When a friend and I produced The Inner Circle series on YouTube in 2023, our aim was to explore how Artificial Intelligence (AI) was shaping conversations and communication, the potential changes it would bring for reputation and risk taking and the implications of AI for organizational storytelling.

What got reiterated through that series, more than anything else, was how being a thoughtful AI leader would positively shape the landscape forward for organizations.

With the introduction of anything new – new processes, new technology, new strategy – business leaders need to build a foundation of trust with their stakeholders and establish authentic relationships in business communication and public engagement. Leaders must communicate intentions and goals to the organization and garner support from stakeholders, ensuring that everyone shares the same vision. 

In today’s AI-powered world, leaders must first understand AI’s potential benefits and risks and how it fits into their business strategy so they can garner support. Sharing anecdotes, examples of applications and use cases are among the best ways a person or a brand can establish trust.  Facts and figures go to the head while stories go to the heart – leading to engagement and helping to drive outcomes.

Balancing curiosity and caution

Marketoonist CEO Tom Fishburne mentioned in his June 2023 newsletter how one of Proctor & Gamble Company’s attorneys talked about the challenge of balancing urgency with safeguards at a time of digital transformation during a digital transformation summit and that she shared a model about providing “freedom within a framework.” 

Boston Consulting Group Chief AI Ethics Officer Steven Mills advocated for a “freedom within a framework” type of approach for AI in an article in CIO Magazine on “Generative AI’s change management challenge”.  As he put it:

“It’s important that folks get a chance to interact with these technologies and use them; stopping experimentation is not the answer.  AI is going to be developed across an organization by employees whether you know about it or not…Rather than trying to pretend it won’t happen, let’s put in place a quick set of guidelines that lets your employees know where the guardrails are … and actively encourage responsible innovations and responsible experimentation.”

Leaders and organizations can encourage curiosity around the use of AI tools by showcasing how they are incorporating them into their workplace and co-creating the process redistribution with the employees and stakeholders.  

For instance, Open Lab, a sustainable fashion initiative, has introduced an AI powered sorting system to help speed up garment recycling processes, in collaboration with its cross-industry partners, global retailer H&M and the Hong Kong Research Institute of Textiles and Apparel. Previously the process was labor-intensive, posed health risks for workers and it was difficult to maintain hygiene standards. The smart system can categorize the fabric of old clothes it processes by pattern automatically before they are turned into new yarn, which helps reduce the time and manual effort of the recycling process.  

Sharing examples like this can sharpen the use cases, help organizations learn from each other and build trust with the stakeholders. AI can be seen as a double-edged sword – on the one hand, there is a fear of AI taking over the world, and on the other, there is the risk of reckless adoption without proper governance.  Organizations are sitting on this see-saw of being AI-cautious and AI-curious and trying to find the balance.

One of the safeguards that Salesforce suggested is “human-in-the-loop”workflows. Two architects of Salesforce’s Ethical AI Practice, Kathy Baxter and Yoav Schlesinger, put it this way in the Harvard Business Review: “Just because something can be automated doesn’t mean it should be.  Generative AI tools aren’t always capable of understanding emotional or business context, or knowing when you’re wrong or damaging. Humans need to be involved to review outputs for accuracy, suss out bias, and ensure models are operating as intended. More broadly, generative AI should be seen as a way to augment human capabilities and empower communities, not replace or displace them.” 

Data work – creating or refining the raw material at the heart of AI?

For example, organizations like Karya are working to create ethical data, creating or refining the raw material at the heart of AI and helping with debiasing. Like its competitors, Karya sells data to big tech companies and other clients at market rates. But instead of keeping much of that cash as profit, it covers its costs and funnels the rest toward the rural poor in India. Karya partners with local NGOs to ensure that its jobs go first to the poorest of the poor, as well as to historically marginalized communities. 

