Artificial intelligence is no longer a future consideration for business leaders. It is actively reshaping how decisions are made, how work gets done, how organizations scale, and how employees interact with their leaders. The pressing issue for executives is how AI changes leadership itself, and what they need to do to survive and thrive in an AI-driven economy.
AI in leadership refers to how executives lead organizations when artificial intelligence plays an active role in analysis, execution, and coordination.
In leadership in the age of AI, executives define goals and values for the company, and AI systems (including AI agents) carry out tasks within those boundaries. This represents a shift from direct oversight to directional influence.
This shift changes how leadership impact is measured. Success is now tied to how effectively leaders enable intelligent systems to support teams and customers. AI in leadership elevates the executive role by freeing leaders to focus on judgment, long-term strategy, and complex trade-offs that machines cannot resolve on their own.
Most of us think of AI as those chatbots that answer questions or write content. But AI agents take things way further. Marie Haynes puts it simply: "An agent is an AI tool that can do things for you, that can take action for you."
From an AI in leadership perspective, agents shift the leader’s role from managing execution to governing systems. Leaders must understand how these agents operate, how they interact, and where oversight is required to ensure outcomes align with business objectives.
What makes agents different from your regular AI tools? They can:
This isn't just theoretical technology. Google CEO Sundar Pichai recently predicted that "within two to three years, agentic solutions will be deeply embedded into our workflow." Similarly, DeepMind CEO Demis Hassabis stated that agents will "fundamentally change how we use the internet within the next couple of years."
Why are these specialized AI helpers so powerful for leaders? Haynes explains it's like building a team: "Each of these will be trained to do one specific role and do that role well. And then eventually these agents will talk to each other and combine, get things done by working with each other, just like a company."
The real game-changer here is how these agents will talk to each other, and what that means for leaders. Google just announced an agent-to-agent protocol that lets different AI systems communicate and work together.
Imagine onboarding a new employee. Instead of scheduling meetings with HR, payroll, and IT, an onboarding agent would coordinate with specialized agents in each department to handle all necessary tasks. As Haynes described, "a lot of the administrative tasks in a company become much quicker to do because of agents. You have to do less paperwork. You don't necessarily need people there to answer questions."
This new aspect of AI in leadership requires executives to think differently about accountability in these scenarios. While agents may execute tasks, leaders remain responsible for the systems that enable them. Clear ownership, escalation paths, and governance structures are essential as automation in their companies increases.
And, this isn't just about automation in the traditional sense. These systems actually understand their domain and can handle unexpected situations. Paxton Gray makes this distinction clear: "It's not the automation of work... it's automation with the knowledge domain behind it."
So what should leaders do to get ready? Haynes has some practical advice: "Encourage all of your employees to be using AI in some capacity at least once or more times a day."
Think of it like learning a new language – you can't get fluent by studying once a month. Regular practice builds competency across the team you lead and helps identify practical applications specific to your business.
Another key recommendation for leaders is designating someone to track developments in AI – essentially creating an AI opportunity scout for your organization. This person can filter through the constant stream of updates and identify which ones actually matter for your business.
The current moment resembles social media's early days around 2005. Back then, businesses couldn't immediately capitalize on platforms like Facebook, but forward-thinking companies were positioning themselves for the shift that was coming. Similarly, today's experimentation with agents builds capabilities that will pay off as the technology for AI in leadership matures.
Expect some bumps along the way. The path to effective implementation of AI in leadership isn't about flipping a switch – it's an iterative process of learning, adjusting, and improving. The organizations that start this journey now will develop valuable expertise that late adopters will struggle to match.
As AI becomes embedded in organizational operations, leaders must develop traits that support effective decision-making in intelligent environments. Traditional management skills are still valuable, but additional capabilities must complement them.
One of these new capabilities is systems thinking. To successfully lead in an AI-driven economy, leaders must understand how people, data, and AI systems interact across the organization. This includes recognizing dependencies, risks, and unintended consequences that may arise when systems operate autonomously.
Leaders also need to develop the ability to make judgment calls under uncertainty. AI can surface insights and recommendations, but leaders need to evaluate their context, ethics, and long-term impact to decide when to trust and when to challenge AI outputs.
And, leaders need to place added focus on adaptability. AI capabilities evolve rapidly, and leaders must be comfortable experimenting, learning, and adjusting their approach over time. These three traits form the foundation of AI in leadership.
AI transformation never happens by accident. It occurs when leaders decide to engage, experiment, and lead from the front. For AI in leadership, transformation starts when executives stop treating AI as a side project and begin treating it as a leadership priority.
Leaders drive AI transformation by setting a clear direction. That means defining where AI should create value, where it should not be used, and how success will be measured. When leaders connect AI initiatives to real business goals, teams move faster and with more confidence. Without that clarity, AI efforts stall in experimentation mode.
Just as important is modeling behavior. Leaders who actively explore AI tools, ask better questions, and share what they are learning signal that experimentation is encouraged. In leadership in the age of AI, credibility comes from active, involved participation.
The best leaders balance momentum with responsibility. They create space to test new ideas while establishing guardrails around ethics, risk, and accountability. AI transformation for leaders means guiding change, shaping judgment, and helping their organization learn its way forward.
AI-ready leadership teams are developed carefully through shared understanding and a willingness to adapt. In AI in leadership, readiness is less about technical expertise and more about how leaders think and work together.
Strong AI-ready teams start with a common baseline of AI literacy. Leaders do not need to understand how models are trained, but they do need to understand how AI systems influence decisions, workflows, and accountability. When leadership teams share that understanding, alignment improves, and friction decreases.
Using AI in leadership development plays an important role here. Organizations that encourage hands-on use, regular discussion, and cross-functional learning help leaders build confidence over time. Designating internal AI champions or working groups can accelerate this process by translating technical progress into strategic insight.
The organizations that succeed in the next phase of AI adoption will not necessarily be those with the largest budgets. They will be directed by leaders who invest early in understanding AI, experimenting responsibly, and building organizational literacy.
AI in leadership is an ongoing journey rather than a one-time initiative. Leaders who engage with the technology today develop instincts and capabilities that will compound over time. As AI agents become more embedded in business operations, these leaders will be positioned to guide change with confidence.
If you want to understand how AI is shaping your organization and where opportunities exist, a structured assessment can help clarify next steps.
Get a free AI audit to evaluate your current readiness, identify leadership gaps, and uncover opportunities to apply AI strategically across your organization.
