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    The Role of Artificial Intelligence in Digital Transformation

    Business professional using a laptop with AI and lock, bar, graph and gear icons floating above it
    • 25 Sep 2024
    Kate Gibson Author Contributors
    tag
    • AI Essentials for Business
    • Digital Transformation

    As industries and customer expectations evolve, businesses face mounting pressure to leverage emerging technologies like artificial intelligence (AI) to innovate and avoid falling behind.

    Digital transformation is no longer optional—it’s essential. According to an International Data Corporation (IDC) report, 53 percent of organizations have enterprise-wide digital transformation strategies.

    Thriving in today’s fast-changing market requires evaluating your organization’s approach to operations, decision-making, and customer engagement to adapt to and seize on digital transformation opportunities.


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    What Is Digital Transformation?

    Digital transformation is adopting new technologies to reshape how your business operates and creates value. It involves:

    • Rethinking business models
    • Optimizing operations
    • Improving customer experiences

    It’s not simply driven by technology but rather by addressing inefficiencies, enhancing agility, and making data-driven decisions.

    In an HBR IdeaCast episode, Columbia Business School Professor Rita McGrath recommends a measured transformation approach.

    “Instead of launching it like a great big bang and running the risk of a huge failure, you take it more step by step,” McGrath says. “So it’s building up digital capability, but in a very step-by-step kind of way. And that allows the organization to much more readily absorb the change.”

    This is where AI is critical. By automating routine tasks, analyzing data, and driving innovation, it enables a gradual approach that builds competence while minimizing disruption.

    If you’re considering integrating AI into your company’s operations, here are four areas where it can drive digital transformation.

    Related: Leveraging AI in Business: 3 Real-World Examples

    4 AI Levers Driving Digital Model Transformation

    1. Strategy

    As you embrace digital transformation, AI becomes pivotal to reshaping business strategy. Unlike traditional strategies that rely on static data and human judgment, AI-driven ones continuously evolve by leveraging advanced technologies such as machine learning and data analytics.

    “When you have digital networks, AI, machine learning, all this kind of cool stuff around, your options for strategy really increase,” says Harvard Business School Professor Marco Iansiti, who co-teaches the online course AI Essentials for Business with HBS Professor Karim Lakhani. “And you can do strategy in a bunch of different ways.”

    For example, AI is core to Amazon’s business strategy and drives its digital transformation. By analyzing real-time data, Amazon anticipates stock shortages, reroutes deliveries, and improves shipping times.

    AI-driven strategies don't merely improve existing practices; they fundamentally transform them. With AI, you can adopt predictive analytics to anticipate customer needs, automate processes to reduce costs, and personalize services to enhance customer satisfaction.

    Netflix offers another example of AI-driven transformation. Using AI and machine-learning algorithms to analyze data—including viewing habits, ratings, and search queries—the streaming service generates personalized recommendations for users, transforming how they consume content. This allows Netflix to predict audience preferences, optimize its content library, and make data-driven investment decisions about shows and movies.

    Related: How to Develop a Business Strategy: 6 Steps

    2. Governance

    Strong data governance becomes more crucial as you integrate AI into your business because it provides the structures, policies, and processes to manage the risk advanced technologies pose.

    Without governance, your company can experience unintended consequences like:

    • Security vulnerabilities
    • Ethical missteps
    • Operational inefficiencies

    Governance is also critical to addressing ethical concerns around algorithmic bias—which occurs when AI systems are trained on prejudiced or unrepresentative data, leading to unfair outcomes. For example, a hiring algorithm trained on historical data could reflect biased hiring practices, such as favoring male candidates over equally qualified female candidates.

    Custom graphic showing 3 examples of algorithmic bias in business: discriminatory hiring, unequal access to resources, and workplace bias

    “We need to be sure that, in a world that's driven by algorithms, the algorithms are actually doing the right things,” Iansiti says in AI Essentials for Business. “They're doing the legal things. And they're doing the ethical things.”

    To mitigate algorithmic bias, build your AI systems with regularly audited, diverse data sets. Recruit a diverse team to participate in developing and reviewing those systems to further promote inclusivity and fairness.

    Additionally, governance facilitates accountability and oversight, ensuring digital initiatives align with your business’s overall strategy. It helps create clear lines of responsibility to monitor and measure digital transformation efforts effectively.

    By establishing benchmarks, reviewing performance, and continuously refining processes, governance enables you to stay agile and responsive in a rapidly evolving digital landscape.

    Related: 5 Ethical Considerations of AI in Business

    3. Architecture

    A robust digital infrastructure is also essential. Your organization’s systems, networks, and platforms should allow for the seamless integration of AI and other emerging technologies.

    “The plumbing—the architecture of the plumbing—is the architecture of the business,” Iansiti says in AI Essentials for Business. “And so, if you really want to take this digital operating model seriously, you've got to take these kinds of terms and these kinds of ideas seriously.”

    Without a well-structured architecture, AI integration can falter—limiting information flow, collaboration, and scalability.

    AI Essentials for Business | Compete in the age of AI | Learn More

    Creating an environment where AI technologies can thrive requires:

    • Cloud-based platforms
    • Scalable AI models
    • Interconnected systems that support data sharing

    For example, General Electric (GE) transformed its industrial operations by implementing cloud-based platforms across its machinery and sensors, creating a unified structure for real-time data analysis to predict equipment failures, optimize maintenance, and improve efficiency.

    You, too, can lay the groundwork for AI to drive innovation, streamline operations, and support sustained transformation by prioritizing a well-designed digital architecture.

    Related: AI-Driven Business Models: 4 Characteristics

    4. Culture

    Beyond technology and infrastructure, digital transformation heavily relies on organizational culture. Not every organization has the culture to support digital transformation. Many struggle with outdated communication methods and departmental silos, which slow the adoption of new technologies.

    AI can be vital to breaking down those barriers. By enabling improved data sharing, workflows, and real-time insights, AI helps teams collaborate and make decisions more agilely and effectively.

    For example, Microsoft shifted its organizational culture by adopting a growth mindset, emphasizing cross-functional collaboration, and leveraging AI to provide data-driven insights to make faster, smarter decisions. This approach allowed the company to fully embrace AI and cloud computing, positioning it as a digital innovation leader.

    Custom graphic showing the differences between growth and fixed mindsets

    Such transformation isn’t possible without leadership-driven change. A culture that supports AI adoption starts at the top with leaders like Microsoft’s CEO Satya Nadella who are open to exploring and investing in new technologies.

    By integrating AI into decision-making processes, you not only can drive change but ensure your team has the tools and insights to support and sustain cultural shifts.

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    The Urgency of AI-Driven Transformation

    Companies that fail to evolve risk being left behind in a rapidly changing landscape. As Iansiti says in AI Essentials for Business: “If you don’t transform, you’re out of here.” This stark reality underscores the urgency of embracing AI and broader digital transformation to compete.

    To prepare for AI’s digital transformation challenges and opportunities, education is essential. With guidance from the industry experts featured in AI Essentials for Business, you can gain the knowledge and skills to lead your organization through its digital evolution.

    Do you want to help shape your organization’s digital transformation strategy? Explore AI Essentials for Business—one of our online digital transformation courses—and download our interactive online learning success guide to discover the benefits of online programs and how to prepare for your educational journey’s next stage.

    About the Author

    Kate Gibson is a copywriter and contributing writer for Harvard Business School Online.
     
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