Chapter 10: Digital Resilience for AI

Foundation of Digital Resilience

The Reality: Organizations are surrounded by instability and uncertainty in the digital economy, making the ability to recognize and manage change more important than ever. While many changes involve small adjustments, organizations also need to make fundamental shifts across all business activities.

Why This Matters: Success requires a disciplined approach to digital transformation that seeks longer-term systemic change, revolutionizing the organization's structure, strategy, skills, and systems. This is essential for thriving in an AI-driven future.

Perspectives on Digital Resilience

Creating a strong plan is all very well. But, as often quoted, no plan survives first contact with the enemy.

Hence, resilience plays a critical role in the success of any digital strategy. In the context of digital transformation, it is this resilience that determines the ability of an organization to adapt, recover and thrive in the face of unexpected challenges, disruptions or changes in the digital landscape. Its importance was highlighted throughout the Covid crisis, when companies that had invested in a robust digital infrastructure, cloud-based tools and secure remote access capabilities experienced smoother transitions to remote work setups and were able to continue serving customers and generating revenue.

Throughout those difficult times, the importance of resilience for business continuity was clear, and this has not diminished. In fact, it has grown with the continued pressure to find new ways of serving customer needs in an era disrupted by significant economic, political and financial instability. In December 2022 this was recognized by McKinsey in an extensive survey that showed that digital resilience was a priority for the majority of the organizations who responded. Rapid deployment of solutions based on generative AI is only serving to increase this focus.

But what does it mean to be resilient in the face of the kind of disruptive digital change we are experiencing with AI? The starting point for responding to this question is to examine the role of data as the foundation for AI. Data is the fuel for AI, and the utility of AI is directly related to the quality, accuracy and availability of that data. A resilient approach to the way data is gathered, stored, managed and maintained is essential.

Smarter approaches to data-driven decision-making require organizations to build the capabilities needed to bring together multiple data sources.

Establishing a broad approach to data resilience enables the data-driven insight at the heart of machine intelligence (MI). It is the combination of capabilities provided by MI that transforms so much data into genuine sources of new value. It can be seen as a core capability for the digital economy. MI holds out the promise of being able to make sense of large volumes of data by exploiting a combination of machine learning and AI to yield entirely new sources of value. It encompasses natural language processing, image recognition, algorithmic design and other techniques to extract patterns, learn from these by assessing what they mean, and act upon them by connecting information together.

MI is inevitably disruptive by nature. Hence, it is essential to recognize that MI and its associated digital business models may pose significant challenges, which can be addressed in the following ways.

Organizations must tackle several key challenges to successfully implement machine intelligence.

• Changing Data Collection and Processing It is important to move away from localized databases associated with specific applications and form larger data lakes that can be exploited by new layers of intelligence essential to MI success.
• Ensuring Flexible, Scalable Technology Infrastructure Business success requires integrating the many applications that constitute a complex set of workflows by using open, component-based techniques as well as connected platforms such as those provided by AWS, Google, Microsoft, IBM and others.
• Tackling Cultural Barriers Across the Organization Previous technology investment often constrained thinking and encouraged business leaders to cling on to ageing business models and supporting processes. New thinking is required. While many of these changes will be ongoing, MI-based innovations will inevitably put stress on existing organizational structures. Leadership is always a critical element of any major organizational change, and until the key business leaders are convinced of the need for radical change, little progress will be made.

Companies as diverse as major technology providers, large-scale business-to-consumer services providers and industrial business-to-business solutions providers are already seeing the impact of such changes.

This illustrates that effective progress can be made when the corporate culture is receptive to new ideas. Further progress requires a clear plan. Business leaders and management should consider exploiting current technology-driven developments through three categories of activity: research, experimentation and execution. These three prongs are central to a robust data resilience strategy, and a range of different approaches to them are adopted by the most successful organizations.

Strategic Framework

The six-point digital resilience framework provides a comprehensive approach to building organizational resilience in the face of constant digital change. This framework addresses data resilience, technology infrastructure, cultural transformation, and strategic planning to ensure organizations can not only survive but thrive in the rapidly evolving digital landscape.