Digital transformation trends to watch in 2019 and beyond
Back in the day, making your product or service incrementally better and cheaper was a sure-fire formula for business success, but those days are over.
Intelligent automation (IA) is poised for explosive growth. In the past, IA was limited to the heavy lifting of very complex back-office processes such as financial processing in banks and provisioning of service on ginormous telecom networks. But the economics have changed with the rise of cloud computing.
With the astonishing evolution of artificial intelligence (AI), competitive advantage can vanish in a flash. Think about it. The average age of a company on the S&P 500 is down from 60 years in the 1950s to less than 20 years today, according to Credit Suisse.
Nearly half of the companies on the Fortune 500 have disappeared in the last 20 years. And 40% on the list today will disappear within the next 10 years. The question is, how do you get ahead of the relentless threat of disruption?
And, if you are able to do that, how can you stay there?
The most successful organisations see disruption coming. Then, pivot to turn it into opportunities for innovation and growth.
So, we researched what some of the biggest thinkers on the planet are predicting for digital trends for 2019 and beyond. Here’s a quick rundown of what we learned:
By 2019, 30% of large enterprises will start generating Data as a Service revenue because of AI
By 2019, over 40% of digital transformation initiatives will use AI services
By 2021, 75% of commercial enterprise apps will have AI built in, and over 50% of consumers will interact with AI
By 2020, personal digital assistants and bots will influence 10% of all sales
In the meantime, experts say that you can expect to see more and more AI and algorithms doing more than just retrieving information.
It turns out that AI is already playing a bigger role in our daily lives. For example, smart systems are making billions of decisions every day that affect many aspects of our lives.
They determine everything from who gets soap from a soap dispenser, to who makes parole, to who gets approved for a loan, to who gets hired or fired from a job and more. But experts warn against a move-fast-and-break-things approach to mainstreaming AI. They fear we’re not prioritising due diligence in the software development process.
Which is why ethics-minded AI experts like Joanna Bryson say it’s essential for us to understand how the AI makes decisions, how it determines what we see and what we don’t, and who’s accountable when it goes sideways.
“We should be able to prove that we can stand behind our software,” says Bryson, a computer scientist at the University of Bath in the United Kingdom. “And we should be held accountable for what our software does.”
It’s important to understand that AI is everywhere. And perhaps the biggest challenges we’ll face in the future are the political, economic and social consequences of not prioritizing due diligence with AI today.
“We made this huge leap between 2007 and 2017 in AI capabilities,” says Bryson, “because we had more data and we got better at machine learning. In the long term, I think that this will accelerate our rate of progress…So, now is the best time to figure out how to integrate AI into our lives.”
“I think it’s going to become increasingly hard to recognise that you’re working with technology,” says Morgan Frank, Researcher, MIT Media Lab and co-author of “Small Cities Face Greater Impact from Automation.”
“We’re (also) going to see more instances where data about us is being used without us knowing it, to drive conveniences that we expect,” says Frank. “Amazon Echo is a good example of that.”
Intelligent automation (IA) is also poised for explosive growth. In the past, IA was limited to the heavy lifting of very complex back-office processes such as financial processing in banks and provisioning of service on ginormous telecom networks. But the economics have changed with the rise of cloud computing.
IA is getting cheaper and easier to do. Which means companies will be using it to do a broad spectrum of work across the entire organisation. For example, many are leveraging IA to provide better, faster customer service. Others are adopting IA to gain more visibility into their sales channels, operating models, and day-to-day operations.
In other words, if you’re waiting for the IA hype cycle to subside. Or, if you’re slow-walking plans to scale up that IA pilot in one of your business units. Think again, because businesses that don’t embrace automation will eat the dust of those that do.
This is why many CXOs are pivoting away from the 10% cost save of yesterday’s offshoring to cash in on the 20 to 40% cost save of digital labour. And this trend will continue in 2019, according to the findings of Appian’s Future of Work Survey conducted by IDG. Here’s the math:
54% have or plan to deploy machine learning
75% have either deployed or plan to deploy IA in the next year
41% plan to implement IA in 2019
What it all comes down to is this. The rapid evolution of cloud, robotics, artificial intelligence and machine learning has put us on the cusp of exponential growth in intelligent automation in automotive, oil & gas, utilities, banking, financial services, and retail.
So, if you’re among the 40% of large organisations that are exploring IA. Or, if you’re among the 38% waiting to automate your operations in the first place, this is probably a good time to double down on your intelligent automation efforts.
Written by Siter Ali, Regional Vice President at Appian