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By Paul Myott, vice president of organizational effectiveness & internal communication
Managing Digital Transformation and the Leadership Required to Get There
What Is Digital Transformation?
The term “digital transformation” gets thrown around just about everywhere. It seems like an elixir that heals all operational bottlenecks. What exactly is digital transformation, though? How does it reshape the way businesses tackle their workflow challenges? And what roles do leadership and culture play?
According to The Enterprisers Project, digital transformation is the purposeful act of integrating technology into some or all business areas, remaking how that organization operates. The Oxford Languages Dictionary defines transformation as a thorough or dramatic change in form or appearance. It is easy to focus on the “digital” in these transformations because technology is the leading catalyst in these change events. Fully achieving digital transformation, however, requires not just a technological change but a leadership and cultural change where internal teams are empowered to challenge the status quo, experiment, and adapt to new ways of working.
The Benefits of Digital Transformation
The reasons for taking on digital transformation are many. Adopting technology for technology’s sake on a large scale rarely delivers the expected ROI and chasing “first adopter” status can be like catching a falling knife. There are several good reasons why enterprises digitally transform their business workflows. Here are a few that Forbes thinks should be considered:
- Keep Pace with Customer Expectations—Seamless customer interactions through their choice of web, mobile, call centers, and email are table stakes now. Integrating channels helps keep current customers and find new ones.
- Improve Efficiency—Automation of key business processes can reduce manual cycles and input errors and improve productivity by enabling employees to access data and collaborate efficiently in real-time from anywhere.
- Gain Competitive Advantages—Lower barriers to entry for artificial intelligence, big data, and the Internet of Things can make customer behavior insights, streamlined operations, and improved decision-making competitive differentiators.
- Reduce Costs—Automating manual tasks and workflows can improve productivity and reduce sales-to-revenue cycles. Adopting cloud technologies can also save on hardware.
- Enhance Security—Ever-evolving cyber security products like multifactor authentication, encryption, and network segmentation protect data from cyberattacks, and data breaches.
- Increase Agility—Widescale digitization enables quicker business cycles increasing the ability to adapt and pivot to evolving market conditions and customer needs. Businesses slow to adapt will require exponentially more effort to gain market share over first adopters.
To achieve these benefits and set a company apart as a high-performing digital business, leaders must become “bridge builders.” They must build the connections between business strategy, people and culture, and technology. Adapting the organization’s leadership style and mindset is half the battle. To apply an old adage to this scenario, “as leadership goes, so goes the people.”
The Key Hallmarks of Digital Transformation
Digital transformation is a marathon, not a sprint. Once the starting gun is fired, there must be a sound business strategy and a committed leadership team behind the program. From there, several factors come into play depending on the size and scope. Dreamix points out that 20 companies that achieved successful digital transformation in 2024 had several hallmarks in common. Here are some of the key attributes to strive for:
- Leadership Inspiration—Leaders must inspire their teams to embrace the change and give the new way of working a chance. As users encounter bumps in the road, it’s paramount to keep pushing for adoption.
- Technology-Driven—Successful digital transformations leverage advanced technologies—such as cloud computing, AI, and automation. This allows them to achieve agility, scalability, and speed in adapting to market demands.
- Data-Driven Decision-Making—Used correctly, data serves as a foundation for decision-making processes. Effective companies use analytics to guide strategy, improve customer experience, and enhance operational efficiency.
- Customer-Centric—Leaders in digital transformation keep customers at the center of their business model and decision-making. They use insights from data and feedback to continuously innovate and improve user experiences.
- Innovation Culture—By deploying digital processes, leadership teams can foster continuous learning and an innovation-friendly culture. They provide the tools that give people the agility to collaborate and create easily.
- Robust Security and Compliance—A strong security posture and adherence to regulatory standards in protecting sensitive data ensures business continuity. They also enhance your brand reputation as a company that cares about its customers and employees.
- Flexible IT Infrastructure—A reliable and scalable IT infrastructure (including cloud and hybrid environments, colocation partners, and on-prem data centers) enables a company to meet customer demands and innovate effectively.
As you strive to achieve digital transformation, it is critical for leadership to assemble teams with diverse viewpoints and expertise. Diversity of thought and experience sparks innovation and creates an environment where employees feel valued. Transformational leadership can shift the culture from top-down decision-making toward an environment of continuous improvement, empowerment, and inclusive thinking. These are the essential elements needed for sustained growth and resilience.
Assess Your Organization Today
Digital innovation challenges traditional practices and requires companies to respond swiftly and adapt quickly to shifting consumer demands and technological developments. Today’s business environment makes digital capabilities the difference between thriving and surviving.
Successful digital companies don’t just utilize digital tools; they embrace a holistic digital culture in all areas of operations. These organizations take advantage of data-driven insights, encourage innovation, and foster agile teams capable of adapting quickly to ever-evolving customer requirements.
DataBank encourages you to assess your organization’s digital strategies against the hallmarks. If you would like to talk with one of our IT infrastructure experts to learn more about how we can strengthen your digital transformation approach, contact DataBank today.
CHALLENGE: The Need for Scalable Power and Cooling
NJIT required an HPC solution capable of supporting dense racks at 30kW, with scalability up to 120kW, far exceeding the capabilities of their on-premises infrastructure. Traditional approaches, such as half-empty racks, were not cost-effective and added complexity. NJIT needed a partner who understood the unique demands of higher education and HPC.
