Illustration by: https://www.istockphoto.com/portfolio/AlexeyYaremenko
With rapid advancements in artificial intelligence (AI), AI leadership is no longer confined to the purview of technical teams. Instead, executives from all sectors must keep up with AI executive governance and drive organizational standards for these emerging technologies.
No matter the industry, AI introduces an unprecedented impact across every job function. This is why leaders must make a concerted effort to understand the concepts and applications of AI. Some senior leaders might seek out executive education programs focused on AI, such as the Stanford Graduate School of Business (GSB) Executive Education portfolio.
When senior leaders help shape organization-wide AI policy alongside technical experts, AI becomes a strategic capability rather than just a technical tool. By using the following framework and questions as a guide, leaders can identify where AI will most effectively improve operations, strengthen competitive advantage, and enhance customer experience.
AI Is a Leadership Skill, Not Just a Technical One
AI advancements are happening faster than governments are able to regulate them. For this reason, AI decision-making occurs at an organizational level and often falls to executive leaders. In the absence of overarching regulations, company-level AI policy should be a collaboration between leaders and their technical teams.
When evaluating new tools and ideating on adoption, executives should consider this framework which includes these three factors for executive AI leadership:
- Strategy – Aligning AI to Business Goals: Conversations about strategy should begin with a survey of business priorities. Once the highest demand workflows and processes are identified, a group of leaders and contributors can determine specific tasks that would most benefit from AI adoption.
- Governance – Oversight and Accountability: Sound business strategy should also inform AI enterprise governance. As processes evolve and workflows emerge, it’s important to establish documentation related to clear guidelines about responsible use.
- Risk – Understanding What Could Go Wrong: Strong leaders must educate themselves on AI risks, such as how human-created bias can skew information, data privacy concerns, and reputational risk that can result from technical missteps. AI misuse can damage brand trust if information is not vetted and data safely secured.
To drive successful adoption, executives must also stay informed about emerging AI technologies and tools. This enables them to guide integration into day-to-day workflows and ensure policies and processes remain agile as AI evolves.
What Leaders Actually Need to Understand About AI
When making informed policies and practices around AI, leaders should focus on understanding the business outcomes of the technology rather than technical aspects. Executives should keep the following considerations in mind when shaping their AI policies.
What AI Can (and Cannot) Do
When it comes to goal-setting and integrating AI tools into established practices, company leaders must familiarize themselves with what AI can realistically accomplish and where there are still limitations. Having a clear sense of where AI advancements are headed will help shape longer-term planning because it will allow leaders to shape employee training and consider plans for workflow implementation.
Although usage will vary organization to organization, executives should be able to explain what AI can and cannot do at a high level:
- Automation: using technology to perform repetitive tasks that streamline processes, such as email triage
- Prediction: forecasting future outcomes based on historical data and machine learning, often used in E-commerce to forecast product demand
- Augmentation: enhancing human performance through new technology, including the use of a virtual assistant that helps answer high-volume customer questions so IT employees can focus on more complex cases
With a general understanding of these foundational usages of AI for executives, leaders will be able to help brainstorm different adoption strategies and conceptualize how they can create overall business value.
Where AI Creates Business Value
Executive leaders must also understand the potential business value that AI can offer to their organization. The rate of change is rapid, but new technologies offer measurable outcomes and efficiency gains across organizational functions.
Operations
AI can help operations teams improve efficiency, reduce costs, and make faster decisions. In particular, AI tools may be useful in supply chain forecasting, customer service optimization, and process automation.
Marketing
Marketing teams benefit from AI’s potential to personalize customer experience, improve targeting, and accelerate content creation. Additional applications may include:
- Search and SEO optimization
- Customer segmentation
- Automated reporting
Finance
Finance professionals may also leverage AI technologies to improve their work. Potential applications include financial forecasting, expense management, and fraud detection. These and other uses can improve risk management and increase financial agility.
Human Resources
For employees in HR, AI can create more data-informed employee experiences. AI is already used for capabilities in many human resources departments that improve talent acquisition, workforce planning, employee engagement, and more.
The Questions Every Executive Should Be Asking
Although most executives will not become experts in AI development, their leadership sets the tone for how new technologies are integrated and how their employees will adopt and use them for strategic workplace tasks. Strategic AI leadership begins with asking the right questions to assess cultural and operational readiness before implementation begins. Developing a critical and yet informed perspective can shape usage and set the standard for best organizational practices.
The following questions can serve as a launching pad for expanding AI implementation at scale.
Aligning Teams Around Strategic Decisions
Consistency in initial strategic decisions can break down silos and pave the way for cross-functional collaboration. To kick off conversations about AI transformation at your organization, consider these questions:
- Are we aligned on why we are investing in AI and on what business outcomes matter most?
- Which teams need to collaborate more closely for AI initiatives to succeed, and what does successful adoption look like across departments?
- How do we evaluate opportunities and risks related to new AI workflows?
Leaders who are seeking more education on making informed decisions may also consider applying for the Stanford GSB Executive Education Harnessing AI for Breakthrough Innovation and Strategic Impact one-week, on campus program.
Investing in Leadership Capability
When it comes to rolling out new AI-informed processes, leaders must possess the confidence to guide new initiatives. The following list of questions can be helpful to begin building leadership capabilities around AI.
- Are we investing in AI literacy only for technical teams, or do leaders across the business understand AI well enough to make informed strategic decisions?
- What skills will leaders need to manage increasingly AI-enabled teams?
- How are we helping leaders build confidence without expecting them to become technical experts?
- Are we fostering a culture of experimentation, curiosity, and responsible risk-taking from the top down?
- How are we facilitating and encouraging AI adoption across the organization?
To build on these initial questions, consider applying for Digital Transformation: Leading Organizational Change in the Age of AI. This program will help leaders learn more about frameworks for implementing AI in a wider digital strategy.
Embedding Responsible AI Practices
As AI use cases expand, the commitment to responsible AI practices cannot waver. These inquiries can form the foundation that leads to ongoing AI policies.
- How are we identifying and mitigating bias, privacy, and security risks early?
- Who owns the decision rights and accountability for AI use across the organization?
- How are ensuring AI is used transparently and appropriately with employees, customers, and stakeholders about how AI is being used?
- How are we balancing speed of experimentation with governance, controls, and brand trust?
- How are we redesigning workflows and roles so people can work effectively alongside AI?
For further training on reshaping culture, operating rhythms, and performance in hybrid human-AI teams, explore The AI-Powered Organization. This program is designed for senior executives leading organization-wide changes as AI reshapes business functions and ways of working.
Leading with Confidence in the Age of AI
Organizations with effective AI adoption are shaped by leaders who bring informed leadership and responsive vision to their work. These leaders are able to see through the hype of new tools and applications so they can make implementation decisions based on real business needs. Rather than technical mastery, today’s leaders are tasked with bringing clear vision and cross-functional support to a new age of technological advancement.
Now more than ever, strong decision-making rests on the foundations of transformational leadership. Stanford GSB Executive Education programs are a pathway for learners to build leadership skills that stand the test of time and innovation. Professionals who complete certain Stanford Executive Education programs will gain mastery of next-level strategic, governance, and risk management skills to lead AI initiatives responsibly.
For the support you need to balance strategy, governance, and risk alongside fast-paced artificial intelligence innovation, explore Stanford Executive Education offerings.
