Gen Z is built for AI x EX

The new AI era is here and demands new leadership models and mindsets.

The 21st Century Problem

Transactional & Extrinsic-focused organizations have produced ultra-low employee engagement it’s never been higher than 38%
The # 1 reason people leave employers is poor corporate culture and bad managers. Learn Intrinsic Self-Motivated Engagement!
Exclusionary hiring practices and cultures left behind the global majority, in this modern century so far, that’s what 2000-2020 did and the whole world knows this. AI Leadership can’t function like that. From Gen X to Gen Z, to develop AI mindsets demands EX, highly engaged employees.

The New Centennial Solution is “Powerfully Human
with AI capabilities!”

AI Leadership produces highly motivated, engaged, and inclusion priority places-of-work. Those work environments are all about EX. EX is the rocket fuel for AI centric companies!
Gen Z has a generational opportunity. Will they be the generation that truly embraces Equality, Equity, and Prosperity for Global Society?

Are you ready?  Let’s  Do  This!

AI x EX-Centric Leadership Developmental Mindsets

Let’s Give You
Let’s Develop Your
Extended Intelligence:
Let’s Construct Your
Mindset for Data:
Let’s Embrace Your
Let’s Give You
AI x EX style:
Let’s Build Your
Foundation to Motivate
inspire Innovation

To succeed in the current, constantly changing and advancing environment, nimble leaders must focus on sensemaking, a set of skills that helps them understand what is happening around them, and reduce complexity. Architecting leaders plan for transformation and help their organizational peers and subordinates develop adaptive capacities and avoid the trap of self-complacency.

In order to be successful in turning data into knowledge and then results, and avoid feeling stuck or overwhelmed with data, leaders must understand what type of data they need as well as its quality and source. That’s not all, there will be many challenges, for example, understanding and integrating AI systems that are compatible with human behavior, and specifically, AI systems that can leverage the manner in which humans use the social information that matters in your organization.

Leadership in nimble organizations looks different than in bureaucracies. It’s more distributed, with people across different units and at all levels of the organization thinking and acting like leaders. Nimble leaders are also skilled at being “incomplete leaders.” Talented leaders know what they are good at—and what they are not — and how to surround themselves with others whose strengths complement their weaker areas.

Leaders must build “human-AI decision systems that extend human intelligence” and that are compatible with human behavior, by understanding how people use social information. Leaders must also architect an agile, nimble organization where AI solutions are used to create the best connections between people and ideas. The goal is not to replace people, but to train individuals and teams to learn from and train AI solutions and engage in continuous improvement.

In order to leverage new generation AI systems and drive organizational performance, leaders must architect a nimble, adaptive organization built on human-machine collaboration, in which teams and decision systems work together to solve complex problems. Leaders must start explaining (and often visualizing) to their team members the decision criteria that the AI systems use. By building awareness of the potential of AI to augment human skills, leaders can transform fear into trust, and improve the adoption rate of these technologies.

As leaders develop their own leadership signature and find their unique signature of combining the key nimble AI-centric capabilities, they also need to model and reinforce ethical standards. High-capacity leaders demonstrate accountability by providing honest and constructive feedback, modeling ethical conduct, accepting mistakes as opportunities to learn, and illustrating the outcomes of unethical or illegal behaviors.

Learn with AI

Create right mindset

Foster human-machine


Map existing competencies

Conduct gap-analysis

Integrate machine learning

Organizational learning

Invest in people, teams, and technology

Create sense of urgency

Build guiding coalition

Form strategic vision

Enlist volunteer armies

Remove barriers

Generate short-term wins

Sustain acceleration

Institute change

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