From AI to automation: Real-world success stories of digital transformation

Technology success stories with business outcomes are popular for a good reason. They’re interesting. They’re inspiring. And perhaps most importantly, they’re instructive.

Over my decades-long journey from data architect to executive, I’ve heard and contributed to plenty of success stories. From AI and cloud computing to microservices and automation, I've seen firsthand how various technologies can drive tremendous progress on companies’ objectives and act as powerful levers toward greater innovation.

Every week, I hear new stories of how organizations leverage technology to drive these efforts and further their business objectives. Technology has completely reshaped the business trajectory for numerous companies, speeding up product launches, informing competitive analysis, and supporting stalwart objectives like increasing productivity.

Here are three stories of how organizations use technology to drive their transformation. They inspire me, and I hope they inspire you, too.

Driving digital transformation

From the beginning of digital transformation around 2007 to now, organizations have sought ways to be more agile and mobile. Moving to the cloud has been a major part of many organizations’ journeys toward these objectives.

Success tastes all the sweeter when overcoming a major business challenge. A leading provider of automated testing equipment struggled with a common one – embracing digital transformation despite its aging IT infrastructure. With a tangle of more than 190 applications, each with complex dependencies, this organization urgently sought a complete overhaul and digital transformation.

The testing equipment provider also needed a total assessment of how to transform its entire infrastructure. Moving applications to the cloud and going from a monolithic system to a dynamic one based on microservices is a key step in transformation. This involved developing a phased approach to migrating and modernizing apps and readying them for a cloud-native environment. Quite an undertaking, but one the company anticipates is already paying dividends by lowering the total cost of ownership and speeding up the time to market.

Automating workflows for greater agility

Agility is a much-sought business objective. While traditional AI has helped automate business processes for years, generative AI makes workflow automation even faster and simpler. If a process that previously took six months now takes three, that will speed transformation to an extraordinary degree.

Digital transformation often involves modernizing your app code. AI capabilities like code generators, automated repo builds and automated testing can make huge agility gains a reality, significantly cutting down on development and product assurance cycles. And the time will decrease the next time. That’s the power of AI as it “learns” from the data.

A success story related to automation that stands out to me is that of a U.S.-based Fortune 100 mortgage company. Its story represents a major leap from before to after because 95% of its product change management processes were manual before implementing a managed pipeline service framework.

Its highly controlled product change process made that agility blocker even more formidable, with multiple constituents managing a change control board. However, the same old process wouldn’t help the company release functionality to its customers more agilely.

By automating all its manual processes, the company increased productivity and collaboration, boosted employee engagement, saved $3 million a year that could be funneled back into innovating new features and realized a 93% reduction in build time – from four hours to just 17 minutes.

Propelling operational efficiency

In today’s business arena, operational efficiency is more crucial than ever. Companies are constantly seeking ways to streamline processes, reduce costs, and improve performance. Technology plays a vital role in achieving these goals, enabling organizations to optimize their operations and stay ahead of the competition.

A large U.S. financial services company illustrates the operational efficiency that can result from modernizing application architecture and development practices. With its core application built on a monolithic architecture, the company struggled with performance issues and delays in adding new app capabilities. This was critical since these apps were connected to its business growth.

To overcome lengthy development and deployment cycles and speed time to market, this company adopted a microservices architecture, continuous integration/continuous delivery pipeline and software development managed services. This client was thrilled by the results, including a 5x increase in speed-to-release for feature updates and a 4x improvement in application performance. Now, this company is far more efficient and ready for multi-cloud.

The tipping point of technological transformation

A tipping point always exists with successful technology. Consider the automobile, electricity, phones and the internet as notable examples. Their usage starts small and expands as people realize the revolutionary impact it provides. It’s a beautiful thing to witness, especially when you detect those first signs of that future flip to widespread use and popularity.

AI is at that tipping point; except it’s tipping at a much faster scale. It’s the difference between a biplane taking off and a spacecraft blasting off. The rapidly evolving pace of innovation is good news for business outcome-focused organizations. They’re realizing incredible outcomes like AI-driven operational efficiency. Implementing AI-driven data strategies can also contribute to maximizing business value.

Write your own technology success story

What business objectives does your organization prioritize? Whether its digital transformation, increased agility, process automation or something else, there's a technology solution that can help you achieve your goals. From AI and cloud computing to microservices and automation, the possibilities are vast. The key is Identifying the right technologies for your specific needs and knowing what considerations to weigh when implementing them.

I never tire of hearing these stories so if you have one, reach out and share it. And consider technology that can lead to a future success story. For AI inspiration, check out Harvard Business Review Analytic Services’ recent report on “Operationalizing Generative AI for Better Business Outcomes.” For other inspiration, learn more about Cloud Management solutions and Data solutions from Unisys.