5 ways to bridge the gap on AI

"Getting those [executive leaders and middle managers] on the same page about their organizations' AI transformation is not simply a communication exercise," the authors write. "It requires executives to acknowledge that the conditions they have created — or failed to create — will determine whether their AI aspirations make it off the ground."

Rather than investing more in technology or developing a bolder vision for AI, the authors recommended executive leaders turn their attention inward to managers and provide them with sufficient support, clarity, and bandwidth to effectively execute AI-related goals.

Five concrete actions that leadership teams can take to close the "messy middle" and align on AI are:

1. Determine where your teams stand on AI.

Consider where your organization is on its AI transformation journey. Do managers and teams understand and embrace your goals for AI? Are there any teams in your organization that are more ready or more resistant to add AI to their workflows?

"You can't close a gap you don't see, and without intentional evaluation, executive leaders' enthusiasm may muddy their grasp of their organizations' realities," the authors write.

2. Collaborate with managers on your AI roadmap.

Although executives should promote their vision and goals with AI, they should also listen to managers' practical concerns and inputs. Leaders should bring managers into roadmap discussions before making any concrete decisions, not after. This helps ensure that all levels of leadership are aligned on a common path when it comes to implementing AI.

5. Create upward feedback loops.

"Many of the gaps we're seeing indicate a critical need for middle managers to align with their executive leaders," the authors write. Leaders can create shared performance measures to guide discussions on what is and isn't working. They can also create structured channels where managers can report any implementation issues and show that cautious assessments or failed pilots provide valuable data.

Overall, "[l]eadership's job is to help move from 'AI is possible' to 'AI is practiced,'" said Ana White, chief people and AI enablement officer at Lumen. "Most successful transformations aren't top down — they're won or lost in the day-to-day realities that managers navigate under real constraints. AI transformation has to reflect cultural and human realities, not just executive ambitions."

Leaders need to own the 'messy middle' of AI

By John League

The five steps outlined above require leaders to answer a powerful and challenging question: "How am I complicit in this problem?" This is not a new question for leaders. It is potentially not a comfortable one. However, it is not a question that can be ignored — for any issue, not just AI — if an organization is to make progress on things that matter.

The specific leadership move needed to address this issue isn't unique to AI, but the urgency and investment in the technology is making it increasingly imperative: leaders must cultivate a strong holding environment. This is the metaphorical "container" that holds the team together while it is working through change, and it includes the people, purpose, and context of the team's work together. It's easy for the environment to function properly when everyone is happy, or when everyone is in agreement about why the work is important and how to do it. But what happens when someone in the team is confused? Or feels threatened? What if they disagree with their leader about how useful or effective AI is?

The assumption of a strong holding environment is baked into the five steps above, but it pays dividends as an ongoing practice and not just as a one-time repair to address alignment challenges.

Leaders can strengthen the holding environment and address any mismatches between executive's and manager's expectations and goals by:

• Building a strong sense of shared purpose and trust at individual, team, and enterprise levels. This is essential for determining where your team stands on AI.
• Drawing a clear line of sight from action to aspiration. Leaders should make this their foundation before collaborating with managers on AI. It also provides a reason to measure readiness and not only adoption. 

After that, leaders can begin to show their responsiveness through:

• Protecting dissident voices. This will allow them to access valuable information on what is and isn't working, even and especially from failures.
• Allowing and encouraging smart risk taking. This will help your teams experiment with AI in novel ways.

Once these conditions are met, leaders can then begin to question existing assumptions —their own assumptions about AI's effectiveness and impact and those of their teams. Without a strong holding environment, it may be both too risky for a manager even to acknowledge misalignment to the leader and too threatening for the leader to probe a manager's position on ROI.