How leadership can navigate the integration of AI

By Wolfgang Lehmacher

Spoiler alert: I think there are no specific leadership skills and qualities required to navigate the integration of artificial intelligence (AI) into business strategies, models, and operating plans.

Although probably over-hyped, no one can ignore AI any longer. Those actors that do, may soon be forgotten. However, dashing blindly into implementation is also not recommended. Successful AI integration requires a considerate and complete approach, driven by excellent leadership.

Taking the perspective of a chief executive officer, secretary general, or similar, this is how I envisage in 10 points that a set of well-known leadership skills and qualities plays out on the path towards AI integration.

1.?????? Visioning to get started with a well-shaped narrative that inspires the organization and people to get excited about AI, constantly and consistently spread through internal and external communication, making AI a topic of relevance, importance, and hopefully fun across the organization or community.

2.?????? Leveraging the "power of the board", i.e., installing a steward and sponsor of AI-at-large at board level, somebody who makes AI a standard board agenda item facilitating discussions around AI governance, strategy, best practices, experiments, plans, dashboards, execution, and learnings; AI needs to be a board responsibility.

3.?????? Experience with large scale change initiatives and deep understanding of how critical changes in structure and managerial as well as operational processes can support innovation; on the structural side this includes tools like a program office, special (support) task forces, help desks, while on the process side, there are strategic planning, budgeting, reviews, and skilling/training across the organization.

4.?????? Management by objectives and incentives giving AI the right level of attention, signaling to teams and individuals that they need to make room for sufficient reflections, discussions, planning, execution, training, etc. on the topic of AI.

5.?????? Talent acquisition and nurturing: get the right individuals on board and in all rooms across the organization to get AI things right; required talent includes data scientists but more importantly people that have experience in implementing AI which need to be focused on critical challenges and supported by teams across the organization, otherwise they get bored and frustrated and leave again.

6.?????? Overcoming inertia and resistance against change, otherwise the organization will get stuck in data cleansing and AI experimentation, and new models will never be deployed, and old ones never supercharged.

7.?????? Constantly encouraging people and helping them to overcome frustrations and AI fatigue, which will certainly occur on the AI journey.

8.?????? Empathy and active listening to deal with people’s concerns and fears, e.g., about losing the job or AI itself.

9.?????? High energy and drive needed to establish a data-driven culture of learning and performance, as it is culture that eats strategy for breakfast, also knowing that cultural change is one of the hardest things to achieve in an organization.

10.??? Call out and celebrate progress and success to create a ‘yes, we can’ spirit and keep the morale high.

AI integration needs experienced and seasoned leaders. It needs visionaries with courage, able to energize and keep organization-wide initiatives on track. Leaders that drive AI integration don’t need to have AI domain knowledge but the ability to configure teams that have it all and mobilize them for change with perseverance.