In the rapidly evolving landscape of generative AI, many companies are experiencing a tug-of-war between the urgent need to adopt AI technologies and the imperative to mitigate potential risks. While this tension, when managed effectively, can foster innovation and resilience, mismanagement could lead to significant challenges and costs.

PwC’s latest “Early Days” Generative AI report delves into how organizations can strike the right balance. Learn how to cultivate healthy tension and explore the six key priorities that leading companies are focusing on to navigate the complexities of AI adoption effectively.

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PWC Insights on Early Days of Generative AI Adoption

Organizations are at the “early days” of generative AI adoption, grappling with both the rapid pace of innovation and the associated risks. In a recent discussion, a CIO from a major healthcare company was prompted to reevaluate her organization’s AI strategy, leading to the development of a focused set of priorities.

These priorities include balancing risk management with the need for speed, aligning generative AI strategies with existing digital frameworks, encouraging scalable experimentation, and strategically leveraging productivity gains.

Additionally, leaders are focusing on preparing employees for the AI transition and collaborating with ecosystems to rethink value chains and business models. As organizations navigate this evolving landscape, they are learning and adapting in real time, setting the stage for successful AI integration.

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Do you have an “early days” generative AI strategy?

Organizations at the forefront of generative AI adoption address six key priorities to set the stage for success.

In a recent conversation about generative AI with one of our colleagues, the CIO of a major healthcare company laid out a wide range of issues that concerned her: risk protocols, use case development, cybersecurity, ethics and bias, training and development, and many more. After a few minutes, our colleague asked the client to take a step back: “How clear are you on what you are trying to accomplish, and why? In other words, do you have a strategy?” These questions stopped the CIO, leading her to call a series of meetings with key leaders, and ultimately the board, to create a sharper set of objectives. What emerged was a group of priorities that collectively formed what might be termed an “early days” AI strategy.

Early days, because—let’s face it—that’s exactly where we are with generative AI. It was only in November 2022 that the consumer release of ChatGPT captured the world’s imagination. Since then, organizations have been struggling to keep up with the pace and potential they see in this new, general-purpose technology application. Some organizations are doing better than others, and it’s not too soon to start taking stock of early leaders that are leveraging generative AI to capture value and pull ahead. Across industries, we’re seeing these leaders tackling a number of critical priorities:

• They’re navigating tensions between the need for prudence and risk mitigation, and the importance of moving quickly to grab emerging opportunities.
• They’re aligning their new generative AI strategy with their existing digital and AI strategies, building on these foundations to guide their thinking rather than starting from scratch.
• They’re thinking big—encouraging experimentation across their organizations, with a focus on identifying use cases that can scale.
• Rather than simply looking for ways to improve productivity, they’re looking strategically at their options for putting productivity gains to use.
• Relatedly, they’re considering impacts on workers, roles, and skills-building, determining how best to both prepare employees to take advantage of the new tools available and include employees in shaping the company’s generative AI journey.
• They’ve realized that with such a potentially disruptive technology, teaming up and collaborating with their ecosystems can be a truly transformative route to a radical rethink of their value chains and business models.

In many cases, these priorities are emergent rather than planned, which is appropriate for this stage of the generative AI adoption cycle. Leaders and organizations are learning as they go.

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Priority 1: Manage the AI risk/reward tug-of-war

Priority 2: Align your generative AI strategy with your digital strategy (and vice versa)

Priority 3: Experiment with an eye for scaling

Priority 4: Develop a productivity plan

Priority 5: Put people at the heart of your generative AI strategy

Priority 6: Work with your ecosystem to unlock even bigger benefits

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