The ‘Inter-AI’ Period: 7 Key Actions Leaders Should Take Now 

Generative AI is not transient, part of a hype cycle, or a fleeting trend. It’s a game-changing innovation that’s opened the door to novel human-machine partnerships, AI-driven superintelligence, and a new way to win in business.

In the AI timeline, we’ve entered “The Inter-AI Period,” a small window of opportunity where leaders can shape how they use AI now and in the future. This window of opportunity is short—perhaps a few years at most—after which decision processes embedded in AI will harden.

For leaders, this period is also an opportunity to establish oneself as a transformative AI leader—or a follower.

One example of such a leader is Satya Nadella, who became CEO of Microsoft in 2014 and drove the company’s shift toward AI and cloud computing. His leadership has been characterized by:

• A Strategic Vision: Nadella clearly sees AI’s role in shaping the future. He has steered Microsoft toward becoming a leading player in AI and cloud services, all while emphasizing the importance of innovation and customer-centric solutions.
• Cultural Transformation: Nadella has fostered a culture of inclusivity, collaboration, and continuous learning. He encourages employees to adopt a growth mindset, which is crucial for embracing new technologies like AI.
• Ethical Responsibility: Nadella is a strong advocate for ethical AI. Under his leadership, Microsoft has prioritized responsible AI development, focusing on transparency, fairness, and accountability.

By studying transformative AI leaders like Nadella and conducting interviews with dozens of corporate CEOs, we’ve identified seven key actions every leader should take now:

1. Educate Yourself and Your Teams
   AI is evolving at lightning speed, so you must develop a way to keep up with the latest AI trends, technologies, and applications. Identify conferences, webinars, or workshops to understand AI’s potential impact on your industry.

   Another approach is to deploy internal AI training programs. For example, Microsoft invests heavily in training its employees on AI and machine learning. The company launched the first-ever AI Business School, offering courses on AI strategy, culture, and responsibility. Microsoft also collaborates with universities and online learning platforms to offer AI training and certification programs.

   The key is investing in continuous learning to build AI literacy across the organization.

2. Develop a Clear AI Strategy
   Your organization can’t chase every AI initiative, so you must define how AI can support your unique business goals. Identify specific areas where AI can add value, such as improving customer service, optimizing operations, or creating new revenue streams. Then, develop a strategic roadmap, outlining the steps needed to implement AI. This should include timelines, resource allocation, and key milestones.

   For instance, Microsoft has embraced an initiative called “AI for Good,” which focuses on using AI to address societal challenges such as healthcare, sustainability, and accessibility. Microsoft strategically acquired AI companies like Bonsai, Lobe, and Semantic Machines—which collectively focused on making AI more accessible to non-experts—to enhance its consumer and business AI products and services.

3. Foster a Data-Driven Culture
   High-quality data is essential for a successful AI implementation, and the adage of “garbage in, garbage out” has never been more true. Ensure your organization has robust data management practices; collect, store, and analyze data effectively; and promote data literacy among employees. Help them understand the importance of data and how it can drive decision-making.

   To help tackle this challenge, Microsoft developed Azure AI, a comprehensive set of AI services and tools that help organizations build and deploy AI models. This platform supports a data-driven approach and enables businesses to leverage AI efficiently. Microsoft ensures robust data governance practices, emphasizing data privacy and security. The company has implemented strict policies to manage and protect data, fostering trust among users.

4. Invest in the Right Technology and Partnerships
   Will your current technology infrastructure support your AI initiatives? Now is the time to assess your cloud computing and data storage solutions. A good strategy is to partner with AI experts, consultants, and technology providers who can provide valuable insights and accelerate AI adoption.

   Again, Microsoft is a great example here. The company invests significantly in AI research, with dedicated research labs and teams working on advanced AI technologies. Microsoft also collaborates with other tech giants, startups, and academic institutions to advance AI research and development. Its partnerships with companies like OpenAI have led to significant advancements in AI capabilities, as showcased in its chatbot powerhouse, ChatGPT.

5. Pilot Projects, Then Scale Up
   Given AI’s steep learning curve, it’s essential to start small. Begin with pilot projects to test AI applications on a smaller scale. This allows you to learn and refine your approach before scaling up. Then, measure and iterate, continuously measuring the performance and impact of your AI initiatives. Use feedback to make necessary adjustments and improvements.

   Even AI giants like Microsoft follow this approach. Microsoft integrated AI into all its products, such as Microsoft 365, Dynamics 365, and the Azure cloud platform. Features like AI-driven insights, predictive analytics, and automation help businesses enhance productivity and decision-making, but these features keep getting refined along the way.

6. Build a Cross-Functional Team
   Assemble a team with diverse expertise, including data scientists, engineers, business analysts, and industry experts. This ensures a holistic approach to AI implementation. Encourage collaboration between different departments to leverage AI effectively. Cross-functional teams can identify unique opportunities and drive innovation.

   AI leaders like Microsoft understand this. Microsoft is known for its cross-functional teams of data analysts, software engineers, domain experts, ethicists, and UX designers. The company fosters a collaborative culture with agile methodologies, integrated tools like Azure AI and GitHub, and regular communication.

   This structure has propelled Microsoft to the top position in multiple AI industries, including healthcare, where multidisciplinary teams work with medical professionals to ensure better health outcomes.

7. Emphasize Change Management
   Don’t underestimate the importance of clearly communicating the vision and benefits of AI to your organization—and doing so on an ongoing basis. Right now, there’s tremendous anxiety and fear about AI. It’s up to leaders to help employees understand how AI will not only impact their roles but also help them.

   Provide support during the transition to AI-driven processes. Offer training, resources, and assistance to help employees adapt to new technologies and workflows.

   A great example of AI change management is Microsoft’s integration of AI into its Office 365 suite, particularly through the introduction of Microsoft Copilot. This AI-powered assistant leverages machine learning to enhance productivity by providing intelligent suggestions, automating routine tasks, and offering real-time data insights.

   To manage this change, Microsoft implemented extensive employee training programs to ensure users could fully utilize these new AI capabilities and not be afraid of them. They established feedback loops with customers to continuously improve the AI functionalities based on user experiences. By embedding AI in familiar tools and providing robust support and communication channels, Microsoft successfully facilitated the adoption of AI. This process enhanced productivity while maintaining user trust and satisfaction.

The bottom line

The future belongs to those who embrace AI. By taking these steps today, you can unlock a new era of human-machine collaboration and propel your organization to the forefront of innovation.

Written by Nada R. Sanders, Ph.D.

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