DATABANK SOLUTION: DataBank’s Tailored Colocation Infrastructure
DataBank’s colocation facility at EWR2 in New Jersey offered NJIT a future-proof solution. With its ability to deliver up to 85kW per cabinet and reserve power for future growth, our facility met NJIT’s needs for both today and tomorrow. Our expertise in supporting HPC clusters for universities like Georgia Tech and the University of Maryland further assured NJIT of our capabilities.
Through close collaboration, we provided customized designs, installing a liquid to the rear door solution to meet NJIT’s requirements. DataBank managed the entire infrastructure installation for this project, inclusive of the secured cage, secondary water loop, rear-doors, overhead conveyance, and power. This partnership allowed NJIT to deploy its HPC cluster, Wulver, featuring 127 compute nodes, cutting-edge NVIDIA GPUs, and peak performance exceeding 1.5 PFLOPs.
RESULTS: A Gold Standard for Higher-Ed HPC
With DataBank managing power and cooling, NJIT can focus on driving $160 million in annual research activity. By leveraging our scalable infrastructure, NJIT avoided the $60 million cost of building a new facility and accelerated deployment timelines. Today, their HPC environment operates at full capacity, supporting innovative research and positioning NJIT as a leader in technological advancements.
This case reinforces DataBank’s role as a trusted partner in delivering reliable, scalable, and innovative colocation solutions for higher education institutions. Together, we empower institutions like NJIT to achieve their ambitious research and education goals.
In all the hype behind AI today, the term, “AI-powered” has become synonymous with efficiency, innovation, and advanced capabilities. From chatbots to recommendation engines, so many apps in are now claiming to be based on AI as a key selling point. However, as more companies jump on the AI bandwagon, it’s becoming difficult for users to distinguish between apps that genuinely use AI technologies and those that use the term for appeal, whether or not it’s true.
At the heart of the challenge: Not all apps claiming to be AI-driven deliver on this implied promise. While some may rely on basic automation or simple rules-based algorithms, they may not use the advanced machine learning or deep learning models that define real AI. This mislabeling not only misleads potential customers, but it also undermines trust in the market. As users become more skeptical related to their AI apps, they wonder if they really can deliver claims of value.
How can you tell if an app is AI-powered or just using the right buzzwords? Let’s look at key indicators when evaluating whether an app is AI-powered – or looking to capitalize on the hype.
Why Does it Matter Whether or Not an App is AI-Powered?
Understanding whether an app is genuinely AI-powered matters because it directly impacts the user experience and the app’s value. True AI-driven apps can offer features like personalization, predictive analytics, and intelligent automation that go far beyond simple rules-based systems.
For example, an AI-powered recommendation engine in an ecommerce app can analyze a user’s behavior in real time to suggest products that they’re more likely to buy. When successful, such an app helps to increase customer satisfaction and engagement. Yet, if an app claims to have AI but only uses basic pre-programmed logic, it may fail to meet those expectations and contribute to frustration.
For businesses
The difference between authentic AI and a misleading label can be significant. Investing in AI-driven technology generally comes with the expectation of improved efficiency, better decision-making, and new competitive advantages. However, if companies invest in apps that falsely market themselves as AI-driven, they may fail to realize these benefits and they may not see the full anticipated returns on their investment.
For Consumers
Consumers also have a stake in this issue. As data privacy and ethical concerns become more prevalent, users want transparency in how apps function, especially when it comes to AI. If an app claims to use AI to make decisions – such as financial recommendations, health assessments, or even content ideas – users need to be able to trust that those decisions were made on powerful, adaptive models instead of simplistic algorithms. Misleading claims can erode consumers trust, making it hard for companies to maintain loyal customers in the long run.
How to Tell if an App Is Truly AI-Powered
With so many apps claiming to leverage artificial intelligence, it’s essential to know how to separate real AI-driven solutions from those simply using the term as a buzzword.
Here are some signs to help you determine whether an app genuinely uses AI:
- Adaptive learning: True AI-powered apps continuously learn from data over time to improve their performance. For example, a virtual assistant should get better at understanding your commands the more you use it. If an app’s responses or recommendations don’t evolve based on your interactions, it may not be using authentic AI.
- Data-driven personalization: Apps that leverage AI can offer highly personalized experiences based on user behavior and preferences. Think of streaming services that accurately recommend shows or music based on your past viewing or listening habits. If recommendations feel generic or static, it’s likely driven by pre-set rules rather than machine learning.
- Natural language processing (NLP): AI-powered apps can understand and respond to human language in a way that feels intuitive. Look for apps that can accurately interpret context, tone, or intent in written or spoken inputs. If an app struggles with understanding nuanced language or complex questions, it might not have genuine NLP capabilities.
- Predictive analytics: Apps that use AI can forecast future trends or outcomes by analyzing historical data. For instance, a fitness app might predict your optimal workout routine based on past activity patterns. If predictions seem overly simplistic or random, it’s a sign the app might not be leveraging AI.
- Transparent AI claims: Companies that use true AI are often transparent about the technology powering their apps. Look for documentation, case studies, or other explanations on how their AI models work. If an app claims to be AI-driven but offers little explanation of the underlying technology, it’s worth being skeptical.
By evaluating apps using these criteria, you can better understand whether they genuinely harness AI technology or are simply riding the wave of AI hype.