While some may find the term ambiguous or overused, digital transformation has become a strategic imperative. The reason? Tangible impact. Consider the money transfer service that achieved triple-digit transaction growth in a year, or the energy company that met industry benchmark goals twenty times faster, saving $60 million annually through AI-driven data utilization.
These examples illustrate that digital transformation is more accessible than ever, regardless of where your company stands on its journey. This article explores key aspects of digital transformation, examines a real-world success story, and discusses how AI can further enhance progress.
Want Your Digital Transformation to Succeed? Focus on 6 Essentials
Successful digital transformation hinges on several critical factors. Here are six essentials to consider:1
1. A clear strategy with real business value
Zoom in on specific areas like a key customer journey or a high-impact process. Identify areas that drive real value. With a clear roadmap, your team can prioritize the right changes and deliver measurable results.
Analog Devices Inc., for example, identified pain points in the customer journey by gathering feedback from field teams and surveying nearly 5,000 customers. This informed a strategy focused on providing seamless, personalized, and self-service interactions.2
2. Digital talent that works shoulder to shoulder with the business
The best transformations recruit—or train— teams of engineers, designers, and analysts working side by side with business leaders. You can also engage with partners that enable and enhance your transformative vision.
Levi's did it through a machine learning bootcamp that upskilled employees in coding, machine learning, and product management. The initiative resulted in 40 employees, including non-tech staff, applying their new skills in current roles or joining the strategy and AI team.3
3. An operating model built to scale
Don’t be afraid to rethink your operating model. For example, many companies choose to merge their digital programs and their traditional IT delivery into a single model.
A McKinsey survey revealed that companies with integrated or fully digital technology operating models are less than half as likely to encounter issues integrating new digital efforts with core architecture. And these companies are 60% more likely to report that their technology investments create business value.4
4. Tech that empowers teams to move fast and independently
Distributed technology lets every team tap into the tools, data, and services they need to build, test, and launch new ideas. APIs, cloud tools, and automated infrastructure help create an innovation-friendly environment.
Toyota implemented an AI platform using Google Cloud's AI infrastructure, enabling factory workers to develop and deploy machine learning models. This initiative led to a reduction of over 10,000 man-hours per year.5
5. Easy access to usable, reliable data
Be sure to give your teams clean, current, and accessible data. That means investing in strong data architecture, proper governance, and reusable “data products” that make it easy to plug the right information into the right solutions.
Meanwhile, poor data quality destroys business value. Gartner research revealed that organizations blame poor data quality to be responsible for an average of $15 million per year in losses.6
6. A serious approach to adoption and change
Change management starts before launch, and it’s mostly human. Think of it this way: for every dollar you spend building a new solution, plan to spend another dollar on training, communication, and process changes.
Research indicates that just over a third of major change initiatives achieve clear success, and 50% result in failure.7 This highlights the importance of comprehensive change management strategies.
From Walk-In to Digital First: How MoneyGram Put the 6 Essentials to Work
MoneyGram’s transformation is a prime example of how to apply the six essentials of digital transformation. As the world’s second-largest money transfer service, the company faced an urgent challenge: modernize a legacy system shaped by in-person interactions and bring that experience to the mobile-first world. With customer expectations rising—thanks to apps like Venmo—MoneyGram needed to evolve beyond the traditional walk-in model without disrupting operations across 45 localized websites, 200+ countries, and a network of 347,000 agents.
Here’s how MoneyGram did it:
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Clear strategy with business value: The goal was focused and measurable—migrate loyal users to mobile while preserving the personal trust built over decades of in-person service.
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Digital talent working with the business: Partnering with digital agency Bottle Rocket, MoneyGram brought together product teams, designers, and engineers to co-develop a seamless customer experience.
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Scalable operating model: Rather than silo the mobile app as a one-off project, MoneyGram built an integrated content management system (CMS) that enabled real-time personalization and localization at scale. This demonstrates a unified operating model across tech and business.
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Empowering tech for speed and agility: The CMS allowed marketing and product teams to push localized updates across regions instantly, while the mobile app architecture supported fast iteration and deployment.
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Reliable, usable data: Insights from user behavior shaped the experience design, guiding everything from onboarding flow to feature prioritization—showing the power of clean, actionable data to drive decisions.
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Serious approach to change management: Migration from web to app wasn’t left to chance. The rollout included thoughtful user education, design that mirrored the in-store experience, and backend resilience to support adoption in even low-connectivity regions.
The results of this coordinated effort were compelling: customer retention among app users rose 48% above in-store rates, monthly transactions grew 34%, app usage soared by 202% year-over-year, and digital transactions more than doubled.
To begin, it's important to assess the company's overall organizational and technological capabilities. From there, strategies can be developed to enhance the customer experience, increase revenue, and reduce unit costs. When done effectively, digital transformation leads to a competitive advantage that is measurable, sustainable, and continually evolving.
Next Steps: AI Builds on a Strong Digital Foundation
The next chapter of digital transformation is unfolding through generative AI—not as a standalone innovation, but as a force multiplier for companies that already have the right foundations in place. When organizations pair AI with a clear strategic focus, embedded digital talent, scalable operations, and clean, accessible data, the results compound.
For example, for companies like MoneyGram, AI-powered assistants that speak every customer’s language, systems that generate localized content in seconds, and tools that surface compliance risks or fraud patterns in real time aren’t just technical wins—they’re strategic differentiators.
Continuous Transformation Starts Now
Digital transformation isn’t a destination, it’s a mindset. Real change happens when strategy, talent, and technology come together with a clear purpose and customer focus. But even after achieving strong results, transformation never ends. Generative AI is already reshaping how businesses operate, engage, and grow.
Whether you're just starting or looking to accelerate, the path forward is clear: build the right foundation, stay adaptable, and keep evolving. The future of digital transformation is already here. What matters now is how you choose to lead it.
Endnotes:
1 McKinsey & Co., What is digital transformation?, August 7, 2024.
2 Deloitte and The Wall Street Journal, Transform and Perform: Analog Devices Retools Customer Journey, March 19, 2024.
3 McDowell, M., Exclusive: Lessons from Levi’s data science bootcamp, Vogue Business, Nov., 8, 2021.
4 McKinsey & Co., Products and Platforms: Is Your Technology Operating Model Ready?, McKinsey Digital, Feb. 2020.
5 Google Cloud, 601 Real-World Generative AI Use Cases from Industry Leaders, updated April 9, 2025.
6 Gartner, How to Create a Business Case for Data Quality Improvement, June 19, 2018
7 CEB Corporate Leadership Council, Making Change Management Work, 2016