In addition to the hourly minimum rate, Karya gives workers de-facto ownership of the data they create on the job, so whenever it is resold, the workers receive the proceeds on top of their past wages. It’s a model that didn’t exist anywhere else in the industry in 2023 and will be closely watched to see how they walk the talk.

Change in workplace dynamics

Ian Bogost’s observation in 2023 in an article in The Atlantic titled “ChatGPT Is About to Dump More Work on Everyone” has stuck with me. “As organizations scramble to incorporate AI, no one knows quite how AI will impact the future of work,” Bogost wrote. Will productivity gains be offset by, as Bogost put it, AI’s “inevitable bureaucratization”?

A more upbeat note came from Nvidia CEO Jensen Huang at a 2023 commencement address at National Taiwan University.  Huang said that “2023 is a perfect year to graduate” and that graduates will be able to “take advantage of AI and do amazing things with an AI copilot by your side.” Huang then voiced a sentiment many of us would have heard. “While some worry that AI may take their jobs, someone who’s expert with AI will.”

While Huang envisions AI as a copilot, others warn of unintended consequences—making governance critical. Some of the biggest open questions about AI disruption involve the organizations of the future, what skills are required, and the impact of productivity. Not even leadership is immune to the potential impact. Alibaba Founder Jack Ma once predicted in 2017 that in the future (30 years later, he said)  “A robot will likely be on the cover of Time magazine as the best CEO.”

Leadership requires a balanced approach – forward thinking business aspirations, an AI-augmented and yet human-centric workplace – that focuses on business outcomes while promoting learning, experimentation, and curiosity. I saw an example of this recently when I was listening to a webinar on rethinking talent management in the age of AI.  

One of the panelists – Patrick Yu, Vice President, People and Managing Director, Southeast Asia of Lalamove, talked about how, at 30 years of age, he is one of the oldest in his organization. Given the nature of the business, he tends to listen to the young computer engineers who were using AI to code for optimization.  But his role as a leader, he said, was to ask the right questions to ensure alignment with business priorities.  

Computer pioneer Alan Kay is often quoted saying: “The best way to predict the future is to invent it.” Referring to this, Satya Nadella, CEO of Microsoft Corporation says, “In the AI context, he’s basically saying, Stop predicting what the future will be like; instead, create it in a principled way. I agree.” 

With AI firmly in the co-pilot’s seat, business leaders need to answer the following questions: 

• What can we do to restore or build a trusting relationship with customers? 
• What stories are stakeholders telling about us or our business?
• What are the questions you are asking about AI? 
• Where do you see AI playing a part in leadership attributes? 

Asking these questions of ourselves will ensure organizational actions around AI are not just safe and secure but remain under human control.

Leadership is about sensemaking, not just surveillance – the human touch adds capability, builds trust and shape culture. AI can take care of the volume while humans can add value and the much-needed nuance to facilitate conversations. A 2025 Deloitte research paper on the “State of Generative AI” concludes, “Building trust is not just about technology acceptance—it’s about creating the type of organizations we want to belong to, and the type of world we want to live in.”

When Melinda Gates was asked to nominate someone for the Financial Times’ 25 most influential women of 2024, she chose Dr. Fei-Fei Li, the Stanford Professor, known as the godmother of AI for her pioneering work in artificial intelligence (AI), particularly in computer vision.  Not only did Fei-Fei Li help develop AI as we know it, but she is leading the charge to make sure it is used to advance human dignity through AI4All, an American nonprofit that is transforming the pipeline of AI practitioners and creating a more inclusive, human-centered discipline.

As Melinda says, “AI is such a powerful tool.  We need leaders with moral sensibilities like hers to make sure power is used to serve humanity.” 

Just as The Inner Circle explored AI’s role in communication, leaders must now craft narratives that align technology with humanity’s values – start by understanding the tools available, co-create and co-design the experiences and reinforce human connections through communication and storytelling. This is the job forward for leaders – this is the job forward for humans.

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