efficiently analyze the data and provide predictive and prescriptive solutions is vital to organizations who want to remain competitive in their industries.” 

For example, the self-driving car industry needs to use machine learning to access and analyze data on the fly and make changes that allow the car to maneuver, brake or stop at any given moment. A trucking company can use machine learning to monitor engine performance in real time and be alerted to any issues that may cause them to have to shift plans around, McDonald explained. 

“Machine learning will continue to advance alongside the ever-expanding digital transformation because they go hand-in-hand in order to be truly effective for data analysis,” he said. 

Within development teams, machine learning is being used for predictive maintenance, quality and customer sentiment analysis. According to Kevin Surace, CEO of the AI-driven software testing provider Appvance, machine learning algorithms can study patterns on a network and learn from its behaviors. When something outside the set of natural behaviors happens, it can alert the proper teams. It can also indicate where or if there are things that are out of tolerance, things that are taking too long, and predict whether or not there will be anomalies in the finished product and insert fixes, McDonald added.  

For customer sentiment analysis, machine learning algorithms take in data points and infer how customers might behave based on those data points in order to better serve customers and improve the odds of making a sale. 

AI can also be used to help a business be more digital in general. For instance, if a business still operates with paper documents for things like audits, contracts and even lawsuits, it can result in slow, manual and mundane tasks, a recent report from Conga revealed. 

“Not only is [digital transformation] fundamentally changing how we do things, but it is also changing customer expectations of how we will interact. These rising customer expectations matter more than ever, since the new, connected economy makes it easier to take one’s business elsewhere,” the report stated. 

Here, AI is being used to automate the manual document process and analyze the data within the document to provide more insight and help businesses and customers make smarter decisions. 

“Digital transformation is at the heart of every company’s move to a better bottom-line today,” said Surace. “ ‘Every company is a software company’ as you may have heard, and that really means that’s where the new profits must come from, that is, the productivity from letting your software systems drive bottom line.”

Automating your way through your digital transformation
At the end of last year, research firm Forrester predicted that digital transformation would become more pragmatic in 2019. The organization found that 2018 was full of failure with 50 percent of digital transformation efforts stalling due to the challenging and costly changes businesses need to overcome. With more understanding and organizational readiness in 2019, Forrester envisioned more tangible efforts such as launching digital products, monetizing data assets and lower-cost digital channels. 

“Digital transformation is not just about technology. It’s the necessary but challenging journey of operating digital-first with the speed and nimbleness to change rapidly, exploit technology to create lean operations, and free people to do more complex tasks,” Forrester explained in a post

Now that we are more than halfway through the year, the organization is seeing just how businesses are taking a pragmatic approach to their digital efforts, and it involves a shift in the conversation. According to Forrester principal analyst Craig Le Clair, instead of digital transformation, businesses are talking about automation. “Along comes this notion of doing rapid digitization through automation,” or robotic process automation (RPA), he explained. RPA is the automation of manual tasks. The reason why more organizations are turning to this trend is because it is a better entry point or “alternative” for digital transformation. 

“The ability to integrate legacy systems is the key driver for RPA projects. By using this technology, organizations can quickly accelerate their digital transformation initiatives, while unlocking the value associated with past technology investments,” said Fabrizio Biscotti, research vice president at Gartner.

Along their journeys, companies are figuring out that digital transformation requires big structural and operational changes that they are not ready for or struggling to obtain. With RPA, businesses can start to use it in their existing UIs and legacy systems without having to change a whole lot and begin to move to a more modern way of working that can continue to be evolved as time goes on. “All of a sudden you have a digital process without touching those systems because you are operating against the applications that exist on the desktop,” said Le Clair.  

Appvance’s Surace added that RPA is coming into play because of its ability to automate repetitive tasks that can then be used later to help the system learn and do more. 

Le Clair went on to explain that RPA is already being widely used in finance and accounting departments where a lot of repetitive tasks like cutting and pasting spreadsheet fields is occupying a lot of a person’s time. “A bot can come in and do the same repetitive task in a fraction of the time,” he explained. 

To take RPA even further, businesses are starting to apply machine learning and AI to make the repetitive tasks a little more intelligent. Le Clair explained conversational intelligence can be added to bots in order to interact with customers, understand human intent and perform an action. 

Another area AI can help RPA is dealing with unstructured content. RPA can only deal with structured or tagged fields, so if you put a layer of text analytics or machine learning on top to be able to decipher data, RPA bots can take actions based on that data, according to Le Clair. 

“In the end, the application of machine learning in the coming years will be a centerpiece of digital transformation. At every company. Because we have decades of data and knowledge which can be learned from, every company can benefit and drive far better productivity,” said Appvance’s Surace.

The changing workforce
All of these new ways of automating manual tasks and helping remove bottlenecks worries some in the industry that AI and machine learning will take over jobs. According to Forrester’s Le Clair, it is a real fear. “The robots that are going to restructure the workforce are the ones you can’t see. The invisible robots,” he said. 

These “invisible robots” are in the form of virtual agent software, RPA, bots and machine learning, and while they won’t impact all jobs initially, they will slowly begin to replace some, Le Clair explained. 

However, ClearObject’s McDonald explained that it isn’t something to panic about because that  “has been the entire point of technology since the beginning of technology. What is different about machine learning is the rate, not the dynamic that it is happening.”

For instance, when cavemen created fire, they didn’t stop figuring things out. It freed them from figuring out how to heat their food, caves or homes and stay alive in the winter so they could turn their concern and focus to other things, McDonald explained. It’s not about whether AI is going to replace some jobs; it is about redesigning the education system to train and retrain people for other job roles, he explained. 

“We have an education system that was designed to teach you what you need to know for a career that at the time it was expected to be what you would do for life. That is not the case anymore in a society where technology is rapidly taking over a lot of those jobs. You are going to need to be retrained for different jobs multiple times in your life,” he said. “The speed and lack of a system to retrain people multiple times throughout their life is actually the root of the problem and the fear that people have. Not that technology takes away jobs because it always has. It is, ‘What am I going to do because there isn’t an education system to help me or relieve me of that pressure, pain or concern.’ ”

However, Forrester’s Le Clair doesn’t believe that the traditional education system will be able to help prepare workers and companies for the different processes and programs they will work with in the future. Instead, he stated more education and certification needs to come from the private sector itself.