Insight
Starting to develop a strategy is a crucial step for increasing organizational readiness, but it is not enough on its own
Given the importance of leadership in driving preparedness for the challenges that AI could bring, it is no surprise that leaders are taking action to increase their organizational readiness. To lead their organization through this change, leaders have shared personal learning, or understanding of AI, as an initial step to be able to undertake any change efforts. At the forefront of these efforts is developing a strategy—more than three-quarters of respondents are taking this step, even though there is no clear blueprint for leaders to follow. While leaders may feel unsure of the next steps in the face of the transition, it is clear from our conversations that making a start with adoption, even amidst uncertainty, is better than not starting at all.
“You better embrace it as a business leader because, if not, your competition and the rest of the market is going to absorb the necessary dynamic capabilities in real-time, and you’re going to be lethargic and left behind.”
Bill Anderson, Bayer AG
However, this action alone is not enough—especially as strategy development is inherently tricky against an uncertain and constantly changing picture of possibilities and risks. Only 14% of respondents reported that strategy development was their sole focus, with the majority saying that they are taking additional actions, including investing in infrastructure (49%), building external partnerships (44%), and recruiting experts (39%).
While AI is acknowledged to have significant disruptive potential, its opportunities may still be greater. Companies take these risks and opportunities seriously, as evidenced by a thirteenfold increase in AI-related corporate investments in the last decade. However, more than a business-as-usual approach will be required to ensure that an organization will thrive in the age of AI. Profound change and strong cultural development will be needed, which will not happen if leadership isn’t at the forefront. We believe that the disruption does not start with strategy or operations, but with leaders themselves. The more they can adjust their professional identity as they embrace AI, the greater the transformation that will occur.
Business leaders can act boldly and strategically to achieve organizational readiness for AI. That will require a deep understanding of current market capabilities and possible gaps in capability within themselves and their organizations. Our conversations with leaders highlighted five key ‘success factors’—they can serve as cornerstones for leaders as they drive AI adoption strategies (see Figure 7).
Five Success Factors
Figure 7
- Business case development. Evaluate the potential for value creation meticulously. This involves a comprehensive assessment of benefits, costs, practicality of implementation, and associated risks before deploying generative AI applications. By prioritizing value creation, leaders can ensure the adoption of effective AI initiatives.
- Data quality management. Prioritize the integrity of data. It is crucial to ensure that the data fueling generative AI is accurate, complete, and free from biases to yield dependable and valuable results.
- Security controls. Establish a robust data security framework. This should include defining user access levels and security measures that adhere to governance, compliance, ethical standards, and privacy regulations.
- Architectural design. Craft an architectural framework that is inherently scalable. This design should be capable of evolving to meet the demands of future use cases while remaining in line with the organization’s core principles and values.
- Change management. Develop a robust change management strategy. This strategy should ensure a smooth transition and integration of generative AI into existing workflows, fostering acceptance and operational harmony. Maintain a people-focused approach during this change, ensuring that all technological changes serve the individuals they are meant to enable.
“AI is like a new colleague. They need to be trained, you have to give them clear work assignments and take your time with them!”
Marianne Janik, Microsoft
“To embrace the change within a big organization, you need to have a clear vision, but you also need the organization and the infrastructure to support it.”
Béatrice Guillaume-Grabisch, Nestlé
“Leadership needs to stay close to tech trends through personal initiative (do not outsource!) and continuously invest in several smaller projects to explore new trends. These projects should be supported ‘bottom-up’ to make the team realize these opportunities firsthand.”
Ron Lior, Uber Freight
“You need to show people examples of success in order to get people onboard.”
Mark Rose, Avison Young